Factors Blog

To make the B2B terms glossary easier to read and follow, we have decided these b2b terms into four broad categories:

Such categories include:

1. Measurement and Analytics
2. Content and Lead Generation
3. Strategy and Planning
4. Sales and Customer relationships

I. Measurement and Analytics:

1. A/B Testing

A/B testing or split-testing is a way to improve engagement and conversion rates, by experimenting using 2 variants of an element with 2 separate audiences to measure & compare the user response to each. For example - testing two versions of a webpage or email and choosing the one that leads to more conversions. A/B testing is more about comparative analysis of the two set groups, providing an insight as to which variant works more effectively than the other.

2. Analytics 

Analytics is the process of finding patterns and sequences and extracting relevant information from data sets. It is used  by companies and softwares to analyze user engagement, marketing effectiveness and engagement rates. Analytics help a company or a user in measuring marketing insights, evaluate trends and judge the effectiveness and engagement rates of their platform. Various analytical tools help the companies in designing the product and put together effective marketing strategies.  

3. Application Programming Interface (API) 

APIs are a series of defined rules that streamline communication between different applications. In layman’s terms, APIs are essentially clearly defined methods of communication between various software components.  APIs act as an intermediary layer that facilitate data transfers between systems and softwares giving the company a more detailed  understanding over the functionality of their softwares, traffic and data inputs.

4. Big Data 

Huge amounts of structured and unstructured data which can be analyzed by various tools and traditional methods for the likes of scraping and visualization etc. Put simply, it is a chunk of a variety of different data compiled into one which needs to be differentiated, segmented and analyzed individually to gain some insight. Big data helps in lead generation, designing marketing models and predicting customer behavior. 

5. Bounce Rate 

It represents the percentage of visitors who enter the site and then leave (“bounce”) rather than continuing to view other pages within the same site. If the bounce rate is extremely high for a landing page, it probably means that the design and call-to-action of the page are not consistent or, it could simply mean that the website content is not relevant and particularly useful for the visitor. Companies design their websites in such a way in order to minimize this bounce rate and generate more inbound leads through SEO, marketing techniques and paid advertisements.

6. Buyer’s Journey 

(synonymous with adoption process)  It can be understood as a complete path taken by a customer right from the first click on the website to the point of being onboarded or buying the said software. It traces the journey right from the inquiry phase to the decision stage. However, it should also be noted the buyer’s journey may also begin from a channel other than the website, say a pop-up ad or direct call or emails sent out by the company.  

7. Click Through Rate (CTR) 

The percentage of people that view an ad and that click on it. A useful metric for measuring the effectiveness of a call-to-action or a pay-per-click ad i.e., paid advertising  A high CTR is not the only indicator of a good paid ad. Similarly if the CTR is high does not necessarily mean that the ad is great. A host of different factors come into play while calculating the relevance and usefulness of the ad.

8. Content Management System (CMS) 

An application that is used to publish, edit, modify, organize, and delete web content in one centralized interface. Common content management systems include WordPress, SquareSpace, and HubSpot. There are also content management systems that are specialized for social media like HootSuite

9. Conversion Path 

The path that website visitors follow to become a lead. It can be understood as one of the many aspects of the potential  “Buyer’s Journey” . It traces out the complete step by step procedure taken by the visitor on the website. Analyzing it gives the company a brief profiling of the visitor and helps the company to know what content of the website is working and what is not. Conversion path is closely measured by the company to track its marketing sales techniques. . 

10. Conversion Rate 

The percentage of website visitors that convert into leads. Here, leads should not be understood as being synonymous with buyers. Leads are visitors who can be potential buyers. Sometimes they may be converted into customers directly and in some cases the company needs to pursue them further  in order to onboard them..

11. Cornerstone Content 

extremely deep content focused on a high-value keyword that is then linked to by other related pieces throughout the site. This is a technique used to rank for competitive keywords.It may highlight a description of your product,  blogs, frequently asked questions and certain keywords.

12. Customer Relationship Management (CRM)

 CRM is a system for managing a company’s interactions with current and future customers. It includes the marketing techniques, customer policies and sales measures employed by a company in order to rope in new customers and maintain good relations with the existing ones. There are many CRM software systems, two well-known ones are Salesforce and HubSpot.

13. Customer churn

Customer churn rate measures how many customers your business has lost in a given time period. It is an important metric to track both your monthly and annual churn rates and provide knowledge on your customer retention across different dates & time periods. It helps keep track of customers gained and lost over a certain period of time. 

14. Customer Lifetime Value (CLV) 

 This is the average amount of money that your customers pay during their engagement with your company. The metric shows average customer worth & provides businesses with an accurate portrayal of their growth potential. It is an important metric for a company to track its costs and the returns it expects on its marketing and selling expenses. Since B2B businesses have a longer sales cycle ranging from days to months, tracking the CLV is important for a company to understand how much it should be spending to gain a customer.

15. Customer Acquisition Cost (CAC) 

 Shows exactly how much it costs to acquire new customers and how much value they bring to your business. When combined with CLV, this metric helps validate the viability of your business model, measure cost and maintain a healthy profitability margin.

16. Form 

A form should be on every landing page. A form is what turns a website visitor into a lead. A form consists of form fields that the viewer fills out to download the offer. At the very least, a form should have a form field to capture the viewer’s email. The email is the primary identifier of any lead. 

17. Disavow Tool 

In 2012, Google released the disavow tool which allowed website owners to “disavow” spammy backlinks that were pointed to their site thus making website owners responsible for their link profile. A high number of spammy links pointing to your website can hurt your search ranking, and in some cases be a reason for Google to place a penalty on your domain. 

18. Marketing Automation (MA) 

 A process or technique through which marketers handle all their marketing channels (website, blog, social media, email, contacts) in one place. Some of the prominent MAs are HubSpot, Marketo, Pardot, and Sharp Spring.

19. Marketing Qualified Lead (MQL) 

A lead that has shown interest in your business, but you don’t know if they are qualified to buy your services or products yet. However, it must be noted that MQL are those leads who are more likely to become the customer than others. MQLs must be researched or interacted with more to determine whether they can be determined a sales qualified lead and given a call by your sales team.

20. Months to Recover CAC

Also known as the CAC Payback Period — measures the number of months it takes to generate enough revenue to cover the cost of acquiring a customer. In other words, it measures when you break even and a customer starts to generate actual cash for the business. 

21. Pay Per Click (PPC) 

Paid online advertising. It is a marketing model whereby the advertiser pays in proportion to the amount of clicks generated on an online advertisement of their company/software/service. This way of attracting traffic to your site can get pricey and must be done the right way to drive the right kind of traffic to your website.

22. Positioning 

Similar to branding, this term describes how a company positions themselves in their market. Positioning is specifically related to the product (or software) the company aims to sell and the problem it intends to address with its services. On a wider scale it may also include the marketing strategies and customer services offered by the company which help it to stand apart from its competitors. 

23. Return On Marketing Investment (ROMI) 

The revenue generated because of marketing efforts. This is the most important statistic in marketing. 

24. Revenue Churn (MRR churn rate)

 Used to look at the rate at which monthly recurring revenue (MRR) is lost, as a result of lost customers and downgraded subscriptions. To put simply, it implies the loss incurred by the company due to loss of customers and decreased subscriptions.

25. Search Engine Results Pages (SERPs)– 

The SERP is the result a user sees when using a search engine. These web pages are ranked based on their keywords and link profiles or they can be listed at the top of the page if they are paid ads. Companies target to be at the top spots of these SERPs in order to gain larger traffic which helps in inbound lead generation and customer profiling through the means of SEO tools, usage of apt keywirds and paid ads

26. Software as a Service (SaaS) 

A kind of software that is subscription-based and centrally hosted, usually on the internet. The most popular kinds of SaaS software are Hubspot, Salesforce, Zoom and Factors.ai.

27. Style Guide 

A set of design parameters that a web designer uses on every page to make sure your website stays consistent.

28. Submission Rate

 On the website page, the percentage of views that resulted in a form submission is called the submission rate. An extremely useful metric for measuring the effectiveness of a landing page as to whether the website has all the relevant content and features to capture the interest of the visitor. If the submission rate is high it means the content posted by the company and its websites are user friendly and capture the interest of the visitor.Most companies operating in B2B and SAAS domain rely on demos and form submissions in order to take a lead forward, as means of converting a website visitor into a prospective customer.

29. Syndicated Content 

When you publish content to your website and someone else likes it so much that they ask if they can duplicate it on their website. This can help deliver your website content like a blog to a wider audience if done correctly or could hurt the rank of your website and the website with duplicate content. 

30. White paper 

A white paper is a sales or marketing document used to persuade potential customers to learn about a particular product or service to get them to make a purchase. A white paper should be “gated“, or put behind a form on a landing page. It is a type of informative and educational  document highlighting various services offered by the company to its customers.

31. White Hat SEO 

SEO that is ethical and refers to any practice that improves your search rankings on a search engine results page (SERP) while maintaining the integrity of your website and staying within the search engines' terms of service. It’s the opposite of black hat SEO and it aims to work in line with the terms and conditions of major search engines like Google.

II. Content and Lead Generation:

32. Campaign 

A way of organizing marketing efforts. Often b2b marketers will use some combination of marketing tools (webinars, ebooks, white papers, press releases, events, keywords, blogs, keywords, social media messages, and buyer personas) for one unified purpose.

33. Chief Marketing Officer (CMO) 

The head of everything marketing at a company.

34. Backlinks

Links from other sites to a website. Backlinks from authoritative websites can increase the search ranking of a website, while non-authoritative websites can hurt a website’s search ranking. For backlinks to help with SEO, they have to be natural and authoritative. For example a backlink from Forbes to Factors.ai would be authoritative and useful for Factors.ai.

35 Branding

 Branding is an integral part of any kind of marketing. A company can create its brand perception through successful customer interactions, company values, products, culture. Good branding makes a company or organization easy to recognize and helps the company be positively perceived by its audience.

36. Call-To-Action (CTA)

 The first step in turning a website visitor into a lead. A call-to-action is an advertisement for a piece of content; this could be a webinar, an ebook, a white paper, or another high-value piece of content. This piece of content is hidden behind a landing page. When a visitor sees a call-to-action and clicks on it, they are taken to the landing page where they are asked to complete a form to access the desired content. The visitor’s information is then stored on a Marketing Automation platform/ Customer Relationship platform and the visitor becomes a lead. 

37. Content 

Comes in various forms like audio, visual and writing(website text, ebook, blog, whitepaper, press release, social media posts), it could be video, static image, or recorded audio like a podcast. Content is at the center of the marketing process.

38. Content Audit 

Content Audit generally consists of mapping out the stages of the buyer’s journey for a given company, then mapping out the company’s existing content to each stage. It is done to ensure that the company’s content is relevant and relatable to the prospective customers and website visitors so that the visitors find content they are looking for and not get stuck in a whirlpool of random information.

39. Content Curation 

The practice of sharing content that was produced by another company. Content curation usually takes place on social media. Content curation is an excellent way for a brand to develop relationships with thought leaders, and show their own thought leadership by association. In some niches, there is already tons of great content out there. In these cases, content curation is a great way to cut through the noise by allying with industry leaders..

40. Content Marketing 

Using content to market products and services. It is usually considered to be a subset of inbound marketing and often functions by educating the buyer about how to solve their problems. Marketers create content that their target market finds helpful and thus create trust and authority. Content should be created for each stage of the buyer’s journey. Blog content should be geared toward the awareness stage, ebooks toward the consideration stage, and content like case studies, whitepapers, and consultations towards the decision stage. 

