Last updated on August 17th, 2017 at 11:08 am
In account-based marketing (ABM), “based” is the word to worry about. It’s English’s offhand way of marking the point from which something will develop or grow. It signals that ABM will require nurturing in multiple areas of expertise, one of which will be your weakest link. Much like in a triathlon – the trifecta of swimming, biking, then running – it’s hard to be good at all three disciplines. But with a balanced base, you can reach the finish line.
My goal is to share some lessons learned in “training” to launch an ABM strategy for R2integrated, the digital agency where I serve as marketing director. ABM challenged our assumptions about how technology, segmentation, and content, the three legs of the ABM triathlon, work together. One of the daunting things about ABM is finding a starting point. I’ll explain why it pays to get your tech stack and accounts right before worrying about the message.
What Goes Wrong?
B2B marketers are familiar with the concept of selling into specific accounts and building relationships that lead to ongoing sales, renewals, and referrals. ABM rests on 80-20 logic: 20 percent of your accounts will produce 80 percent of your revenue. Identifying and choosing that 20 percent is more complicated than anyone expects.
ABM requires coordination between marketing and sales, which, in many companies, spend more time arm wrestling (as we like to call it at R2i) than aligning. There’s no point in marketing to an account if the sales team won’t pursue it. Thus, ABM often dies because marketing and sales can’t agree on the basics.
If sales and marketing do get past that hurdle and target an agreed upon market, the next issue is segmentation. When we decided to use an ABM approach, we circled about 5,000 accounts that matched up with all our target-market criteria. Then we bought a tool – Terminus – and decided to run a singular campaign against all the accounts. We quickly learned several things:
- The architecture of a CRM limits its ability to target accounts. Often, the CRM needs custom fields (e.g. target account, channel target, services target) to produce useful segments in ABM tools
- With good reason, Terminus only allows 2,000 accounts in any given campaign
- Gated, on-demand webinars are not good awareness content (but that’s a topic for another time)
In Terminus, we were forced to split the 5,000 accounts into three segments that received the same webinar ad. Through some reporting acrobatics, we could measure which accounts engaged with the ad most, but we didn’t know why they found the content relevant.
Let’s use an ice cream shop as an analogy. If you only serve chocolate ice cream, how would you know if your clientele find chocolate ‘relevant’ to their taste buds? Chocolates sells, but does it sell better than cookie dough and pistachio? Segmentation allows you to base content on a common denominator like industry. Then you can serve Medical-oriented chocolate, cookie dough, and pistachio to healthcare companies and see which appeals most to whom. And then you can tell sales to pitch Medical cookie dough to a hospital CEO supported by data showing the CEO engaged with that flavor.
In retrospect, we went into ABM neglecting segmentation. Thus, we couldn’t drill down from 5,000 accounts to a few hundred to the couple dozen we’d label best bets. Like the triathlete who runs and swims in training but avoids time in the saddle, we went into the triathlon imbalanced. We were account-based, but based on too many accounts and too few segments.
Tech and Targets First
When you do ABM, you sort of know who you want to sell to. The problem is distinguishing the 20 percent of accounts (best bets) that will produce 80 percent of the results. We found a way to get all 5,000 accounts into Terminus by splitting them into smaller groups, but we needed to create actual segments first.
To solve that problem, introduce segmentation strategy and technology earlier. ABM platforms build upon platforms you use already such as CRM and marketing automation. You feed it email addresses, phone numbers, revenue data, and other data you routinely collect. But, that data alone doesn’t solve your 80-20 dilemma.
One potential solution is an “intent” tool that scores prospects based on their likelihood to buy. It analyzes search keywords, website visits, and other traceable behaviors against custom personas to gauge an account’s interest in your services and products. For example, one service called KickFire will trace the anonymous IP addresses of web visitors to company names, locations, social handles, and other information you’d want before targeting an account.
The second potential solution is a “predictive” tool that uses your CRM data and external sources to predict what known prospects and customers will need, want, and buy next. Infer’s predictive scoring tools are good examples. They’ll pull company data (size, revenue, industry, etc.) and behavioral data (engagement with emails, social posts, ads, etc.) to figure out which accounts resemble your past buyers.
The ideal ABM tech stack will account for your CRM, marketing automation, intent and/or predictive analytics data, programmatic targeting, and content delivery. That stack will help you distill down, reach, and expand into the accounts worth targeting.
The Finish Line
ABM required a different strategy for technology, segmentation, and content compared to when our approach was to put R2i in front of anyone who Googled “digital agency.” As I argued, “based” hinted that account-based marketing would be more complex than expected.
Until your ABM tech stack and account list are sound, the content and its delivery don’t matter. Trust your data services and analytics to modify and segment the final list of accounts. Tools I mentioned like KickFire, Infer, and Terminus have to be looked at as an investment against the lifetime value of accounts rather than a source for individual lead generation. They can give you the data to prove to sales why they should target the accounts in the first place.
When ABM is done right, you’ll triangulate the identities of account decision-makers. Ideally, someone with purchasing power will see your ad while they’re perusing CNN.com on Sunday night. They’ll click the ad, read the linked blog post, and start perusing your website. Your tech stack will alert you to the activity. Then you can give sales the green light to focus on that account. Eventually, your data shows whether account-based marketing influenced new business.
That’s ABM at the finish line. The swim, bike, and run never get easier – you just get stronger and faster each time.
