Data which got us to embrace Account Based Marketing

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There is a constant ongoing management debate around starting deal sizes in enterprise deals. And something we definitely faced during the early days of Belong. 

On one side of the debate are opinions which state that initial deal values don’t matter much, it's more important to secure a logo, this is commonly referred to as “land and expand”. On the other hand, there’s a belief that if you already have all the stakeholders mapped out, and there’s a clear immediate need, why not strike when the iron is hot and capture as much of the budget and try to get a starting price which is meaningful and then expand from there. 

This is especially pertinent for: 

• Traditional enterprise companies that have enterprise only products (unlike say Slack).
• Companies moving upmarket from ACV $5-10K to bigger numbers (upwards of $25K), without the comfort of a strong brand and relying on outbound sales. 

From a salesperson’s perspective, this becomes a bit of a peek-a-boo exercise, where a sales guy ideally would like to have some sort of a heuristic to get a sense of the initial deal value vs effort required. 

And once there’s a few data points, it's always good to look back and see what works or not (eventually building a case for having a sales operation function).

When I triangulate some of the patterns that we thought worked in our case by looking at a cohort of deals over a period interesting patterns emerge.

Multi-threading vs Entry Deal Sizes

As we distilled the data, it was clear that ours was a consensus driven sale, which required buy-ins and engagement with multiple personas in an account. We used to call this process as multi-threading.

There was a weak correlation between (R^2 = 0.38) multi-threading vs the entry deal sizes. I was curious about the anomaly case at the far right (highlighted in red), which didn’t seem to agree with the hypothesis. Maybe it was just a one off case, since these were early days of our enterprise sales process. 

But if we ignored that one case, the correlation became much stronger (R^2 = 0.74). So clearly we needed to continue to double down on multi-threading.  

However, that one case did bother us. We went deeper into the raw data and noticed something interesting.

Effect of meeting CEO/Site Lead/CHROs on Entry Deal Sizes

While the previous graph helped us come up with some sort of a target metric around how much multi-threading was required for each type account (we had bucketed accounts basis size, industry, revenue per employee), we needed to know if the juice was worth the squeeze.  

Hence we tried coming up with a potential account value for every account. Our model eventually took into account multiple factors, however, in general it was correlated to the amount of mid-senior level hiring an account was doing in their technology organisation (incl. Product / design). 

Looking at our entry deal sizes, and running some pivot tables, we got a sense of how much money we were leaving on the table. And so, say we entered an account with an ACV of $50,000 (amazing! Since we started with $6000), we should be cognizant of the account potential. If the account potential was $3M, then we knew that there was room for improvement. 

We charted the graph that’s seen above. Clearly the deals where we met with the CEO / CHRO had higher deal sizes compared to the overall budget. 

This was especially true for mid sized firms (i.e having < 2500 people in India). Regardless of the multi-threading aspect, the deal size would be capped unless we involved the CEO/Founder or Site Leader (in case of an offshore engineering centre). If you think about it, intuitively it makes sense. At this stage the MD/CEO still has considerable control over the organization. 

This led to a bunch of initiatives: 

1. Sales Process: We updated our sales checklist and target input metrics for our sales team. The idea was to find ways to navigate the account, incase we got stuck at one of the stages. (say we engaged 9 people viz 45% of recruiters & business leadership, but not HR leadership? Let’s try tactics A/B/C to meet the HR leadership). We also created an internal tool to help keep tracking of data to help compute lead scores and help make the sales team’s life easier (topic for another post).

We wanted a sales funnel which ran through the entire company (from MQA qualification to post sales churn leading indicators) and created the process below. If you look at it below, you can see that the stages in the funnel are from the customers perspective and not from a salesperson or customer success person’s perspective. Creating stages like these helps putting funnel stages in perspective for the entire company and also helped us come up with better probabilities for sales conversion instead of just writing something like “Lead to Opp” conversion metrics, which doesn’t tell a salesperson, why the number is what it is. Or how to push things further down the funnel. Each of these stages corresponded to directions for salespersons to act on incase they got stuck, and over a period of time, we got a sense of how long should each opportunity be in each stage (something Aaron Ross / Jason Lemkin call age-ing).  

1. Push towards ABM: We started creating deeper account specific strategies for some of our larger prospect accounts with engagement strategies for each of the personas and these were closely tied to their budget cycles. 
2. Investing in CXO relationships: In addition to helping our relatively young sales team (who were all in their mid 20s, and one 30+ guy) expand their network, we set up a team in the CEOs office dedicated to investing in our CXO advisory network. This advisory network warrants a separate post, which hopefully I will get to write in the days to come. 

While I am sharing this story, all of this was a team effort of a stellar team including Shuchi (who was our Chief of Staff), Kaushik (leading marketing), Sravan (leading mar-tech), Antoine (salesops), innumerable conversations with our sales team (Ravi, Vivek, Abhinay) and ofcourse Vijay.