41. Content Shock

A term coined in 2014 by Mark Schaefer in a blog post. Mark articulates that the amount of online marketing content is increasing exponentially faster than people’s ability to consume it. The supply is growing way faster than the demand, and thus making successful content marketing more and more expensive.

42. Content is king 

A phrase that has truly earned buzzword status. It’s pretty self-explanatory as it just communicates the power of content marketing. Content is more important for the companies operating in the SAAS and B2B sphere since content is the key driver of their sales and marketing endeavors.  

43. Copy 

It refers to the piece of written work by a copywriter or a content creator, about the product or service used for marketing and advertising purposes.

44. Copywriter 

Someone who writes marketing and advertising content. 

45. Direct Mail 

A way of traditional marketing where marketers send marketing content by postal mail. This used to be common practice, but in the digital age, the practice has become less frequent and is often looked down on by marketers.

46. Ebook

 A content piece that can be used to educate your buyers and thus help them to move along the buyer’s journey. Ebooks fit into the awareness and consideration stage of the buyer’s journey and the attract and convert stage of the inbound methodology. An ebook should essentially be “gated” or put behind a form on a landing page for visitors to fill out and download.

47. Email Marketing 

A facet of content marketing. It can be done using inbound methods or outbound methods. Outbound methods of email marketing are invasive and include buying email lists and spamming random people about your products or offers. Inbound methods of using email marketing focus on connecting with and helping people who have already expressed interest in your company. Email marketing fits into the consideration and decision stage of the buyer’s journey and the close stage of the inbound methodology. 

48. External Links 

While internal links link somewhere else on the same website, external links link to another website. If a website has external links that link to authoritative websites, it will help it rank higher in search engines, while a link to an un-authoritative or spammy website will make it rank lower in search engines.

49. Gated Content 

Content that is higher in value and usually for buyers in the consideration or decision stage of the buyer’s journey. This content is placed behind a “gate” or a form on a landing page. The users must fill out the said form or fulfill certain specific requirements of the gate in order for them to access such gated content.  Lots of different kinds of content can be placed behind a form (ebooks, case studies, consultation, whitepaper, webinars, etc.).

50. Guerrilla Marketing 

A strategy to drive publicity, and brand awareness of a product or service by promoting using unconventional methods designed to evoke surprise, wonder or shock.

51. Historical Optimization 

The practice of optimizing past content (blogs, ebooks and other content) to increase its visibility and, as a result, lead generation.

52. Inbound Links 

When another website links to a page on your website. Websites link to other websites when they feature remarkable content. Inbound links give a website more authority and help to drive more relevant traffic to the website.

53. Inbound Marketing 

A term coined by HubSpot founder Brian Halligan. Inbound marketing aims to create a positive experience for the potential buyer by using techniques like website, social media, email, and blogging to attract customers.

54. Influencer 

An influencer or a thought leader is a person that influences a great number of people in an industry. Examples of marketing thought leaders are Seth Godin, Joe Pulluzi, Guy Kawaski, Brian Halligan, and Dharmesh Shah. Nowadays the term influencer has become more pervasive with the advent of social media. Companies also employ such social media influencers in order to drive their advertising. However, they are not as relevant for B2B players since such social media influencers target end consumers not businesses.

55. Integrated Marketing 

A term used to describe when both inbound and outbound (traditional) techniques are used in marketing efforts. To put simply, when the company employs the usage of cold mailing and follow ups on generated leads to onboard new customers, it is called integrated marketing.

56. Internal Links 

While external links to another website, internal links lead to a place on the same website. Internal links help with navigation, user experience and help Google crawl your pages more quickly.

57. Lead 

A person or entity who has given your company their email address and any other information about themselves and expressed interest in your company. Usually, this happens when a person visits a website and fills out a form to download a piece of gated content.

58. Lead Scoring

The process of assigning a score to each contact in your database based on how likely a contact is to close as a customer. Lead scoring is usually done by marketing automation software and it entails adding or subtracting points on several criteria including a contact’s engagement, their persona, their demographic and more.

59. Lead Generation

The task of turning website visitors into leads. There are seemingly infinite ways to generate leads. Everything including your website, social media pages, and content should be generating leads.

60. Lead Nurturing 

The process of moving your leads further down the funnel until they turn into customers. Measures employed by a company to pursue a lead in order to convince such leads into turning clients of the company. Different companies have different means and measures in their respective funnel to nurture the said lead, some employ direct calling, others employ giving a demo session and many such measures. Email marketing is the most common form of lead nurturing.

61. Omni Channel Marketing 

Omni channel marketing refers to marketing that takes place off multiple channels (also called multi-channel marketing). For example, most companies today must have marketing content for mobile devices, computers, ipads and more. The more seamless the experience is across different devices, the better.

62. Outbound Links 

Links from your website to other websites. This can establish your website's authority. However, this could also result in the loss of leads since the website visitor may not come back to your website. Therefore, this is a gamble since it poses a risk of losing prospective customers to other players. One must employ discretion while employing such outbound links in their blogs and websites.

63. Outbound Marketing 

A term used to describe old school marketing techniques like cold calling, email blasts, or television ads. This term is synonymous with “traditional marketing.” Usually, outbound marketing is less tech-savvy than inbound marketing as it is deeply focused on broadcasting yourself to your target audience.

64. Pipeline Marketing 

A term that Bizible claims to have coined. This term addresses the disconnect between lead generation and acquiring customers. Pipeline marketing focuses its efforts on acquiring customers, not just on generating leads as the majority of the leads do not end up converting. According to Bizible “Pipeline marketing is what you’re doing while content marketing, inbound marketing, lead nurturing, and growth hacking is how you do it.”

65 Request for Proposal (RFP) 

Traditionally it has been used as an opportunity to find a marketing agency or consultant with whom you can build an ongoing, mutually beneficial relationship. Most RFPs sent to marketing agencies are pretty standard, asking for facts, figures, management bios, client lists, recent wins and losses, capabilities, strategic approach and case histories.

66. Search Engine Marketing (SEM)

Internet marketing that promotes websites by increasing their visibility in search engine results pages. This term is often used synonymously with SEO.

67. Social Media Marketing 

The use of social media for marketing purposes. With well over 1 billion people on social networks today, social media provides a huge opportunity for marketers to gain new leads and prospects. Marketers can use social media to share their marketing content, stay informed on industry trends and news, create business connections, engage with their audience, and find new customers. Social media marketing fits into the awareness stage of the buyer’s journey.

68. Shaped Marketer 

A concept used to describe a marketer that has a breadth of knowledge about a lot of subjects, but also has a depth of knowledge in one or two areas. The concept was first introduced to the spotlight in 2010 by Tim Brown.

69. User Experience 

User experience refers to the experience that someone has on a website. The whole purpose of the website is to give the user a positive experience while helping them align their goals with the goals of the company. User experience includes everything about the look and feel of a website including design, navigation, and even content.

III. Strategy and Planning:

70. Account Based Marketing (ABM) 

Account based marketing is a B2B marketing strategy that focuses on specific targeted accounts which the business want to retain or convert into clients. Here, the business takes a holistic approach of marketing, designing strategies and offerings in order to suit the needs of these particular clients.The benefits of such marketing tools are shorter sales cycles, cost benefit and marketing and sales alignment.Do check out our beginner’s guide to account- based marketing (ABM) for a deep dive into this essential marketing concept.

71. Advocate Marketing 

Advocate marketing is a marketing policy whereby the businesses especially B2B businesses use their existing customers to advocate or market their product. Therefore, this requires less resources since your existing customers become mouthpieces of your company's product. Companies use rewarding mechanisms and loyalty programs to reward such existing customers for their advocacy. 

72. Affiliate Marketing 

Performance-based marketing where a business rewards an affiliate for each visitor or customer brought by the affiliate's marketing efforts. Common forms of affiliate marketing include PPC and Organic search.

73. B2B Marketing 

Business-to-business marketing refers to marketing policies adopted by a firm to market its products and services to other businesses and organizations. In layman’s terms, it is where a business markets its products and services to other businesses or organizations as opposed to a consumer(B2C marketing). Companies who serve other businesses as their customers rather than individual consumers are called B2B companies.

74. B2C Marketing 

Business-to-consumer marketing that takes place between a business and a consumer. It is where a business markets its products and services to an  individual consumer. For example marketing strategies employed by FMCG players like ITC to market its shampoos.

75. Black Hat SEO

SEO that is focused on outsmarting the search engines instead of working with them. Black hat SEO makes a website appear more authoritative than it is. It includes but is not limited to link schemes, link farms and keyword stuffing. (see White hat SEO).

76. Deliverables 

A term used in project management to describe a tangible or intangible product that is the result of a project.

77. Demand Generation 

A function of marketing that drives interest in a company and creates a demand in the company and its products or services.

78. Keywords 

The words that potential users type into a search bar to find you online. One part of driving traffic to your website is finding out what your buyer personas type into search engines to solve their problem and then create valuable, relevant content around those keywords. This will ensure you rank higher in search engines for that keyword. Search engine Optimzation (SEO) works primarily around specific keywords in order to rank articles and search engine pages.

79. Keyword Stuffing 

A form of black hat SEO that used to be effective where webmasters would take a keyword they wanted to rank for and put it all over the page. But, today keyword stuffing can hurt your search ranking.

80. Landing Page 

When a person clicks on an advertisement or call-to-action, they are taken to a landing page that features the advertised offer. Landing pages usually feature a form that the viewer fills out to obtain the offer.

81. Gamification 

The use of game-like  techniques like competitions, reward generation and other interactive measures to enhance non-game contexts. It's a technique that employs our natural desire to play games. Examples like loyalty programs, daily quizzes, actual games and rewarding schemes can be termed under the module of gamification.

 82. Growth Hacking 

A phrase coined by Sean Ellis in 2010. He describes it as “a person whose true north is growth. Everything they do is scrutinized by its potential impact on scalable growth”. It’s a trendy term that is used to describe a way of integrating marketing and technological savvy to create unmatched growth.

83. Inbound Methodology 

A hybrid term between the buyer’s journey and the sales funnel. It is the process that inbound marketers use to attract strangers to their business and eventually turn those strangers into happy customers that advocate their business to other strangers.

84. Link Schemes 

A link scheme is an unethical way of making your website look more authoritative than it really is to search engines so that it will rank higher in SERPS(Search engine results page).

85. Link Farms 

A link farm is similar to a link scheme where pages are created with the sole purpose of linking to a target website to try and improve that target website’s search ranking.

86. Long Tail Keywords 

A long tail keyword is a keyword phrase made up of multiple words. They are more specific and hence less competitive, which ends up attracting more of the right kind of traffic to your site. An important point to note with such keywords is you have to be precise and particular in drafting such long tail keywords.

87. Newsjacking 

The practice of putting a spin on a breaking news story to gain media attention, gain leads and create revenue.

88. Organic Search 

A free channel for attracting traffic to your website by optimizing it for search engines and using the correct keywords. Organic search will work seamlessly as long as your website has relevant and authoritative content that uses the right keywords.

89. POV 

Short for “point of view”, a POV is a report that a marketing agency gives to a client to help the client assess different marketing channels. For example, a POV would show whether a company’s target audience spent more time on Pinterest, Twitter or Facebook and therefore which social media platform was a better option.

