How Account-Based Advertising Impacts Pipeline 

Getting Real With ABM 

At Demandbase, we strive to not only deliver top notch ABM technology to help B2B marketers achieve more success, but we also aim to find diamonds in the rough to help our community grow from our own learnings.

We know that B2B marketers have a plethora of options to choose from. We also know—or at least say we do—that better engagement increases the chances of a sale. But we wanted to put our money where our mouth is and not simply stand on the pulpit of historical thought leaders. And so, our “Getting Real With ABM” blog series was born.

In it, we’ll dive into how we’re testing our own ABM practice, including the successes and failures we’re seeing along the way. We’ll continue to bring you the key insights as we evolve our ABM practice, so be sure to subscribe to our blog newsletter to keep up to date on the latest in ABM performance. Until then, here’s our first experiment.

How Account-Based Advertising Impacts Pipeline 

For the first installment, we wanted to start with one of the first challenges most B2B marketers experience: creating awareness within high-value accounts and measuring how that engagement impacts sales pipeline down the road.

The Hypothesis:
Accounts who receive ads are more aware of Demandbase and those receiving ads who engage on our website are more likely to turn into pipeline.

We assumed the answer was “Yes—of course they will” but thought we should back that assumption up with some solid data. To do that, we designed the following experiment.

The Experiment
We relied on our own Account Selection technology to identify a set of target accounts and then delivered personalized ads to them with the goal of driving them to engage with our website, regardless of whether they clicked on the ads or not. We planned to have an evaluation period of two quarters so that the test would expand beyond a simple cohort.

Here are a few examples of personalized ads we ran during that time frame:

Next, we chose metrics to measure against our hypothesis. The test performance would ultimately be decided by comparing the pipeline generation rates for two groups:

Group A: Lifted Accounts – accounts who engaged more with our website during the test period than during the baseline period
Group B: Non-Lifted Accounts – accounts who did not engage more with our website during the test period than during the baseline period

The Results
After running the test for a total of 6 months, we categorized the accounts on our target accounts list to either Group A or Group B. Then we compared the pipeline generation rates for those groups to each other during that test time frame.

The results showed that lifted accounts (Group A) turned into sales opportunities at a 60% greater rate!

Now, some may say this is the result of a self-fulfilling prophecy because of course the accounts who are are more engaged on our website are more likely to convert to a sales conversation. And while that’s true, what really matters is being able to identify those accounts and prioritize high conversion campaigns to them because these are the easiest accounts to sell to now.

Stay tuned for our next experiment: How We Cracked the SEM Code.

If you’re interested in learning more about how we approach ABM here at Demandbase, check out our upcoming live demo.