The underlying challenges with optimizing programmatic ABM are no different than those faced with traditional advertising approaches.
Think back to the first time you heard about programmatic advertising and account-based marketing (ABM). Whether you heard them from a colleague or read about them online, there’s a point where you said to yourself, “OK, I get it. Now what?”
According to recent B2B programmatic research from Dun & Bradstreet, 65% of B2B marketers are buying advertising programmatically, and 70% are using or plan to use ABM in 2017. Suffice it to say programmatic and ABM are no longer “the next big thing.” Rather, they are beginning to play a big part of B2B marketing mixes and budgets, with the focus shifting to the optimization of these strategies to generate results.
Programmatic ABM is one way B2B marketers are optimizing how they build top-funnel brand awareness by targeting audiences that mirror their “Strategic ABM” list. However, one of the central challenges with Programmatic ABM is balancing scale with precision -- an age-old marketing problem relevant across modern and traditional tactics. In this article, we’ll spotlight 3 key tips to help you reach a broad audience while staying within the universe of your strategic targets, thereby giving your 2017 ABM strategy a fresh perspective.
Tip 1: Use a Persistent Identifier Across Online and Offline Channels
While successful ABM has been widely categorized as the “collaboration between marketing and sales,” we’ve avoided thinking of successful ABM as the connection between online and offline insights – simply because these interactions are so messy to stitch together.
According to Bright Funnel’s 2016 ABM Report, there is a 4:1 ratio of Event touches (both trade shows and field marketing) to digital tactics such as display advertising. If you’re not considering offline interactions, you’re over-valuing online metrics and attributing success incorrectly. Use a persistent identifier tied to online and offline account records to unify account interactions under one umbrella across your DMP, CRM, MAP, and ad agency partners. This will give you a single source of truth to continually inform your Programmatic ABM strategy, and help you focus your messages on the right audiences.
Tip 2: Expand Reach to the Corporate Family Tree
Recently, consumer conglomerate P&G revealed that it was scaling back on hyper-targeting audiences in Facebook, citing diminishing returns as a primary reason for the change. Similarly, avoiding hyper targeting with programmatic ABM can be difficult with so many enticing ways to hone in on “ideal” audiences.
However, achieving scale doesn’t necessarily mean you have to sacrifice precision. Use your current “Strategic ABM” list and include companies that are within their corporate hierarchy – parent companies and branches with decision-making authority. Tapping into the formal and informal communication channels across these related companies will build awareness among decision-making circles and turn influencers into new advocates. Below is a visualization of what a current “Strategic ABM” lens might look like, and how expanding to the full corporate hierarchy for Programmatic ABM can build scale within the universe of your target accounts.
Tip 3: Model Lookalikes Based on Account Behaviors
The attributes used in your model to create lookalikes of your strategic ABM list can make a big difference. Go beyond traditional firmographic attributes like company size and industry to find similar accounts that you can reach. When predictive and behavioral attributes are layered into the model, you’ll have better matches to your list by focusing on audiences that are likely to exhibit similar behaviors to the ones you’re laser-focused on.
Brad White, Director of Statistical Consulting at Dun & Bradstreet, explains how lookalike models are created with this approach for customers: “Our model evaluates 64 different business attributes that describe the Strategic ABM list to identify similar businesses. Those attributes do include revenue and industry. But they also include location and behavioral information like the payment history of strategic accounts. It’s utilizing an advanced machine learning system to identify complex relationships in the data that an ordinary list build could never do.”
The machine learning engine produces model results comparable to full-scale custom models built by modelers manually. The upside is that the lookalike results are delivered in 5-7 days, rather than 6-10 weeks, helping marketers execute in shorter timelines and be more nimble.
Where to Go from Here
Overcoming programmatic ABM challenges starts with using a strong foundation of data that can break silos between the online and offline worlds to ensure you’re measuring and attributing success correctly. Once you’ve set the right foundation, you can build the right audiences that are both related to and look like your strategic ABM targets to achieve scale.
Optimize your ABM strategy with a complimentary Online Audience Reach Report from Dun & Bradstreet that highlights cookie, mobile device ID, Facebook and Twitter reach associated with your target accounts. The report provides a clear picture of your online reach by mapping these digital identifiers across revenue, industry, job function and seniority segments to better inform your next campaign. Click here to see a sample report and request yours today.