90. Retargeting 

A form of digital advertising that tracks visitors to a site and then shows them ads for that site on other sites.

91. Search Engine Optimization (SEO) 

Search Engine Optimization is the process of optimizing a website using appropriate keywords in order to rank higher in search requests. The process includes a range of things like creating authoritative content based on the correct keywords for your buyer personas, acquiring inbound links, creating outbound links, gaining social proof, and more.

92. Smart Content 

Website content that changes depending on who is viewing it. Smart content can be set up to show viewers different content based on their location, their device, their lifecycle stage, their buyer persona, or actions they have completed on the website (content they’ve downloaded, or pages they’ve viewed).

93. Social Monitoring 

The act of monitoring specific social users. Social monitoring is especially useful for Twitter. Marketers can create Twitter streams using tools like TweetDeck, or HubSpot’s Social Inbox that only show tweets from specific users or that include a certain word. This can help identify needs or opportunities to share helpful information. Social monitoring is often used synonymously with “social listening.”

94. Synergy 

When multiple marketing channels work together to communicate the same message. Synergy is an integral part of any marketing campaign. Many times the most successful marketing takes place by creatively using different marketing channels in complementary ways.

95. Thank-You Page

When a prospect clicks on a call-to-action and is taken to the landing page and fills out a form to download gated content and thus becomes a lead, they should then be taken to a thank-you page. A thank-you page is a great way to move the viewer farther down the buyer’s journey. The thank-you page thanks the viewer for their interest in the offer and then can show them related offers, or direct them to look at some other aspect of the site. This fits into the decision stage of the buyer’s journey, close and delight stages of the inbound marketing methodology.

96. Value Added Reseller (VAR) 

A company or person that resells a product, usually software and provides certain value over and beyond the particular product or service to be sold. For example providing additional services apart from selling a software in terms of its maintenance, upkeep and installation.

97. Webinar 

A piece of high-value content, a webinar is a great way for a company to educate their buyer personas about a problem and establish themselves as thought leaders. Webinars should be “gated“, or put behind a form on a landing page.

98. Workflow 

A system of nourishing leads down the buyer’s journey through email marketing. They are a series of emails that a marketer can set up in their marketing automation to send out to leads who perform certain actions on a website. The workflow would then send out a series of emails designed to keep the lead interested in the company and prepare them to purchase the company’s product or service.

IV. Sales and Customer Relationships:

99. BANT 

(Budget, Authority, Need, Timeline) An acronym used by sales reps to determine whether a contact has the budget, authority, need, and timeline to purchase their products and services. This calculates and gives a value to the ability of a lead to buy their product and turn into a prospective customer. Different companies employ different measuring and valuing techniques as they deem fit.

100. Blog 

Business blogging is one of many components of inbound marketing. Having a relatable and informative blog on a business’s website can help a business increase traffic, conversions, improve SEO, and do several positive things for a website. Blogs fit into the awareness stage of the buyer’s journey.

101. Buyer Personas 

A semi-fictional representation of your ideal customer based on real data and some select educated speculation about customer demographics, behavior patterns, motivations, and goals. It is a characteristic of the potential buyer sketched by the marketer to design the marketing selling tactics around and about this persona to successfully onboard the client while adjusting to their demands and needs.

102. Channel Partner 

A company or person that partners with a manufacturer or producer to market the manufacturer’s products, services, or technologies. A value-added reseller (VAR) is an example of a channel partner.

103. Cold Calling 

A form of outbound marketing where a person calls random people that may or may not be interested in the hopes to sell them a product or service.

104. Sales Funnel 

A visual representation of the journey that buyers take from strangers to customers of your company that the marketing team uses to categorize contacts. The top of the funnel represents people who are farther away from buying (strangers, visitors, subscribers) and the bottom of the funnel represents people who are closer to buying (SQL‘s, Opportunities, Customers, Evangelists). The company employs various attribution methods to rank such leads.

105. Sales Qualified Lead (SQL)  

A lead that has been determined to have the ability to purchase your company’s products or services. A sales qualified lead is then passed from the marketing team to the sales team to hopefully be closed into a customer. It comes as a next qualifying step after the Marketing Qualified Lead or MQL.

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105 Essential B2B Terms: A Marketer’s Glossary

A comprehensive resource categorizing key B2B marketing terms to enhance industry knowledge and strategy.

1. Measurement & Analytics: Covers A/B Testing, Analytics, API, Big Data, and Bounce Rate for data-driven decisions.
2. Content & Lead Generation: Defines key terms related to content creation, lead attraction, and nurturing.
3. Strategy & Planning: Focuses on essential terms for developing effective marketing strategies.
4. Sales & Customer Relationships: Highlights terminology for sales processes and customer engagement.

This glossary is a must-have for marketers aiming to master B2B concepts and improve campaign effectiveness.

The ideal scenario for every business is to sell to high-intent customers and not waste time on unqualified leads. This is achievable through ABM - Account-Based Marketing.

ABM helps weed out companies that do not fit a business’s ICP (Ideal Customer Profile). Doing so ensures that the efforts of marketing and sales teams align to convert best-fit customers.

In 2022, Foundry conducted an ABM & Intent Benchmarking Study. It revealed that 94% of the 500 B2B technology marketers surveyed rate ABM as extremely important in their overall marketing objectives.

TL;DR

• Account-Based Marketing is a strategy to identify high-intent accounts and target them with personalized campaigns.
• ABM helps find best-fit customers, enabling sales and marketing teams to build and nurture relationships with them throughout the sales cycle.
• Take into account factors such as ACV, TAM, product category (is it a new product or an established one) and organization size of your target accounts (SMB, mid, or enterprise) when deciding if ABM is the right strategy for your business.
• Streamline your ABM efforts, measure and analyze their effect on KPIs, and optimize your strategy based on your results.

What is ABM?

Account Based Marketing (ABM) is a marketing strategy focusing on a specific set of target accounts to build awareness and engagement amongst them and eventually convert them into customers.

Types of ABM

There are broadly 3 ways to execute ABM: One-to-One, One-to-Few, and One-to-Many. For each type, we have listed the top engagement programs & metrics used for tracking

1. One-to-One ABM

In this highly customized approach, the engagement is focused on a small set of accounts (Average: 39, Median: 14)* with the highest revenue potential. Existing customers are mostly targeted here (~80%).

Engagement Programs

• One-on-one Meetings, Workshops, Lunch and Learn Meetings to build relationships
• Highly personalized content via emails, advertisements, and dedicated microsites
• Extensive and consistent research on account for gathering actionable insights

Key ABM Metrics 

• Pipeline
• Revenue
• Number of Target Accounts engaged meaningfully (showed high intent such as demo request).
• Number of Accounts where a specific Persona (say VP, Finance) has been engaged.

2. One-to-Few (or Sales Addressable Market)

In this approach, the engagement is performed in a segmented fashion by grouping accounts with similar characteristics. The average number of accounts in this list is 177, with a median of 50*. Both new and existing accounts are targeted here at an equal share.

Engagement Programs

• One-on-one Meetings, roadshows, and virtual events
• Digital advertising, custom email campaigns, and microsites with segment-specific communication
• Tailored outreach campaigns

Key ABM Metrics

• Pipeline
• Revenue
• Number of Target accounts engaged meaningfully.
• Average Number of Contacts Engaged within a Target Account.
• Number of Accounts where a specific Persona has been engaged.

3. One-to-Many (or Total Addressable Market)

In this approach, the engagement takes place at a larger scale, with hundreds to thousands of accounts having the lowest revenue potential. The focus is greater on new customers (70%) than on existing ones (30%).

Engagement Programs

• Virtual events and roadshows
• Targeted demand-generation campaigns with lower customization levels

Key ABM Metrics

• Pipeline
• Revenue  
• Number of Leads from ICP.
• Number of ICP accounts engaged.
• Number of Touchpoints from ICP Accounts.
• Average Number of contacts engaged within a Target Account.
• Number of Accounts where a specific Persona has been engaged.

Advantages & Benefits of ABM

Advantages

• Focuses on a specific set of target accounts only, making it more quality-focused
• Aligns Marketing and Sales teams efficiently
• Utilized to accelerate pipeline through strategic engagement with accounts.
• Gives a better Customer Experience with the level of personalization throughout the engagement.

Do Consider:

• ABM requires a significant amount of investment and patience before you begin to see results.
• Identifying a contact and relevant stakeholders within a target account is a difficult task, especially when the account size is large.

Benefits of ABM

1. Personalized marketing

Account-based marketing focuses on providing personalized campaigns that directly address the pain points of high-value accounts. This personalization helps empathize with the prospects and show that the business understands their challenges and can provide valid solutions. 

2. Build and nurture relationships

ABM also involves engaging prospects with customized messages at each stage of the sales cycle. By engaging with them at every stage, businesses can build a deep understanding of their needs and challenges and provide more personalized solutions. 

By doing so, businesses can build strong and credible relationships with their prospects.

3. Align marketing and sales team

With ABM, the marketing initiative will be more targeted and purposeful for the sales team to align directly with marketing goals.

By doing so, both teams can keep each other accountable for their specific goals. Additionally, this allows them to identify the purpose-driven activities that address the unique needs of each account.

For example, the marketing team will be responsible for creating and distributing highly customized content that speaks directly to the needs of the target accounts. At the same time, the sales team will be accountable for developing and nurturing relationships with key decision-makers. 

4. Higher ROI

ABM focuses on a set of high-value accounts that meet your ICP criteria rather than focusing on a broader audience. And by targeting these high-value accounts with personalized campaigns, ABM can reduce the overall marketing cost and increase the likelihood of converting these accounts into paying customers.

Therefore, the ROI of ABM campaigns is higher than traditional marketing campaigns that focus on a wider audience.

Is ABM the right marketing strategy for you?

Even though ABM has been trending for some time now and many organizations have seen success using it, you should always take a step back and analyze where your business stands before moving forward. Here’s a small checklist for you:

Annual Contract Value (ACV)

Since ABM involves a significant investment, calculate the ACV for your target accounts and determine the resulting ROI. Then ask yourself, is it worth the effort? 

In case you’re at crossroads and have only 3-4 high-value accounts, you can also follow a mixed approach wherein you adopt ABM for those accounts and other strategies like Demand Gen for others.

Total Addressable Market (TAM)

Your TAM is the revenue opportunity available for your product in the entire market. If you have a small TAM, ABM might be a good fit since you can easily personalize your engagement strategy for the target accounts. 

In case you have a large TAM, consider using ABM. You will need to put in more effort to narrow down target accounts and, thereafter, create personalized engagement strategies.

Established vs. New Product Category

Similarly, if you have a product in a new category for which the initial demand is bound to be low, ABM will be a good strategy for you. 

You can identify the key accounts and engage with them with tailored programs. In case your product belongs to an established category, you can still use ABM to target the top 15-20 accounts generating the most revenue for you.

SMB vs. Mid Market vs. Enterprise

If your target market is SMB, Inbound marketing rather than ABM might be a better fit for you. It is based on the assumption that the ROI from this market for ABM is lower.

If your target market is Mid-Market, ABM can be considered for high-revenue potential accounts while using Inbound as one of the primary channels.

If your target market is an Enterprise, you should definitely adopt a highly tailored ABM plan for each account in the target list. Converted accounts should be given equal focus to improve retention rates and advocacy.

You may experiment with ABM and then scale based on your results. However, the key to ABM is patience. It may take a significant amount of resources, both in terms of time and people, before you actually see the results (depending on your sales cycle). Therefore, it is worth gauging all metrics before beginning with ABM.

