In this article we’ll cover,
Revenue intelligence (RI) is a popular buzzword in today’s marketing landscape. This enthusiasm may be warranted. RI is revealing itself to be a powerful tool for marketing and sales teams to derive powerful data insights that were hitherto unforeseen. RI uses AI to gather data that would otherwise remain uncaptured.
Let’s start with an example.
GrowNow is a marketing agency for start-ups. They focus on both digital and event services. Their content team has put out several articles on how marketers should approach scaling at various stages of growth.
Akshat is the marketing head of Company X that has a fintech product. They’ve found their product-market fit and now they are looking to scale. He is searching online for ways to scale marketing and branding efforts. He comes across GrowNow’s website and finds the information that he is looking for.
He is not a lead yet but marketing has the information on how he came upon the website and what pages he’s engaged with. He finds his way back to the website a few days later whilst searching for more information on what tech stack his team would need. He downloads a free report on GrowNow’s website on the latest trends in martech.
Finally, after a few weeks, Akshat comes back to GrowNow’s website, this time with a direct search and the intent to check out the services that GrowNow provides. He even fills a form for a preliminary call.
Now that Akshat has been converted, he is pushed to Sales and GrowNow’s CRM has the information that he filled on the form: his name, email address, title and company. They might also have other information like the report downloaded by him. Marketing directs a few more adverts towards Akshat over the next few weeks. Soon sales gets on call with Akshat, they use this information to convert him and they are successful.
Later on, Deepti, the CEO of clothing brand Y which has several pop-up stores finds GrowNow in an article on up-and-coming marketing agencies and clicks on the link which redirects her to their website. She spends some time looking through the website and fills a form. On receiving a call from an SDR, she learns more about their services. Marketing continues to send the same adverts based on Deepti’s website activity. However, after a few calls, they quickly realise that Company Y and GrowNow do not have a good fit. Sales had the same basic information about Deepti as they did with Akshat.
Both Akshat and Deepti’s customer journeys were a little different which sales were unable to access — like the data on their journeys pre-form fills. Similarly, marketing was unable to personalise websites based on Deepti and Akshat’s activities once they went down the funnel to SDRs. This in part, came about due to different locations of this data. Marketing has its data on first touch, web pages visited, time spent on webpages, adverts clicked on Google Analytics or other marketing platform while sales has its data on its CRM like Salesforce. Both departments were unable to access the other’s platform nor did they have an integration in place that allows for seamless flow of this information.
This is where Revenue Intelligence comes in.
In its simplest terms, revenue intelligence refers to the process of leveraging AI to collect, sync and analyse data across sales, marketing and customer success to produce critical insights and generate revenue.
It is a powerful revenue operations tool that helps companies bring synergy between their customer-facing teams (marketing, sales and customer success) and make decisions that are powered by metrics.
More and more companies are increasingly realising the limitations of human intelligence in identifying important data points as well as the limitations on relying only on CRM data for insights on customer journeys.
The solution to this, has been to look at AI to collate and identify data that humans cannot. Furthermore, RI helps teams coordinate and capture data at the right time, before data decay diminishes value -
Data silo is a problem when there is a lack of seamless coordination between teams, especially in terms of data collection and storage. A huge chunk of insights get lost when the data captured by these teams remains limited to their own teams. This is propelled by storing of data on different locations and difficulty in cross-departmental access of this data. All three of these departments are interacting with customers and have intelligence on customer trends and opportunities that get lost with interdepartmental misalignment with data getting siloed.
A revenue intelligence system captures and integrates the data from all these teams in real-time and creates a single, consolidated platform for the entire organisation. This ensures that everyone is on the same page and allows for seamless coordination between teams that helps create a unified strategy.
Sales and customer success teams have to manually enter customer data like contacts, engagements, etc into their CRM. Two problems arise with this:
1. Manually entering data for each and every customer interaction is time consuming.
2. This leads to negligence as many sales and customer success fail to enter all a lot of this data. Around 55% of salespeople admit that they do not enter all lead and customer data.
Resultantly, a lot of available data remains uncaptured and the company relies on this incomplete data for reporting, planning and forecasting.
RI solves for uncaptured data by automatically capturing contacts and engagements data from all customer facing teams, solving for both time and incomplete data, leading to more accurate and reliable sales reporting and forecasting.
Sales and marketing data is susceptible to becoming stale.
Relying on manually entered contact details and the fact that people change jobs and positions and do not update their linkedin profiles leads to databases and CRMs being outdated and filled with errors. Good, high intent leads are very critical for both sales and marketing to reach their conversion goals.
Then there is also the consideration for the hidden cost of redundant data. Bad or outdated data can muddle up research, competitiveness and accuracy of forecasts. Poor data leads to the wastage of sales’s time and IT’s time in syncing systems. It causes frustration when data-backed decisions fail to execute results.
RI solves for this by automatically tracking and updating changes to the leads in the CRM. This ensures more up-to-date and reliable prospect data.
We’ve spoken about the problems of unco-ordination and data silos between sales and marketing. When marketing is unable to access sales data, it prevents potential for improving marking activity and checking for inefficiencies in the existing process. As discussed earlier on the Factors Blog, getting multitudes of leads won't have a positive impact on revenue unless they are good, qualified leads. Infact, it may just lead to a waste of the sales efforts. In such a case, RI helps marketing access sales data that is pertinent for marketing’s processes and planning for more efficient campaigns.
Auto-creating of leads based on sales’ experiences, auto-removal of leads that sales has already dealt with or are low-intent based on previous experiences — both lead to coordination of data as well as a more seamless process of lead identification and capturing of contacts.
Furthermore, automated opportunity association of leads and tracking of interactions (emails, meetings, etc) helps get more insights from available data.
Apart from sending better leads to sales, RI also helps paint a clearer picture of how marketing is helping sales acquire leads that lead to conversions. This helps in both having a better understanding of customer journeys and measuring the impact of marketing in the organisation’s overall functioning.
Revenue intelligence helps with marketing attribution reports that highlight marketings total impact, impact in each channel and the creation of first-touch, last-touch and multi-touch reports. RI also simplifies visualising the opportunity journey with easy spotting of marketing email and campaign touchpoints and deal updates as leads move through the funnel.
Revenue Intelligence helps optimise ABM by improving the data quality of the contacts that are captured for the various accounts. With automation, more contacts can be captured. These contacts are also of better quality due to the improved tracking of customer engagements.
RI also allows you to pursue better personalisation and target marketing efforts based on an account’s firmographic features and funnel position. So teams can get more meaningful insights from CRM and build improved target account audiences.
RI helps sales leaders have a better understanding of the customer journey and gain insights into the prospects that are coming in. Furthermore, having a real-time system of data relating to sales helps with insights into the sales process.
Better prospects, higher intent leads determined based on historical and real-time data improves the quality of leads entering the sales pipeline which in turn leads to higher conversions. Apart from higher output, RI also helps SDRs close deals faster and improve productivity.
Revenue Intelligence helps sales forecasting by solving for outdated and uncaptured data to improve the reliability and accuracy of predictions.
RO&I is a tech category that leverages AI to perform the principal task of revenue operations: integrating sales, marketing and customer success. In other words, RO&I is technology that allows the integration of sales technology, marketing technology and customer success technology to provide an end-to-end solution from customer acquisition to retention and expansion.
Revenue Intelligence tools help teams get the best out of revenue intelligence and empower their Rev Ops efforts with better data and more improved efficiency in mapping customer journeys. Knowing when to reach out to potential customers with the right information at the right time is critical to improving experience and conversions.
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