We have a tremendous opportunity to use account data to understand which accounts we should invest our account based marketing efforts.
Every marketing technology vendor is talking about account-based marketing this year. And for good reason. Understanding the effects of account-based marketing is becoming possible with the increasing engagement data we have access to, and the sophisticated predictive models available.
With all the buzz and technology advances around ABM, there’s a need for a framework to help marketers approach reporting. After all, if you can’t connect marketing efforts to revenue, how do you justify investing in it?
In this post, we’ll look at the strategic moves you can make around performance measurement and reporting when doing account-based marketing.
Grade Your Target Accounts
We will be reporting on a variety of account-focused tactics like mailers and paid media at the “grade” level.
Account-based marketing reporting is a lot like farming. A farmer understands that certain plots of land are more valuable than others. Certain soil is more fertile, and located in areas with optimal climate conditions, thus more likely to sustain a healthy crop yield.
In marketing, certain groups of accounts are more likely to close because they are a better fit for your product, or because you can observe that their demographic or firmographic traits match closely with your best customers. In other words, they are more sales ready and are more valuable to you than other accounts.
So what do you do?
You prioritize your account-based marketing efforts to target those prime accounts.
A farmer can see his crop yield and know whether the soil and climate conditions were ideal. He can see the revenue that comes in when he sells his crops. But how does a marketer know whether his A accounts indeed were the ones worth spending more money on to engage with?
The short answer is ROI.
If you have 10 A accounts and 10 D accounts then your A accounts should close faster, require less effort (spending) and generate larger deal sizes. This is holding time and spend constant, meaning ROI should be greater for your A accounts. It’s proof that a one-to-few approach to marketing is worth the investment. Otherwise, why even invest in ABM when you could market to every lead and account with equal effort and equal ROI?
The first step in ABM reporting should be assigning grades to your accounts. This enables you to prioritize your efforts and measure the effectiveness of your efforts to close the most valuable accounts.
Implement Account Engagement Scoring
Engagement is fundamental to ABM. Engagement refers to how accounts respond to your marketing efforts, the recency of those responses or interactions, whether they engage with key content associated with closed-won deals, and the quality and duration of those responses.
When firmographic and geographic information is attached this engagement data, a score is produced using a predictive model.
How is the predictive model created? By passing your past account engagement and sales data through a statistical model we can get an account engagement score that answers the question: How much engagement is required for these accounts to become close-won deals?
It’s a lot like Moneyball, “the book by Michael Lewis, published in 2003, about the Oakland Athletics baseball team and its general manager Billy Beane. Its focus is the team's analytical, evidence-based, sabermetric approach to assembling a competitive baseball team, despite Oakland's disadvantaged revenue situation” (Wikipedia).
The general manager started backwards and asked, how many wins does a baseball team need to make it to the playoffs? That number sits around 95 wins. He then asked how many more runs does a baseball team need to score than their opponent to get 95 wins? That number sits around 135 more runs than they allow. And then asking the on-base percentage and slugging percentage (made of individual player statistics) needed to make to score 135 more runs.
Just like how Moneyball can tell us how many runs or wins we need to make the playoffs, account engagement scores can tell us how much engagement our accounts need to become customers.
Runs and wins are like marketing responses/engagements, and revenue goals are like winning The World Series. Ok, maybe it’s not the same at an emotional level, but on a technical level there are a lot of similarities between baseball statistics and ABM measurement.
Set A Revenue Goal
If there’s a lesson to be learned from the previous section, it’s to set a revenue goal.
Armed with an engagement score, i.e. a predictive model, you now have a clear understanding of what’s required from marketing to hit a revenue goal.
Bizible’s predictive model is based on closed-won deals and revenue, offering marketers everything they need when it comes to account-based marketing and reporting.
Your accounts with an “A” engagement score are sales ready. On the other hand, an engagement score of “D” means it requires your attention and engagement before they are sales ready.
So how do you use this information in a systematic way?
By reporting on how engagement scores change over time, you can understand which ABM efforts are working and which ones aren’t.
Let’s talk about how in the next section.
Using Account Engagement Scoring To Measure ABM Success
If our engagement score increases then our account-based marketing efforts are working.
It means the accounts are responding to key content, many contacts within an account are engaging, and they are engaging multiple times. These are all good signs. And your account engagement score will increase as accounts become more sales ready, or closer to becoming a deal.
There are several performance measures to look at:
Account engagement score increases over time
Account engagement score decrease over time
Account engagement score is stagnate
Account engagement score differences across account grades
Let’s look at these individually.
Choosing a specific time period, perhaps quarterly or monthly, look at your A grade accounts and identify the tactics you used to get your account engagement score from D to A.
These are tactics or content that is working. Below is a visualization of a group of accounts (let’s say your A grade accounts) and their engagement score change over time.
You’ll want to replicate these ads, messaging or outreach strategy.
On the other end of the spectrum are accounts where engagement score decreased over time. This is where responses to your ABM campaign dropped.
Identifying trouble spots in your ABM is essential to creating the winning formula that helps you reach that revenue goal.
Lastly, you’ll want to compare your spend and effort across your account groups, from your grade A accounts to your least prioritized accounts.
What’s the ROI from your grade A accounts? Did higher investments spent on engaging A accounts result in a greater ROI compared to investments in B accounts?
If not, then we need to take a close look at the efficiency of our ABM campaigns.
In baseball a winning formula may never be found, but it’s the ultimate goal. That’s why the story of Moneyball changed the game of baseball. A baseball team took a different approach to the game and despite having a tiny budget, performed way above expectations. Anyone who can make something out of nothing is worth following.
That’s why in account-based marketing it’s so important toconnect engagement data to revenue. We simply can’t hit revenue goals and understand how to make smarter marketing investments without revenue measurement.
To recap the process:
Grade and prioritize your target accounts
Implement account engagement scoring
Set a revenue goal
Reach revenue goal using account engagement score to improve ABM tactics
With the above covered process in mind, marketers will be able to report on ABM efforts in terms of hitting revenue goals.