Introduction to ABM Platforms

Account Based Marketing (ABM) platforms are tools that help businesses run focused marketing campaigns. They help identify, engage, and convert important accounts through tailored marketing.

ABM technology has grown from simple targeting tools to advanced platforms using artificial intelligence. Since 2004, these platforms have added features like intent data analysis and predictive analytics.

In today's B2B marketing, ABM platforms automate account selection, customize content delivery, and track campaign success. These tools shift the focus from individual leads to high-value accounts. Recent data shows that 96% of marketers have an account-based marketing (ABM) strategy, making these platforms vital for effective marketing.

Understanding ABM Platform Capabilities

Modern ABM platforms have key features that are crucial for effective account-based marketing. These main features include:

Core Features:

• Identifying and targeting accounts
• Managing campaigns across channels
• Personalization tools
• Monitoring intent data
• Tools for analytics and reporting

Integration Capabilities:

• CRM systems (like Salesforce, HubSpot)
• Marketing automation tools
• Analytics platforms
• Content management systems

AI and Machine Learning Components:

• Predictive scoring of accounts
• Automated personalization
• Behavioral analysis
• Processing intent signals
• Algorithms for prioritizing accounts

These features combine to form a complete ABM technology stack that supports advanced marketing strategies

Key Features to Look for in ABM Platforms

When you evaluate ABM platforms in 2025, look for these key features:

Account Identification and Selection

• AI account scoring
• Firmographic and technographic data analysis
• Custom ICP modeling

Cross-Channel Orchestration

• Unified campaign management across channels
• Automated workflow triggers
• Multi-touch attribution tracking

Personalization Capabilities

• Dynamic content customization
• Account-specific messaging
• Real-time personalization

Analytics and Reporting

• Account engagement metrics
• ROI tracking and reporting
• Custom dashboards

Intent Data Integration

• Third-party intent data
• Behavioral tracking
• Predictive analytics

CRM Integration

• Two-way sync with major CRMs
• Automated data enrichment
• Real-time lead routing

These features ensure effective ABM campaign management and clear results.

Implementing an ABM Platform

To implement an ABM platform well, follow a clear plan:

Choosing the Right Platform

• Check if it fits with your current tools
• Look at your team's skills and resources
• Make a list of vendors that meet your needs
• Try out demos and test the platforms

Best Practices for Implementation

• Begin with a small test program
• Set clear goals for success
• Plan the rollout in stages
• Write down the steps and workflows

Common Challenges

• Issues with data quality and consistency
• Problems syncing with CRM systems
• Resistance from users
• Limited technical resources

Training and Adoption

• Create clear training guides.
• Hold regular training sessions.
• Find platform champions within your team.
• Set up ways to get user feedback.
• Track how people use the platform and fix any issues.

Take your time and use enough resources for a smooth implementation. Rushing can lead to poor use and lower returns. 

Measuring Success with ABM Platforms

To measure ABM platform success, focus on these key metrics:

Key Performance Indicators (KPIs)

• Account engagement scores
• Pipeline velocity
• Deal size and win rates
• Marketing-qualified accounts (MQAs)
• Sales acceptance rates

ROI Measurement

• Cost per acquired account
• Customer lifetime value (CLV)
• Campaign ROI by account tier
• Resource use efficiency

Account Engagement Metrics

• Website visit frequency
• Content consumption patterns
• Event participation
• Email response rates
• Social media interactions

Attribution Models

• Multi-touch attribution
• First-touch vs. last-touch
• Account-based attribution
• Cross-channel impact analysis

Track these metrics regularly and adjust strategies based on data. ABM success often takes 6-9 months to show significant results, so maintain consistent measurement and reporting. For more on measuring success, check our Funnel Conversion Optimization page.

Cost Considerations and ROI

Most ABM platforms use these pricing models:

• Annual Subscription: Costs depend on accounts, users, or features.
• Usage-Based: Charges rely on engagement or data use.
• Tiered Pricing: Offers different features at various prices.

Total Cost of Ownership includes:

• Platform subscription fees
• Implementation costs
• Training expenses
• Integration with existing tools
• Ongoing maintenance

ROI Calculation Methods:

• Account engagement rates
• Pipeline speed
• Deal size growth
• Customer lifetime value
• Revenue influenced by marketing

Budget Planning Tips:

• Start with a pilot program
• Consider hidden costs
• Plan for growth
• Set aside funds for training,
• Include integration costs
  
  

Most companies see positive ROI within 6-9 months, with average returns of 25-50% reported by successful programs. 

4 Steps to Streamline Your ABM Efforts

ABM is all about connecting with the right buyer at the right time with the right message. You can increase the efficiency of your ABM efforts by following a few steps. 

1. Gather your data sources for a complete view of account activity from the visitor's very first interaction. It will enable you to make decisions on account-level customizations.
2. Prepare a list of target accounts based on revenue potential and intent data.
3. Develop a concise engagement plan (content, ad communication) for all the accounts/segments. While planning, consider how advanced the account is in the buyer funnel.
4. Measure and analyze the impact of ABM on your KPIs and plan the next steps based on the results.

Account-Based Marketing (ABM): A Strategic Approach

ABM focuses on high-intent accounts, aligning sales and marketing efforts for targeted engagement and higher conversions.

1. Core Strategy: Identifies and prioritizes high-value accounts, delivering personalized campaigns to drive engagement.

2. Ideal Use Cases: Best suited for enterprise sales, expanding within existing accounts, and converting key prospects.

3. Key Requirements: Strong sales-marketing alignment and ABM tools for tracking, organization, and execution.

4. Business Impact: Enhances demand generation, increases brand awareness, and boosts profitability by focusing resources on the most promising opportunities.

Implementing ABM ensures efficient marketing spend, maximized conversions, and sustained revenue growth.

Conclusion

This brings us to the end of this article. It’s quite easy to get lost in the discussion of what ABM is, its various advantages, and its benefits. The key objective of ABM is to show that you empathize with your target audience's pain points and provide a solution that alleviates their pain. 

ABM analytics software such as Factors can help you identify various high-intent accounts visiting your website. It can also track their journey on the website and provide insights into how they engage with the content. Sales teams can use this information to tailor email campaigns, sales calls, and other efforts to target those accounts individually and improve engagement and conversions. 

Engage with high-profile accounts regularly as they progress through the buyer journey. Monitor your metrics and optimize your ABM efforts based on the revenue generated. Continuously engaging and putting effort into building meaningful relationships with your visitors and leads will make your ABM strategy more effective and efficient.

Podcasts are bigger than ever. The number of series worldwide have shot up from an already sizeable 500,000 in 2018 to a whopping 2 million in 2021. Unsurprisingly, podcast consumption has also been rising steadily over the past 15 years. In fact, nearly 60% of all American adults report that they’ve listened to at least one episode this year.

And Videos? They're bigger still. A third of all online sessions are spent consuming videos — everything from sleep talking cats to educational/explainer videos. To sit down and watch every single one published over the past month alone would require approximately 5 million years. And the best part? Nearly all of this is available on the internet for free. As a result, audio/visual content is more accessible, and hence, more popular than ever before.

The opportunistic folk that we are, B2B marketers have taken little time to capitalize on this wave. I can’t remember the last time I scrolled through my Linkedin feed without stumbling across a post for a friend’s friend’s colleague’s boss’s brand new B2B SaaS RevOps podcast. In fact, upwards of 85% of businesses today produce audio/video content as part of their marketing efforts. They are by far the fastest growing marketing channels out there.

And why not? 

Just like any other marketing channel, podcasts and videos can be effective mediums to communicate a specific message to a specific set of people. They are relatively easy to ideate, produce, and distribute. They require little investment from either the supplier or the consumer. And they’re far more palatable than a 20-page white paper. 

Yet, while audio/video content can be valuable assets, marketers face one glaring issue when it comes to identifying and measuring their ROI in terms of conversions — trackability. As is the case with any marketing activity, marketers are keen to understand how their content is performing. However, since anyone can listen to a podcast, or watch a YouTube video anonymously through any device, it becomes nearly impossible to accurately track how your content is contributing to pipeline and revenue. 

How then must a marketer go about gauging their content's performance? 

While there is no perfect solution to this quandary yet, here are a few tips to indirectly optimize your attribution process:

1. Unique URLs

Create a unique URL for every podcast/video you produce. Drive all your marketing efforts (social media posts, emails, etc) towards that URL. And use that URL as a proxy to track detailed information on who’s landing on your page. Once this data is consolidated, it can be stitched onto the remainder of your customer journey (ads, website, CRM, etc) using Factors.AI. Ultimately, this will indirectly provide insights into your content's pipeline contribution.

2. Distinct promo codes

Along similar lines as the previous point, it might be worth employing distinct promo codes for each piece of content you release. The logic behind this is that when a prospect enters a specific code, it provides an immediate signal as to where they’re coming from. This information can then be accounted for in your CRM for further analyses. That being said, a few issues may occur if listeners/viewers refer the promo codes to their networks. As there’s no automated method to verify the same, one may run the risk of corrupting their datasets and insights. 

3. Don’t forget your Guests

Speaking of recording contact data into your CRM, always ensure you do the same with your guests as well. More often than not, guests are invited to marketing podcasts for two of two reasons — one; they’re experienced professionals with vast knowledge on the topic of discussion. And two; they themselves fit the Ideal Client Profile (ICP) that the host company is going after. Inviting a guest onto a podcast is often simply a wind-about route to securing a demo call. With this in mind, it’s important to account for your guests. This way, if they do eventually close a deal with you, the podcast is present as a definite touchpoint. 

4. Just ask!

Audio/Visual content attribution is a real challenge. There are only so many behind-the-scenes steps you can take to optimize for an accurate customer journey. That being said, one sure shot approach to tackling this evasive phenomenon is to simply  ask your customer about their journey to purchase. Maybe a friend told them about it, maybe they read a positive review on ProductHunt, or maybe, just maybe; they loved that one demo video you released last week! Either way, it doesn’t hurt to ask. 
And there we have it!

Though they’re far from perfect, we’ve covered a few simple tricks to track customers who become customers as a result of a degree of influence by your AV content. Listen/View counts and geographical metrics are decent metrics to gauge content performance. But drilling down into who is sliding down the funnel as a result of your content is pivotal. Using unique URLs and Promo codes, and making a habit of accounting for your guests are great ways to grasp a high-level understanding of your content's contribution to revenue and pipeline. And if it comes down to it, just asking your customer about their journey will also be fruitful .

The following post is the second part of our “Attribution is Broken” series.

Here’s a link to the introductory post if you’re interested.

I recently came across an Instagram ad for a shiny new pair of noise-cancelling headphones. Being the mindless sheep I am, I decided that I needed a pair. So after some light research involving a few customer reviews and price comparisons, I went ahead and bought them. From start to finish, the purchase process took me about an hour or so. Admittedly, the headphones set me back a little but who cares? I can always return them if I’m not happy right? This was a short and sweet journey that’s easily digestible by most multi-touch attribution tools. And yet, this journey takes quite the turn when marketers want to reach out to businesses instead. 

B2B purchase decisions are tricky affairs. They involve complex high-value contracts, lengthy sales cycles that stretch over several months, and limited scope for backtracking once confirmed. As a result, all B2B purchases — especially those made in technology — are critical decisions. So, to mitigate the risk of making poor purchases, organisations include multiple stakeholders across multiple departments over multiple levels of seniority in their decision-making process. As an unfortunate consequence, however, this involvement of heterogeneous stakeholders tremendously complicates the account’s journey from awareness to purchase. 

