Episode

3

All Things ABM! (With Monish Munshi)

In Episode 3 of The Factors Podcast, we’re joined once again by Monish Munshi — back to discuss all things ABM! We chew over the philosophy, history, and practice of B2B ABM.

January 17, 2022

Q. How would you describe the evolution of ABM to its current prominence?


A. The way I see it, B2B marketing has always been account based. 


If we look at its history, when technology improved, marketing’s ability to generate leads also improved greatly. This created a silo between marketing and sales where the former is working on leads coming down the funnel while the latter is focussed on converting them into opportunities. 


So with better technology, marketing started optimising lead generation from every channel (web, advertising, content syndications, etc). However this volume was too much for sales to handle since there are limited people in the team. This prompted marketing to create segments of these leads which they expected would have a higher engagement rate. Eventually, they started working around a focussed account strategy: the account potential is huge with multiple departments within the organisation which you can proliferate with your product portfolio. This is also where the RAD (retain, acquire, develop) model came into picture. Marketing became very enterprise focussed and they started focussing more on accounts over leads.


Two things started happening here:

1. With ABM, marketing teams started seeing good results. So they started to do a lead to account matching where every lead that comes in is matched to an existing account or a new account is created for that category.

2. More sophisticated algorithms were getting developed which allowed for cheap storage — this led to the advent of CDPs (Customer Data Platforms), which led to the creation of the first layer of the ABM infrastructure. 

CDPs would ingest data from leads, deals, customer engagement and then layer a third party intent layer to come up with the ideal customer profiles. 


Q. In the context of global target lists and the ability to identify these accounts, of the total number of enterprises in the world, how many of them would you say are identifiable through contact databases like Zoominfo and others? Particularly if we also consider SMBs (small and medium businesses)?


A. For targeted account lists, if the enterprises in the list are around 5 to 10 million dollars, then you can easily create the list from a revenue viewpoint. At a regional level, there would be master lists of 500 million companies across the world. 


However, when LinkedIn came in, people did not have to go through these lists, especially if they wanted to identify accounts that would be outside the range of what these lists are able to identify. So it became a preferred source for a lot of people. Meanwhile CDP vendors also started creating aggregate data sources which come in from several different signals, the employee size, revenue and more — based on which you can perform your segmentation of SMBs, mid-market and other organisations. So now it has become easy to customize in a way that regional nuances are present. You can use different platforms out there for different regions and you can create a targeted account list that works for you. 

For SMBs it does become hard because any business can be an SMB. Say, a kirana store that is not registered can be an SMB. However, if we focus on registered SMBs which people can track, there are probably around 130-200 million. But it gets hard to create territories with them and the focus can get dispersed to the point that the targeted list is not targeted anymore. 


Q. When companies are creating their targeted account strategy, how many accounts should they plan for? Should it be more top line driven, where you have your revenue targets and you know how many accounts you want to close to reach those targets. Or how do you suggest companies go about it?

A. Target revenues are important for sure but your starting point should be your average deal size. If you are dealing more at the enterprise level, your average deal size would be in the 500-600k dollars range, if you are dealing more with the mid-market, commercial organisations level, then your average deal size would be in the 50-100k dollars range. This number will help you understand how many accounts you need and in what segment to achieve your target revenue, thereby impacting your list size. 

Another fact that matters is your product portfolio. If you are a single product company, you will have a separate target list as compared to a multi-product company. This is because the ICP will be different for product portfolios that you have. 

These two factors will determine the number of accounts as well as the nature of the sales team that will deal with these accounts. You can either have a product specific sales team or a product agnostic sales team.


After that, you have to build capacity to go through this target list with SDRs and the sales representatives. You have to look at this capacity as a constraint because you cannot employ any number of salespersons to match the list. Say your list has 10k accounts, you cannot employ 1k salespersons to go over the entire list.

Eventually you need to create an account list for your sales representatives. After you have your targeted account list, you create a cohort which the SDRs can work and exhaust its potential before they receive the next cohort. 



Q. Within the three types of ABM: one-to-one, one-to-few and one-to many, what are the key strategies that come in a one-to-many execution plan?

A. One-to-many is actually smaller in size. Globally, I would say there are around 400-500 accounts. I talk mostly about programmatic ABM where everything in marketing (segmentation, campaign planning and execution) is ABM driven. Here your marketing campaigns are based on accounts. Programmatic ABM moves away from lead and MQL metrics. You aggregate everything from impressions, website visits, third party and first party intents on an account level.



Q. For a company to get started on ABM, do they really need the technology to test out ABM and ascertain whether it is the right investment? Are there ways to implement ABM without investing in expensive tools?

A. The best thing to do for such a company is to first get started on the fundamentals. As discussed above, B2B marketing will alway be accounts-focussed. So you can start by adapting your processes on an account level: if you are using lead capture, see to what extent it is on the account level, if you are practicing lead-scoring, aggregate it to the account level, etc. Even conversations by sales representatives should be tracked for how engagement is working on an account level.


Sales representatives usually tend to be the second eyes on the leads which have been generated by marketing. For example, when SDRs spot the same contact in the list for a different product on the portfolio, prospecting stops at contact details. So there needs to be some sales prospecting if you want to move towards ABM.


But in essence if you’re able to do a lead to account match, you can start ABM. Start with the first step where you look at your inbound leads from an accounts perspective. You can start with targeted LinkedIn ads tailored to account types. You can also get in some third party intent data like data from G2 crowd to get third party signals of which accounts are spiking and use that for prospecting. A third step can be programmatic website display which can be executed at an account level. 


However, there is one area where having a funnel that is not going to be part of your targeted account list is important: if you are a new SaaS based organisation which is trying to approach the SMB market. Particularly if you are promoting trials. Here, product usage or trial data becomes the most important thing that you need for qualification, that is, how people are using your product during the trial period. In this case, understanding product usage without focusing on accounts also has to exist at the same time. 


Q. The last thing I wanted to ask you pertains to intent data. How should one go about understanding the accuracy levels of these solutions?


A. First, intent data is perishable data, so you need to act fast on it. Second, if you go really broad, that is, you focus on all the intents and categories that you are involved in, the accuracy reduces. So the best thing to do is to restrict intent criteria. Here, the signals might become lesser but the data you get is more actionable.


In conclusion, to start off with ABM, the marketing team must look at everything from an accounts lens and get relevant information from sales on how different accounts are performing to refine the list that they will eventually use to reach the revenue targets.