Hi, everyone. This is Arun from FunnelEnvy. And today I want to talk about the secret to making your ABM account-based marketing personalization campaign a success.

So what do I mean by ABM personalization? Well it’s website experiences that look something like these: very targeted, personalized experiences that either speak one-to-one to an account or to a group of important accounts. I found this definition online, personalized campaigns that are designed to engage each account based on the marketing message on the specific attributes and needs of that account. So in doing this, you’ve decided that certain accounts are more important and therefore are worth the effort of this level of personalization.

So the typical steps to doing this are, one, identifying who those targeted accounts are. Step two is targeting those accounts in real time with personalized campaigns. And step three, measuring the effects of those campaigns. Now one and two are pretty straightforward, certainly there are potentially pitfalls in those, but what I want to talk about today is the secret is number three, because the truth is that the wrong measurement strategy can doom your ABM, personalization efforts to failure.

So what do I mean by this? Well, a common way to evaluate the effect of an onsite experience is through an A/B test. I’m also calling it the CRO way, conversion rate optimization approach, because that’s what a lot of conversion optimization practitioners do. So in this case, you might run a randomized A/B test, evaluating the effect of personalizing the homepage against the baseline or control and measure an on-site goal, like lead conversions. You can do this in a variety of platforms, measure the effect on your goals, and try to determine the effect that that personalization had.

Of course, this approach makes several assumptions. First off, it requires a large sample size to establish confidence this way or statistical significance. It also assumes that all of these conversions are equivalent. If you’re effectively looking only at the difference between lead conversion for the baseline and lead conversion for the personalized, you’re assuming that they’re equivalent. So really what this means that this approach measures the impact based on the quantity of those conversions, not necessarily the quality. So we should ask ourselves, are these assumptions consistent and compatible with our ABM strategy?

Well, when we’re thinking about the ABM approach, the whole point is to capture more revenue from a smaller number of accounts. That’s how you can justify the investment in doing things like targeted ads, website personalization, or direct mail. Another thing to keep in mind is that the further up you go up the ABM pyramid, the number of accounts decreases while the value or expected revenue per account increases. In many cases, the white glove accounts could be worth a hundred times more what a volume SMB account is. And because those accounts are likely large enterprises, they’re going to take a longer time to buy.

So what all of this means is that your ABM personalization strategy should probably include a quality metric, and the best quality metric is pipeline and revenue over a longer period of time. Now this can conflict with the CRO approach that we showed in the previous slide, which is very transactional, top of the funnel, and assumes that every conversion is equivalent.

So a simple solution, many of you might be already doing this is to pass the variation information back from your optimization platform into your CRM, for analysis against pipeline and revenue. Often, this means embedding the variations that a user saw in a hidden field on a lead capture form, and then building some custom reporting based on your CRM data on the backend. So what this does get you is better insight into the down funnel impact of your experiences based on pipeline and revenue, but you can also have, and this can also result in a one-off solution for the website experience that doesn’t really align with the way the rest of the demand gen team measures and attributes revenue.

Now, many of you are probably running multi-touch attribution models, either with off the shelf tools like Visible, or with a custom solution. These work for longer journeys by allocating revenue back to customer journey touchpoints, like the first touch, lead creation, or the opportunity creation and giving credit to the things that influenced it. B2B attribution solutions are inherently account-based and they’re typically used for channel and campaign analysis, but they can also be used to measure the effect of on-site activities like ABM personalization campaigns. Now, the real advantage here is by integrating your website experiences with your multi-touch attribution model. You’re aligning your website activities to the measurement strategy used by the broader demand generation team.

So how does this work? Well, let’s say you have touchpoints established and you’re allocating revenue in some proportion across them. Here, the actual percentages don’t matter. The point is that you are allocating revenue back to new customer touchpoints. So once you know the revenue at a certain touch point over a period of time, with attribution, you’ll be able to assign credit back to the activities that influenced that touchpoint conversion. As I mentioned, it’s typically done at a channel and ad campaign level, but there’s no reason that an onsite experience can’t be an influence over a touchpoint as well. Campaigns and variations are certainly one example of those, but you could also consider things like chatbots, content, anything that’s influenced that touchpoint. What you’ll get out of this is pipeline and revenue credit associated with the things that influenced those touch points, and in this case, on-site experiences.

So what you get out of doing that is a much better understanding of the impact that your on-site campaigns can have on your business. So rather than talking about some percentage of conversion lift on a superficial vanity metric, you can do things like report on the campaigns over time with respect to their sourced pipeline. You can look at the impact that your campaigns have had, based not only on onsite metrics, but also based on sourced, influenced pipeline and revenue, as well as closed one deals. You can also look at the variations within your experiments and report on the uplift based on pipeline and revenue correlated directly with their attribution model.

So with that, I want to leave you with some other things that you want to think about to make your ABM personalization efforts a success. Definitely recommend starting your revenue insights journey by being able to measure the revenue contribution of your existing offers. By aligning with your attribution strategy, you can actually look at the on-site offers that you have, and assess each in terms of the revenue contribution.

Segmentation is a big part of account-based personalization. The audiences that you create should have differentiated intent. You don’t want to spend a bunch of time creating audiences that are effectively the same and would want to see the same experience. You want to think about how your account clusters and account groups are differentiated, and therefore what offers they’re going to want to see that are specific to that group of accounts.

Definitely recommend avoiding what we call vanity personalization, where you maybe slap in the name of the customer or the name of the account coming to the site, and really focus on the offers that you’re putting in front of the visitor. I’ve mentioned this in previous videos and blog posts, but really the most important thing and the highest leverage thing you can do is present a more relevant offer throughout the demand gen funnel to that visitor. So think about when you’re segmenting and thinking about the offers to these target accounts, which offers are going to be more relevant to that group of accounts we’re personalizing for.

And finally, don’t just think of this as a top of funnel activity. Obviously we’re talking about demand gen marketing, your full customer journey, and a long revenue funnel. So once you have the ability, just think about how you can align offers and optimize, not only for top of the funnel, but for every buyer stage all the way to revenue. Thank you for listening today.