Here’s a simple example of a complex B2B sales cycle:

HubForce, a promising CRM start-up takes out a couple of ads on Linkedin and Facebook.   They also publish content in the form of blogs and host interactive webinars on a regular basis. Additionally, HubForce’s SDR team requests demo meetings from CSOs, Demand Gen VPs, and Project Managers on a daily basis through outbound emails.

Ali, who is project head at Drifter (a leading chatbot service provider), receives one such mail. Ali happens to be in the market for a CRM tool and schedules a demo with HubForce. HubForce’s sales head, Vinay, walks Ali through the several technical features they have to offer. This includes HubForce’s ability to integrate with Drifter’s current tech stack and a cutting-edge AI tool that automates a lot of Ali’s grunt work. Ali is impressed and wants to onboard Hubforce. However, he needs to run the purchase decision by his CEO, Anaiya, before making it official.

Upon hearing Ali’s rave reviews, Anaiya is curious to learn a little more about HubForce.       She reads a couple of their blog posts and digs up a few reviews written by existing customers. Being a fastidious CEO, Anaiya also schedules a follow-up meeting with Vinay. This time around, Vinay demonstrates what HubForce can bring to Drifter’s revenue and sales pipeline. Rather than zone in on technical details, Vinay focuses on HubForce’s big-picture gains instead.  Anaiya likes what she sees but wants to discuss their budget constraints with her finance chief, Albert, before signing on the dotted line.

During their weekly catch-up, Anaiya fills Albert in on the HubForce deal — specifically the pricing details. Albert isn’t thrilled. He’s of the opinion that Drifter would be overpaying for what’s essentially a roided-out excel. Upon hearing this, Anaiya decides to put the deal on hold until next quarter. During this time, Albert is frequently targeted by HubForce ads on Linkedin. He even attends one of Hubforce’s webinars on their cutting-edge, AI-powered CRM technology. Eventually, Albert is convinced of the value that the CRM platform could bring to Drifter.

As the next quarter rolls around, Ali, Anaiya, and Albert discuss the deal one last time. They weigh the pros and cons and arrive at a unanimous decision to purchase a HubForce subscription. Congratulations you guys!

Clearly, the previous purchasing process was far more complex than the case of the headphones. A nuanced web of back and forth interactions had to take place before the deal could be closed. As a marketer looking to replicate this process in a scalable manner, multi-touch attribution is your go-to tool. Attribution modelling empowers marketers to unravel their intricate customer journeys, and understand the performance of nearly every marketing activity. Attribution reveals, to a large extent, what campaigns are working, and what campaigns aren’t. In turn, marketers can make data-driven resource allocations across their marketing activities. All that being said, attribution isn’t without its challenges when it comes to dealing with multiple stakeholders.

Across the length of the previous example, HubForce depended on a variety of content, strategies, and channels to get their deal across the line. They had to sell different aspects of their products to different types of audiences. Project managers may care about practical details like integration, accessibility, and time-saving. CEOs may be interested in high-level gains like ROI, pipeline, and revenue. Finance heads want to know that they’re getting the best possible price. On top of all this, each position is filled by individuals with their own motivations and preferences. The one-on-one demo clearly worked for Ali, but Anaiya chose to perform some background research as well. Albert, on the other hand, was convinced after a couple of targeted ads and a relevant webinar. All these variables contribute to the challenges of B2B attribution:

The B2B Buyer Dichotomy

B2B marketers engage with individual contacts through personalised emails, targeted ads, etc. However, the purchase decision ultimately involves a buying committee. In the example discussed above, there are three stakeholder groups that make up the buying committee- the core buying group (Ali and his project team), the group that focuses on negotiating terms (Albert and his finance team), and finally, the group which exercises the final approval (Anaiya, the CEO).

The core buying group initiates the process by identifying the need for the product, ideates on the potential solutions, and looks for options. The group that negotiates the terms will focus more on protecting the company’s interests. This involves the members from teams like legal and finance. Lastly, the final approval stakeholder group has the final say or authority. The focus of this group is to look at the company’s larger aims and strategy implementations. 

The marketer has to align these diverse internal stakeholders during the sales journey.

Different Strokes for Different Folks

Now that the different internal stakeholders within the buying committee have different core focuses, the marketer needs to adjust their approach to each group depending on what they care about. For instance, in our example, finance cares more about the pricing, while the CEO cares about the revenue and ROI, and finally, the marketing team would care about metrics like conversions, pipeline, etc.

In addition to this, the sales cycle is often complicated and non-linear. Complex B2B purchases such as enterprise software, have a lot more information for the buying committee to consider. This process becomes more drawn out with the complexity of the solution and the presence of alternatives. The multiple stakeholders in an account who have different preferences and objectives, may revisit the various stages of the buying process non-sequentially and sometimes, simultaneously. The stakeholder behavior can also be loopy where they may switch between being interested to not interested to being interested again, as we saw in our example.

Each stakeholder group keeps referring to each other in non-linear learning loops before they come to the final decision of moving forward with the purchase or not.

Invisible Touchpoints

The touchpoints in our sales cycle are of different types. While digital ads, reviews, page views are visible, there may be some that are invisible. Attribution models trying to map stakeholders might be unable to account for these touchpoints. For instance, in our HubForce example,  the finance head, who was not entirely on board with the CRM purchase, attends a webinar which finally leads to the deal being won. Data issues can arise if your CRM and marketing automation data are not flowing properly. In this case, if the impact of the webinar has not been stitched in the sales journey.

Today, most B2B marketers employ a single attribution model across a fixed timeline to derive insights from their campaign data. Sure, this approach is easy, quick, and uncomplicated. But it is also dangerously inaccurate. The issues brought on by the involvement of several stakeholders (Heterogeneous preferences and objectives, long sales cycles, loopy (back and forth) behavior of interest, and a diverse range of touchpoints) render simple attribution modelling ineffective. Instead, marketers should aim to treat each group of users independently and attempt to learn what works best for each one of them. This involves parsing out each type of customer and individually employing the appropriate model. This approach allows you to ask nuanced questions and derive genuinely actionable insights. Of course, this is a far more advanced process than an all-encompassing approach — but it’s infinitely more accurate as well. 

So what’s the solution for implementing incredibly advanced attribution models? 

Well, an incredibly advanced attribution platform of course! 

Learn more about Factors.AI cutting-edge attribution here.

In 1908, Henry Ford introduced the Model-T to the world with a full-page advertisement in Life magazine. The print ad read like an article and was chock-full of technical jargon by design. Back then, a marketer’s function was straightforward — inform all potential customers of the existence and superiority of the product. Who you were marketing to wasn’t half as important as what you were marketing. As long as buyers in the market were aware of the Model-T’s vanadium steel chassis and four-cylinder engine, Ford’s marketing team could sleep well at night knowing they had done their jobs.

Of course, the role of the marketer has evolved *a little* since then. At the time, print ads were one of the few viable communication channels available to marketers. There was also a stubborn focus on the product itself — with little thought given to what worked for each customer. Owing to years of progress in marketing technology and a radical shift towards customer centricity, marketers today have a lot more to think about. Recent digital transformations have empowered marketers with dozens of channels: social media, email, blogs, videos, podcasts, websites, etc.  In turn, they’re able to reach potential customers with content that’s specifically tailored to them. 

On the other side of the equation, digital transformation has also provided customers with far more control. Relevant market information (product details, reviews, alternatives) is instantly accessible to potential buyers. And when your competitors are a single click away from you, there is no room for complacency. As a result, the modern marketer must go above and beyond traditional information distribution. Today, the four staple functions performed by marketers are: 

• Delivering predictable pipeline and revenue 
• Building the company’s brand 
• Developing long-term growth initiatives 
• And empowering the sales team 
  

Still, as marketing has evolved in terms of technology and practice, analysing data and deriving insights have grown increasingly complex as well. While marketers are able to design sophisticated multi-channel campaigns, determining the basic metrics — what’s working, what’s not, which campaigns to invest in, etc. — can become tricky. Here’s an example to illustrate this: 

Gendesk, a help desk software start-up, takes out advertisements on Youtube and Facebook. Deepti, a customer success VP, stumbles upon the YouTube ad while trying to watch a video of a sleep-talking cat. She takes notice of Gendesk and clicks through to their website. Though she likes what she sees, she forgets to sign up for a demo. Later that week, Deepti comes across the Facebook ad while scrolling through her feed. This time, she ensures to schedule a call and finds the product to be a great fit. After discussing with her team, Deepti decides to make the purchase.  

As a marketer, this is great news. But when you’re looking to repeat this process in a scalable manner, a key question to ask yourself is “Which ad do I credit for the purchase decision?” Though there are cases to be made for each ad, the right answer is a subtle combination of both. Identifying this combination of credit, or in other words; determining the values to attribute to the various touch-points along the customer journey is now the holy grail of marketing analytics.     

Enter: Marketing Attribution

The previous example was based on a highly simplified customer journey — one customer and two channels. In reality, marketers target several types of customers and employ several different channels to engage with their audience. What’s more is that the buyer’s journey is almost never a linear path. Deepti may well have stumbled upon the youtube ad, visited Gendesk’s website, interacted with their chatbot, reviewed the pricing page, read a blog about the product, and clicked back to the website before coming across the Facebook ad and making his purchase. Marketing attribution is a tremendously powerful system that determines these various touch-points along the customer journey and attributes a percentage value to each one of them.   

Okay, but why’s marketing attribution so important anyway?  

“The reality is that marketing has become THE most efficient way to accelerate growth in our digital economy. The imperative is to connect the dots, so each marketing expense dollar is aligned and reported against revenue growth.”

- Paul Albright of Captora. 

A well-oiled marketing attribution system can result in efficiency gains of up to 30%. At its core, attribution modeling enables marketers to allocate resources in a strategic manner. Marketers can ensure that they’re actively driving conversions by optimizing their spending based on data-driven metrics. Zendesk’s marketing team, for example, can use a variety of attribution models to derive an understanding of what campaigns are working, and what campaigns aren’t. Accordingly, they can make evidence-based decisions on where to invest and what to alter. Ultimately, this results in a notable rise in ROI, a stronger grasp of SEO/SEM, and an improved alignment between marketing and sales. On average, marketers employ at least 6 communication channels to reach their customers today. As this number continues to rise, attribution will only become increasingly critical to the success of modern marketing initiatives. 

________

All that being said, marketing attribution isn’t without its challenges. In fact, even after the emergence of highly effective multi-touch models, several organizations continue to report attribution manually through spreadsheets. 

There are many considerations that go into choosing the right attribution model which can present several challenges for the marketer:

The Sales Cycle: 

Attribution is a lagging indicator. It takes time and patience to see if models are working. Based on the length of the sales cycle, the effects of a new campaign or changes made into existing ones will reflect much later into the future.

Ease of Set-up and Implementation: 

30% of companies in the UK say that they have chosen their current attribution model based on ease of use. If put in a position to choose between a model that is easy to implement and a complex model that would be tedious for the team to implement, marketing heads would prefer the simpler model. Similarly, technological limitations may also hinder the execution and implementation of attribution models. 

A Culture of Data and Measurement: 

To be able to value the insights provided by attribution models, there needs to be a culture of measurement and accuracy within marketing teams.

