Account-Based Marketing (ABM) in simple terms is pursuing a few chosen logos in your customer base and finding ways to make it happen. If you look closely, sales teams have always had an account-based mindset, they chased specific accounts. And the modern-day marketing with the advent of AI has made it completely data-driven.

However, if one doesn’t get data attribution right, then your approach to ABM becomes random despite relying on data. In the context of ABM, data attribution refers to identifying the right set of data that signifies the actions that are making your target accounts move towards you.

Inbound vs. Outbound Attribution

Typically, a marketing team knows what it took to create interest, to move a prospect to conversion, but they hardly have an insight into the revenue generated or the account farming that happens over a time period. Similarly, sales teams know what got the deal going but they do not know the exact contribution from marketing to a particular sale. As a result, there is a definite possibility of double counting the impact, which can make ROI calculations unreliable.

Data attribution helps you clearly see the actual impact created by each activity in the customer lifecycle. As part of my journey at Fiind, I’ve seen within my team as well as with our customers, that attribution directly has an impact on the productivity of the sales and marketing teams. For starters, it helps you ensure that you are contributing to the expected outcome.

Data Attribution Is the Key to ABM Success

Especially for marketers of today, who are continuously moving towards account-based marketing makes data about the targeted organizations extremely important. However, there are two kinds of data attributions here:

1. What are the data that’ll transpire into my approach towards the accounts?
2. What data is considered for attribution?

So, in the case of looking at what data determines the approach to the accounts, there are three broad factors to consider especially as part of an ABM campaign:

• Progression rate: What percentage of target accounts from top of the funnel, moved to mid-funnel? What number of accounts from mid-funnel moved to bottom-funnel?

The data that attributes to these questions are not just about the marketing and sales approach, but about where the given accounts are in the sales cycle. A tool such as Fiind Smart Signals, gives you 360° view of the targeted accounts – including data on their tech stack, whether they exhibit signals of buying interest if your product is a good fit for them, etc. So the primary data to attribute to is whether you have targeted the right accounts and the logic behind the choice of accounts.

• Pipeline velocity: Are you accelerating the progression with sensible and dynamic insights? Did the insights accelerate your sales cycle? Did you close more deals this quarter?

You need to be able to mine your existing accounts for cross-selling and upselling opportunities apart from prospects. So, it’s all about understanding what content accelerates the movement of a prospect/ customer and why.

• Conversions and Revenue: And finally, it is all about closing a sale and all the opportunities to expand the relationship with the account.

Looking at the Right Data Matters the Most

A lot of information is usually in hidden in what is usually referred to as “dark data” or in simple terms unstructured data. For example, there is so much valuable data across sources such as text messages, social media, forums, job sites, email, video and more, in which real insights for customer experiences are hidden.

One of my clients who is in the business of selling CRM software was looking at ramping up his sales productivity. The idea was to improve CX by building relevant conversations. Of course, our sales intelligence solution offers all the necessary intelligence, but the trick was to ensure that we consider the right signals.

For instance, signals such as their target organization hiring a lot of salespeople, whether these prospect companies got funded recently and signals about their tech stack mattered a lot to identify if the customer was in the buying cycle if the CRM was a good fit to their tech environment, etc.

Finally, data attribution isn’t all about crediting the right campaigns, but about optimizing activities to improve productivity, to ensure activities drive the desired outcome and eliminate the activities that don’t add value. It offers a scientific aspect to the art of marketing.