Communication of Insights: 

Communicating the insights from the model is significant for communicating cost justification as well as for taking action based on the insights from attribution. To get funds and approvals for software costs, and implementation costs in terms of time, effort, and training, the team needs to be able to communicate the insights well and accurately.

Attribution to Improve, Not Prove: 

Marketers often use attribution to prove that campaigns are working. As mentioned in the earlier section, this is important to be able to justify costs. However, limiting attribution to this purpose can lead to lost insights and higher costs. Attribution, at its core, is directional in nature. Attribution models can be used to see what is working well and also to check what is not working and needs to be abandoned. Marketing and Sales teams are often working on several kinds of campaigns and this is a useful tool to see which campaigns are performing better and can be emulated in future projects.

Volume bias: 

Most often, an organisation’s highest volume campaign can show up as its most successful campaign if marketers do not track other metrics like conversion rate and win rate. To understand, let’s consider the example of an organisation that sells CRM software to businesses. Say in the last six months, they saw a total of 500 downloads, out of which 400 were attributed to Campaign A which was implemented in the form of in-person promotional events like webinars while the remaining 100 were attributed to Campaign B which was implemented in the form of ads on YouTube and Instagram. By themselves, these numbers make it seem like Campaign A was the more successful campaign. But what if we find that the 400 downloads were made by customers from a total of 10,000 attendees in those in-person events while the remaining 100 from the second campaign were made by customers out of a total of 500 users who were presented with the ads. So if we look at the conversion rates for Campaigns A and B, we see that they were 4% and 20% respectively. This comparison could possibly give us the insight that if Campaign B was promoted further, with more funds and effort directed towards it, the organisation might’ve seen more downloads of its software with the it’s higher conversion rate relative to Campaign A.

Absence of predetermined hypotheses: 

To get effective insights from an attribution model, marketers need to be specific about what they’re trying to measure. For example, say the conversion rate for leads from campaign X within the period of the last 30 days since it went live for geographic location Y- can be used to understand if a campaign was successful within the target audience from that location. If marketers do not know what exactly they are looking for, they will end up giving an overall attribution report and miss out on gainful insights.

Invisible touchpoints: 

Several attribution models being used by organisations do not account for certain important touchpoints. Models that do not track the relationship between online activity and offline sales may lead to digital signal bias. For eg. one might have seen the ad for a clothing app on Instagram but they decide to go to the store and purchase the item. Models that do not include sales touches may not include the impact of sales actions. On one hand, it may hamper the accuracy of the outcome metrics and on the other, it may cause disarray with the sales teams instead of aiding collaboration between the two teams.

In order to choose the right attribution model for your team and reap the benefits that attribution brings to modern marketing, marketers need to be wary of these challenges and address them.

In further blog posts, we will be exploring the various challenges of attribution that we have outlined here in greater detail.

I recently came across an article that placed a great deal of emphasis on getting your definitions right. Of course, ‘defining’ things — roles, processes, objectives — holds plenty of value. From providing clarity and purpose to qualifying breakthrough ideas, a good definition can help teams go a long way in reaching their goals. And yet, even the most precise definitions are bound to change. 

With that in mind, this post discusses the elements that define the new and improved Revenue Marketer. In particular, we explore six pillars of Revenue Marketing and highlight the value of data, technology, and organisational alignment in effectively driving revenue growth.

But first, let’s quickly run over the fundamentals of Revenue Marketing.

Like many others, I learned about the term 'Revenue Marketing’ through Dr. Debbie Qaquish. About 10 years ago, during a transition from a long career in sales to a role in marketing, her CEO sat across her desk and posed a single question: “What are you going to do about revenue?” Long story short, this set off the development of a significant approach that transforms marketing teams from flowery cost centers to high-performing revenue machines. This approach, we've come to know as ‘revenue marketing’.

“Revenue marketing is the combined pillars of strategies, processes, people, technologies, content, and results across marketing and sales that drop leads to the top of the funnel, accelerates sales opportunities through the pipeline, and measures marketing based on repeatable, predictable, and scalable contribution to pipeline, revenue, and ROI” 

Phew. 

That was a mouth full. 

Now don’t get me wrong; this continues to remain the foundation upon which Revenue Marketing is built. But back then, the market looked very different from what it is today. We’ve had major changes that mandate an updated definition of revenue marketing. Accordingly, here are three additional challenges that redefine what it means to be a revenue marketer today.

Challenge #1 - Digital transformation

In 2011, the average number of technologies available to the marketing industry was about 150. Today, that same measure stands at an astonishing 7000. It’s becoming increasingly normal for marketing teams to employ upwards of 30, or even 40 different pieces of MarTech products. But digital transformation isn’t just about getting your hands on the hottest new tech toy. Now, Marketers have to choose between all-encompassing platforms like SalesForce and specialised best-in-class solutions for each use-case. The key challenge here is to centralise customer data and orchestrate these platforms to deliver a personalised customer experience. 

Challenge #2 - Customer centricity

It's no secret that as an industry, marketing has been progressing towards customer-centricity. Now more than ever, a firm’s customer experience signals its competitiveness in the market. Again, at the root of this change is digitalisation and technology. Digital customers are in control because your competition is now a single click away from you. Accordingly, identifying and employing the appropriate marketing channels — and distributing relevant content within those channels becomes a key challenge. 

Challenge #3 - Revenue accountability

A 2019 report by Duke University found that 80% of CMOs are under pressure to deliver ROI, revenue, and growth. However, only about a third provide any financial reports as a result of technological inaccessibility and an overall lack of training. Though we have countless programs and platforms to crunch marketing data and derive revenue metrics, they can be a little too inaccessible for marketers without analytical backgrounds to make effective use of. 

And so, we arrive at three challenges — each one based to varying extents in data, technology, and alignment  — that are driving the new definition of revenue marketing.

The new and improved Revenue Marketer 

Teams in leading B2B companies continue to transform themselves from cost centers to predictable and scalable revenue machines. Except now, they have an additional focus on digital transformation, customer-centricity, and revenue accountability. As an outcome, marketing is driving non-linear growth in a world where buyers are averse to direct sales.

Okay - so far, we’ve established our basis for the contemporary definition of revenue marketing. But let’s go even further. Not only is data, technology, and alignment fundamental in defining revenue marketing; it is essential to every capability within every pillar associated with the approach as well.

Strategy

In revenue marketing, strategy involves understanding your team’s readiness for change, aligning your company’s key business initiatives, and most importantly — forming revenue synergy with sales. While a large part of this ‘getting everyone on the same page’ process involves planning, communication, and leadership; technology is playing an increasingly important role as well. Though instinct and qualitative responses can complement strategy, data, metrics, and indicators are crucial ingredients in developing accurate customer profiles and journeys. And as all three merge across sales and marketing, teams require ecosystems that are conducive to a symbiotic, well-aligned workflow. An easily accessible analytics platform (*ahem* Factors.AI) enables sales and marketing folk to speak the same language — revenue.

//Factors.AI is an AI-powered marketing analytics platform that provides critical insights into your marketing activities, decodes customer behaviour, and empowers your marketing team to focus on real strategic decisions. In short - we do all the analytical heavy lifting for you.//

Process

The process pillar isn’t dissimilar to traditional marketing. In general, Process primarily involves campaigns and data. Accordingly, there are two aspects worth highlighting — campaign management and data management.

Campaign management involves executing, tracking, analysing, and measuring digital conversions in terms of business impact. There has been tremendous progress in the MarTech space within each of these functions. Not simply to automate the process, but to derive detailed insights as well. It’s a similar story with data management. Easy access and insight into your marketing data can make all the difference in the world. Implementing this process could be as simple as consolidating all your data under a single roof or automating any recurring analysis.

//Factors.AI enables your marketing team to consolidate and crunch marketing data from across all your sources - Google, Linkedin, Facebook, and more. Our integration process is completely code-free as well. In fact, we could have your marketing team onboarded in a single week.//

People

The people pillar consists of broad capacities involving the management of people in and outside of marketing. Stakeholder alignment, resource planning, and talent acquisition are important, but talent management in particular, is an aspect worth highlighting. A firm can employ all the data and technology in the world, but if the marketing team doesn’t have sound control over these tools, they won't be of much use at all. One solution to avoid this issue is to keep things simple.

//Factors.AI is simple by design. Our platform has been tailored to make the user experience very, very intuitive. In fact, our AI-powered analytics platform does all the work behind the scenes, so detailed insights into your data becomes as straightforward as a google search.//

A training program with a specific focus on revenue marketing tools can also go a long way in improving technical fluency and ensuring your team has a good grasp of revenue-oriented data.

Customer

As a revenue marketer, it is important to understand your customer across their entire life cycle. It’s no longer sufficient for marketers to get a customer through the door and call it a day.  Revenue marketing encourages you to keep tabs on all the touchpoints a customer goes through. Additionally, a revenue marketer aims to optimize their customer data - not only to improve campaign performance but to access valuable business insights as well. A second aspect that’s closely tied to the customer is content management. The batch and blast approach simply doesn’t make the cut anymore. It’s just as important for content to be relevant to the intended audience as it is for that content to travel through the right channels.

//Multi-touch attribution, End-to-end customer insights, and Automated analysis are but a few of the several features Factors.AI has to offer. When coupled with highly customisable campaign analytics - our platform makes for a very simple, very powerful marketing tool.//

Results 

Finally, we arrive at Results. Results to a revenue marketer involves a variety of measures associated with financial outcomes (Shocker!). But it doesn't end there. Along with delivering an impressive ROI, revenue marketers also aim to accurately forecast their revenue. In essence, they construct a marketing machine that drives repeatable, predictable, and scalable revenue. I probably sound like a broken record at this point but analysing data, utilising the right tools, and ensuring organisational alignment are crucial elements at this stage. Needless to say, sufficient training and practice won’t do any harm either.

//Factors.AI’s explain feature differentiates us from the rest of the game. Along with consolidating your data and performing automated analytics, our AI-powered platform provides actionable insights in a matter of minutes.//

Over the course of this post we’ve discussed what it means to be a Revenue Marketer today, we’ve briefly explored the six pillars associated with revenue marketing, and we’ve highlighted the value of utilising data, ensuring alignment, and employing the right tools and technologies. At the end of the day, revenue marketing is a pretty straightforward idea — A well-organised, well-equipped approach that empowers marketing teams to bring in money in a predictable, scalable manner. So as a marketer, the only question left to ask yourself is this:

“What are you going to do about revenue?

Continuing with our series on “Fun with Factors” (please find the first part here), we had another session on “Intuition can only take us so far”, wherein we discussed how non-intuitive concepts such as irrational numbers are very much real. Furthermore, we established the importance of grounding ideas to their bare-bones structure, lest we confuse ourselves and fall into paradoxes.

The Irrational Route

For a number to be rational is to possess the ability of being expressed in the form of a fraction -- or the well-known p-by-q (p/q). Now, just for completeness, recall that ‘p’ and ‘q’ should be integers. And ‘q’ should be non-zero.

That said, is it not easy to see that every number is rational? What’s the big deal? Wait, prepare to be challenged! You need to prove (or disprove) that the square root of 2 (i.e., √2) is a rational number. Oh, I heard you! You say √2 an "imaginary" concept with no practical existence. Smart; you took the challenge to another level! So let’s first see how √2 looks like, and how it’s very real!

Take a square piece of cloth ABCD, each side of which measures 1 m. Now cut it into two pieces along one of its diagonals (say, AC). What you get are two right-angled triangles ABC and A’DC’. Let’s take one of them -- ABC. How much do its sides measure? We know AB = 1 m and BC = 1 m; but AC = ?.

Following Pythagoras’ advice, we could compute AC = √(AB² + BC²) = √(1+1) = √2. Bingo! We have a triangular cloth with one side measuring √2 metres. But you might object! “Why √2? I used a ruler and measured it to be 1.414 m.” Are we in a fix? Not yet. Analytically, we have AC = √2, but on measuring it using a ruler, we get 1.414. One can deduce that the value of √2 is 1.414. That is a smart move because if you could prove that, you would have √2 = 1.414 = 1414/1000, a rational number indeed! Let us see.

So what sorcery is this entity called √2? Simply speaking, it’s the number whose square should be 2. So, we should expect the square of 1.414 to be 2. Alas! It turns out that 1.414² = 1.999396, a little short of 2, isn't it?

Never mind, you procure a better ruler with more precise scale markings and measure the diagonal side of the cloth (AC) to be 1.41421356237 m. But on squaring it, we get 1.41421356237² = 1.9999999999912458800169, again, short of 2.

The fact of the matter is that no matter how precisely you measure the value of √2, it’s inexpressible as a fraction. But how do I convince you of that? You should demand a proof. A proof that √2 is not a rational number.

Let’s see what we could do:

Assume √2 to be a rational number; and let’s give this assumption a name: "The Rational Root Assumption" (TRRA). Now, if TRRA were to be true, we should be able to find two integers p and q such that √2 = p / q. In addition, let us demand p and q to meet a condition: that they have no common factors except 1. Let us call this the “no common factors” condition (NCFC). Now, “√2 = p/q” simply means that p = q√2, or p² = 2q². As soon as you multiply something by 2, the product becomes an even number. So we have 2q² to be an even number, and hence p² is an even number as well. This leads to our first conclusion: that p is an even number (because if it were not, then it would be odd, and if it were odd, then p would be equal to 2k+1 for some integer k, and this would mean (2k+1)² = 4k²+4k+1 = 2(2k²+2k) + 1 would be odd, and so would p² be, which is not possible since we showed p² is even). Let’s call it the “p is an even number” conclusion (PENC). But what does PENC mean? That p could be written as 2m for some suitable integer m. Let’s replace this in the equation p² = 2q². We get (2m)² = 2q², or 4m² = 2q² or q² = 2m². Oh, we have seen this before. This means q² is even, and hence q is even (for reasons made clear above). Let us call this the “q is an even number” conclusion (QENC).

The summary of the foregoing discussion is this: [TRRA and NCFC] implies [PENC and QENC]. In other words, if √2 is a rational number with numerator p and denominator q, and p & q have no common factors, then both p and q are even numbers. Wow, isn't that hard to believe, because how could p and q be even and not have any common factors? If they are even, they would have 2 as a common factor. Now, this is what we call a contradiction! And since the logical flow was flawless, there is only one explanation to the contradiction: the TRRA assumption -- that √2 is rational. Hence, we have proved that √2 is irrational. Period!

Was this discussion easy to follow? Yes.

Was it easy to write? No, because we had used wholesome English words to express the proof.

In fact, proofs are best expressed using shorthand symbols. To illustrate, the following would be a shorter version of the same argument:

To prove √2 ∉ ℚ.

Proof: Assume √2 ∈ ℚ.

⇒ ∃ p, q ∈ ℤ with p⊥q and q ≠ 0 s.t. √2 = p/q.

⇒ p² = 2q² ⇒ p²|2 ⇒ p|2 ------------------> (1)

⇒ m ∈ Z s.t. p = 2m ⇒ (2m)² = 2q² ⇒ q² = 2m² ⇒ q²|2 ⇒ q|2 ------> (2)

Now from (1) and (2) above, we have p|2 and q|2.

⇒ p⊥q is not true. Hence, we have a contradiction.

So, √2 ∉ ℚ. Hence, proved.

So √2, after all, is an irrational number and hence could not be written as a fraction of two integers.

Impossible Probabilities

To find the probability of an event is to measure something. And the prerequisite to make measurement possible is to define what to measure. Imagine what happens if what you want to measure is not well-defined. When asked to compute the conversion ratio of a campaign, your first question is to seek what the definition of a conversion event is. Let us understand the importance of defining concepts explicitly and clearly with the following example from the book on Probability and Statistics by Vijay K. Rohatgi et al, referred to as one of Bertrand’s paradoxes.

Question: A chord is drawn at random in the unit circle. What is the probability that the chord is longer than the side of the equilateral triangle inscribed in the circle? 

To understand the question more clearly, consider the circle as follows.

We have a circle (in red) centered at C with radius r = 1. Inscribe into it an equilateral triangle PQR (blue). If we now randomly draw a chord on this circle (call it chord AB), what is the probability that it is longer than the side (say s = PQ = QR = RS) of the triangle PQR?

Do you see any problem in the question formulation? If no, then you might be surprised to know that there are at least three solutions depending on how one defines the concept “a chord at random”.

Solution 1: Every chord on the circle could be uniquely defined by its end-points. Let us fix one of the end-points -- A -- on the circumference of the circle. This also defines a unique inscribed equilateral triangle APQ. The choice of the other end-point (B) dictates the length of the chord AB.

If B lies on the arc between A and P (Case 1 below), we get a chord shorter than the side of the triangle. Similar is the case when B is chosen on the circumference of the circle between A and Q (Case 2 below). But when we choose B to be somewhere on arc PQ (Case 3), we get a longer chord. 

Hence, we have the favourable points that could act as B (i.e., in a way that AB is longer) to be points on the circumference between points P and Q (Case 3). Now, since points A, P, and Q divide the circumference of the circle into three equal arcs AP, PQ, and AQ. We have length(arc AP) = length(arc PQ) = length(arc AQ) = 2𝜋/3. Hence, we get the desired probability as length(arc PQ) / circumference = (2𝜋/3) / 2𝜋 = 1/3.

Solution 2: Another way in which the length of a random chord is uniquely determined is by the distance of the chord’s midpoint from the circle’s centre. If we fix a radius OC, we would have an equilateral triangle PQR cutting OC at S. Moreover, length(OS) = length(SC) = length(OC) / 2 = 0.5. Our problem could be solved by picking a point X on OC and drawing a perpendicular line AXB as a chord.

Now, where that X is picked decides how long the chord would be. If X is picked on line SC, we have a shorter chord; and the same done on line OS gives a longer one. So our favourable region to pick X is line OS. In other words, the desired probability would be length(OS) / length(OC) = 0.5 / 1 = 1/2.

In conclusion, we have that the same question has two solutions -- 1/3 and 1/2 -- based on our interpretation of the concept of a “random chord”. If you refer to the book, there is another solution that gives a probability of 1/4. This shows how important the exercise of “defining” a concept could be.
At Factors, we support the philosophy of crunching numbers (rather than intuition) to provide intelligent marketing insights, which are only a click away for you to experience: click here to schedule a demo with us. To read more such articles, visit our blog, follow us on LinkedIn, or read more about us.

“Trust your intuition; it never lies.”, a saying most of us have heard and might strongly agree with. But at Factors this week, things were quite different when we had a session on “Intuition can only take us so far”. The idea was to relook at known concepts -- concepts we use more often than not -- and reimagine their implications from different perspectives. This article is an account of the one-hour discussion. We associate the word “factors” with different concepts at different times. Here, we associate it with maths!

Mathematics: Sturdy yet fragile

We started with the following story from “How Mathematicians Think” by Willian Byers:

A mathematician is flying non-stop from Edmonton to Frankfurt with Air Transat. The scheduled flying time is nine hours. Sometime after taking off, the pilot announces that one engine had to be turned off due to mechanical failure: "Don't worry -- we're safe. The only noticeable effect this will have for us is that our total flying time will be ten hours instead of nine." A few hours into the flight, the pilot informs the passengers that another engine had to be turned off due to mechanical failure: "But don't worry -- we're still safe. Only our flying time will go up to twelve hours." Sometime later, a third engine fails and has to be turned off. But the pilot reassures the passengers: "Don't worry -- even with one engine, we're still perfectly safe. It just means that it will take sixteen hours total for this plane to arrive in Frankfurt." The mathematician remarks to his fellow passengers: "If the last engine breaks down, too, then we'll be in the air for twenty-four hours altogether!"

Well, from basic math knowledge, you might find the next number in the sequence 9, 10, 12, 16 to be 24. Here’s how you find it. The first four numbers could be broken down as follows:

9 = 9

10 = 9+2⁰

12 = 9+2⁰+2¹

16 = 9+2⁰+2¹+2²

Pretty clearly, the next number in the sequence has to be 9+2⁰+2¹+2²+2³ = 24.

But does that mean the plane will stay in the air for 24 hours? No. It has only four engines. And if the last one breaks down too, the pilots would either perform an emergency landing or, in the unfortunate case, it would lead to a fatal crash. This shows both the strength and the fragility of maths. While in the first four cases, we could accurately measure how long the journey would take, as soon as the conditions are changed (i.e., gliding into the air instead of being thrusted by engines), the dynamics of motion change too.

Intuition could misdirect

Following is an example the “professor of professors”, Prof. Vittal Rao had given in one of his talks: Imagine you have some identical coins you are supposed to distribute among some identical people. How would you do that? Or more mathematically: In how many different ways P(n) can you distribute n identical coins to any number of identical people? Let us understand the problem by taking cases:

n = 1

• The only way to do that is to give it to a single person:  o.  Hence, P(1) = 1.

n = 2

Distribute 2 coins. Here are two different ways:

• You either give both coins to one person:  oo
• Or you take two people and hand them a coin each:  o|o
  

Hence, P(2) = 2.

n = 3

Distribute 3 coins. What do you think P(3) should be? If P(1) = 1, P(2) = 2, we could expect P(3) to be 3, right? Let’s see.

• ooo
• oo|o
• o|o|o
  

And 3 it is! Hence, P(3) = 3.

n = 4

Now this drives our intuition even further. The sequence we have seen until now has been 1, 2, 3. So it’s natural to assume P(4) to be 4. Let us enumerate all cases again.

• oooo
• ooo|o
• oo|oo
• oo|o|o
• o|o|o|o
  

We have 5 ways to distribute 4 coins -- this beats our intuition. We get P(4) = 5.

n = 5

With new information in hand (i.e., the sequence being 1, 2, 3, 5), we could update our intuition and say this matches the Fibonacci sequence, and expects it to follow 1, 2, 3, 5, 8, 13, ... Let’s see what happens with 5 coins in hand:

• ooooo
• oooo|o
• ooo|oo
• ooo|o|o
• oo|oo|o
• oo|o|o|o
• o|o|o|o|o
  

We get P(5) = 7 (not 8 as we had expected).

n = 6

Now what? We could now turn to a different logic: They are either odd numbers (barring the extra ‘2’) following 1, 2, 3, 5, 7, 9, 11, …,  or prime numbers (barring the extra ‘1’) following 1, 2, 3, 5, 7, 11, 13, ..., giving P(6) to be either 9 or 11 respectively. Taking n = 6, we have:

• oooooo
• ooooo|o
• oooo|oo
• ooo|ooo
• oooo|o|o
• ooo|oo|o
• oo|oo|oo
• ooo|o|o|o
• oo|o|o|oo
• oo|o|o|o|o
• o|o|o|o|o|o
  

That’s 11 ways! The prime-number logic worked.

n = 7

Going by the same logic, we would expect P(7) to be 13 (the next prime number). Now, if you would go on and calculate it, we would have P(7) to be, in fact, equal to 15 (please go ahead and enumerate them).

In fact, it turns out that the sequence P(n) expands as follows: 1, 2, 3, 5, 7, 11, 15, 22, 30, 42, 56, 77, 101, 135, 176, 231, 297, 385, 490, etc. You could take a moment and think about it intuitively, but chances are rare that you would come up with the following formula:

approximating P(n), where we have:

The foregoing formula was derived by the well-renowned mathematician Srinivasa Ramanujan (along with G. H. Hardy). This illustrates the fact that intuition could take us only so close to the solution, and formal maths might have to be invoked in some cases.

At Factors, we support the philosophy of crunching numbers (rather than intuition) to provide intelligent marketing insights, which are only a demo away for you to experience. To read more such articles, visit our blog, follow us on LinkedIn, or read more about us.

Find the next article in this series here.

In the previous blog, we very briefly went over the history of Big Data Technologies. We saw how databases evolved from relational databases to NoSQL databases like Bigtable, Cassandra, DynamoDB etc with the rise of internet along with development of technologies like GFS, MapReduce etc for distributed file storage and computation. These technologies were first developed by companies like Google, Amazon etc and later picked up in a big way by the open source community.

Big Data and Enterprises

Soon enough commercial versions of these open source technologies were being distributed by companies like Cloudera, Hortonworks etc. Traditional enterprises started adopting these technologies for their analytics and reporting needs.

Prior to this enterprises built data warehouses which were actually large relational databases. It involved combining data from multiple databases of ERP, CRM etc and build an unified and relatively denormalized database. Designing the data warehouse was complex and required careful thought. Data was updated periodically. Updation involved a three stage process of extracting data from various sources, combining and transforming these to the denormalized format and loading it into the data warehouse. This came to known as ETL (Extract, Transform and Load).

With adoption of Hadoop, enterprises could now just periodically dump all their data into a cluster of machines and run ad-hoc run map reduces to pull out any report of interest. Visualization tools like Tableau, PowerBI, Qlik etc could connect directly to this ecosystem, making it seamless to plot graphs from a simple interface, but actually done by crunching large volumes of data in the background.

Customer Centric View of Data

Databases are a final system of record and analytics on databases only gives information on the current state of customers and not how they reached here.  With the rise of internet a lot of businesses are now online, or have multiple digital touchpoints with customers. Now it's easier to instrument and collect customer data as a series of actions, be it clickstream or online transactions. This customer centric model of data enables richer analytics and insights. Additionally the data is incremental, and can be made available immediately in reports, instead of being updated only periodically. More enterprises are moving to this model and datastores and technologies that cater specifically to these kind of use cases are actively being developed like TimescaleDB, Druid, Snowplow etc.

So what’s next?

To summarize, the bulk of the big data revolution, that has happened in the last 15 years, is to build systems capable of storing and querying large amounts of data. The queries are raw i.e if X and Y are variables in the data and x1 and y2 are two corresponding values of interest, then the system can return all data points where in the variable X matches x1 and Y matches y2. Or some post processed result on all the matching data points. Along the way, we also have systems that can compute on large amounts of data in a distributed fashion.

So what’s next in analytics from here? Is it building machine learning models? Certainly, the availability of all these data, enables organizations to build predictive models for specific use cases. In fact, the recent surge of interest in machine learning has actually been because of the better results we get by running the old ML algorithms at larger scale in a distributed way. While most ML techniques can be used to build offline models to power predictive features, it is not useful in the context of online or interactive analytics. Most techniques are particularly designed for high dimensional unstructured data like language or images, where the challenge is not only to build models that fit well on seen data points, but also generalizes well to hitherto unseen data points.

Datastores that make sense of data

The next logical step would be datastores and systems that can make sense of data. Making sense of data would mean that instead of blindly pulling out data points such that variable X is x1 and Y to y2, it should also be able to interactively answer different class of queries like

• Give the best value for variable Y,  that maximizes the chance that X is x1.
• Find all the variables or combination of variables, that influence X most when X is x1.
  

Such a system would continuously build a complete statistical or probabilistic model as and when data gets added or updated. Models would be descriptive and queryable. The time taken to infer or answer the different class of queries should also be tractable.  But just like there are a host of databases each tuned differently for

• Data Model
• Scale
• Read and Write Latencies
• Transaction guarantees
• Consistency, etc
  

We could possibly have different systems here tuned for

• Assumptions on Data Model
• Accuracy
• Ability to Generalize
• Scale of the data
• Size of the models
• Time taken to evaluate different types of queries.
  

Autometa - is one such, first of it’s kind, system that we are building at factors.ai. It continuously makes sense of customer data to reduce the work involved in inferring from data. Drop in a mail to hello@factors.ai to know more or to give it a try.

Apache Hadoop, Hive, Map reduce, TensorFlow etc. These and a lot of similar tems come to mind when some one says Big Data and Analytics.  It can mean a lot of things, but in this blog we will restrict it to the context of - analytics done on relatively structured data, collected by enterprises to improve the product or business.

When I started my career as an engineer in Google around a decade back, I was introduced for the first time to MapReduce, Bigtable etc in my first week itself. These were completely unheard of outside and seemed like technologies accessible and useful to only a select few in big companies. Yet, within a few years, there were small shops and training institutes springing up to teach Big Data and Hadoop, even in the most inaccessible lanes of Bangalore.

It’s important to understand how these technologies evolved or rather exploded, before we dwell upon the next logical step.

Dawn of time

Since the dawn of time (or rather the unix timestamp), the world was ruled by Relational Databases. Relational Databases are something that most engineers are familiar with. Data is divided into (or normalized) into logical structures called tables. But these tables are not completely independent and related to each other using foreign keys. Foreign keys are data entries that are common across tables.

Take the example of data from a retail store.  The database could have 3 tables, one for the Products it sells, one for Customers of the store and one for Orders of the products bought in the store. Each entity can have multiple attributes and is stored in different columns of the corresponding table. Each data point is stored as rows in the table. The Orders table contains entries of products bought by different customers and hence related to both Products and Customers table, using the columns product_id and customer_id.

Few implications of this structure are

• Since each data unit is split across tables, most updates would involve updating multiple tables at once. Hence transaction guarantees are important here, wherein you either update all the tables or none at all.
• Data can be fetched almost any way you want. For example, we can fetch all orders bought by a specific customer or all customers who bought a specific product. Additional indices can be defined on columns to speed up retrieval. But since data is split across tables, it sometimes could involve costly joins when matching the related items across tables.
  

SQL (Structured Query Language) became the de facto standard to query these databases and thus SQL databases also became the namesake for relational databases. These served the needs of all enterprises. As the data grew, people moved to bigger and better database servers.

Rise of Internet

Then in the 90’s there was the internet. One of the limitations of the SQL database is that it needs to reside in one machine, to provide the transactional guarantees and to maintain relationships. Companies like Google and Amazon that were operating at internet scale realized that SQL could no longer scale to their needs. Further, the data model did not need to maintain complex relationships.

If you were to store and retrieve the data unit as a whole, rather in parts across tables then each data unit is self contained and independent of other data. The data can now be distributed to different machines, since there are no relationships to maintain across machines.

Google for instance wanted to store and retrieve the information about a webpage only by it’s url and Amazon product information by product_id. Google published a paper on Bigtable in 2006 and Amazon on DynamoDB in 2007, of their inhouse built distributed databases. While DynamoDB stored data as key value pairs, Bigtable stored data by dividing data into row and columns. Lookups can be done by row key in both databases, but in Bigtable only the data in the same column family were co-located and could be accessed together. Given a list of rows and columns of interest, only those machines which held the data were queried and scanned.

Now you no longer needed bigger and better machines to scale. So the mantra changed from bigger and super machines, to cheap or commodity hardware with excellent software. And since hardware was assumed to be unreliable, the same data had to be replicated and served from multiple machines to avoid loss of data.

Open source projects soon followed suit. Based on different tradeoffs of read and write latencies, assumptions in the data model and flexibility when retrieving data we now have plethora of distributed databases to choose from. HBase, MongoDB, Cassandra to name a few. Since these databases were not relational or SQL they came to be known as NoSQL databases.

Related Big Data Technologies

This fundamental change in databases also came with auxiliary changes on how data was stored and used for computation. Most data is stored on files. But now, these files should be accessible from any of the machine. These files could also grow to be very large. And files should not be lost when a machine goes down.

Google solved it by breaking files into chunks of almost equal sizes and distributing and replicating these chunks across machines. Files were accessible within a single namespace. A paper on this distributed file system called GFS was published way back in 2003. Bigtable was infact built on top of GFS.

Distributed databases allowed you to access data only in one way (or a couple of ways) using keys. It was not possible to access data based on the values present inside the data units. In SQL you can create index on any column and access data based on the values in it. Take the example of Google storing web pages, you could access information about a webpage using url cnn.com (row key). Or you could get the links in a given webpage using rowkey (cnn.com) and a column key (links). But how do you get urls of web pages that contain the word say “Captain Marvel”.

So if the data needed to be accessed in a different way, it had to be transformed, such that data units that are related to each other by the values it holds come together. The technology used to do that was Map-Reduce. It had two phases - First it loads the data in chunks into different machines. All the urls of pages that contain the word “Captain Marvel” are sent to other process called Reducer, which collects and outputs all the matched urls. It usually requires pipelines of map reduces for more complex data transformation and joining data across different sources. This MapReduce framework was generic enough to perform various distributed computation tasks and became the de facto standard for distributed computing. The paper on MapReduce was published by Google in 2004.

Yahoo, soon took cue and developed and open sourced these technologies, which we all know as Hadoop, later adopted by Apache.  Now if Map-Reduces can be used to transform data, it could also be used to retrieve data that match a query.  Technologies like Apache Hive, Dremel, BigQuery etc were developed, which allowed user to fire SQL queries on large amounts of structured data, but the results were actually delivered by running Map Reduces in the background. An alternative to loading data into a different machine and then compute on top of it, is to take computation closer to where the data reside. Frameworks like Apache Spark, were developed broadly on this philosophy.

In the next blog, we will see some of the current trends of these technologies and discuss on how we think the these will evolve.

We are excited to announce our integration with Segment, further enabling companies to easily instrument user interactions across platforms and push different types of customer data, from any 3rd party source in realtime to FactorsAI.

FactorsAI provides advanced and intuitive analytics for marketers and product managers, to help drive growth. With FactorsAI you get immediate insights to optimize marketing campaigns, improve conversions and understand user behaviours that drive feature adoption and retention.

A good analytics setup requires detailed tracking of user actions like page views, Signups, AddedToCart with different attributes. The quality of insights on user behaviour shown by FactorsAI is dependent on the level of detail in tracking. With Segment integration this is a one time setup and you could send the same events to other tools for marketing automation, CRM etc.

Further with Segment integration, you can send data from different data sources like email, livechat which will send events like Email Delivered, Email Clicked, Live Chat Started etc. These additional events are useful when analyzing user conversions and by using Segment it can be done without the need to write custom code to hit our API’s.

Segment can perform all data collection tasks for FactorsAI. It can capture all the data that FactorsAI needs and sends it directly to FactorsAI in the right format, all in real-time. So, if you are on segment, you can now start getting insights on how to grow your customer base in no time.

To integrate with Segment, follow the steps here. Happy Analyzing!