Turning from static account lists and combining intent sources for fuller coverage
Account-based marketing (ABM) strategies can bring businesses closer to their best opportunities, at the right time, delivering real value to the business. Until recently, ABM was mostly practiced on a 1:1 scale by large enterprise companies – those that were afforded the time and resources for highly-targeted efforts. But thanks to increased access to data and data-driven MarTech, marketers from SMBs and enterprises alike are running with ABM strategies from 1:1, to 1:few, to 1:many. ABM can be achieved now on a 1:1 basis through a 1:many, thanks to sophisticated data analysis, and account-based marketers need to understand how to add to their toolboxes and take advantage of the value here. The payoff is real – businesses whose teams are aligned in ABM campaigns can see a 208% increase in marketing-derived revenue.
An ABM strategy can take an account that appears to be an ideal fit based on profile, and let the marketer guide them smoothly to the point of making a deal. The problem is that determining the right time to reach out to accounts is an inefficient process, often involving a great deal of manual effort. Even with a list of high-fit accounts, chances are many of those accounts won’t be in-market for your product at the moment of contact. Account-based marketers need more efficient methods – something that provides deeper and more actionable insights than an account list in itself. This is why account-based marketers are increasingly shying away from static account lists, and instead prioritizing accounts with predictive intent.
Make the most of intent sources
The modern B2B buyer journey is complex, and involves various channels including the company’s owned and operated sites and apps, product review sites, social platforms, content marketing initiatives like webinars and downloads, messaging platforms, and industry events. Because a dynamic and successful ABM model today requires analyzing signals from all these sources and more, an account-based marketer needs to go well beyond their own CRM to collect data if they hope to locate the right in-market accounts without guesswork.
First-party intent data reveals topic interest and price point signals from activity on your own properties. The further down the account drives into your digital properties, the clearer the insights and signals become to inform customization in content and offers. Second-party intent data will often come from sources like business partners, product review sites and customer surveys to provide, among other benefits, valuable background on how audiences are researching your competitors. There are great insights in this data – but they’re focused primarily on the middle and lower funnel. Third-party intent data delivers volume, comes from varied sources, and can fill in blind spots about upper-funnel interest. While combined, this multi-source intent creates a clearer picture of propensity within the ABM list, but it can be difficult to align the signals in these various sets for actionability. An AI-powered intent tool relieves a great deal of pain here – providing a steady stream of multi-source, real-time intent and analysis that can trigger marketing automation, without piling on work hours and additional headcount.
With robust intent data, account-based marketers can optimize their strategy by layering intent on top of the account list to understand which accounts are currently in-market further down the funnel. Intent data can also be used to expand your ABM list, revealing who’s researching your competitors and which additional lookalike accounts are also in-market. AI plays important roles in ABM orchestration, integrating this intent data from in-funnel accounts into the business’s ad and CRM platforms. This can efficiently align in-market businesses with ICP (ideal customer profile) accounts, and reveal where those two groups overlap. These strategies combine the firmographic “right fit” element with the critical “right time” element that allows account-based marketers to identify hot accounts and leads earlier, and close before their competitors.
Make sure martech and intent solutions play well together
With ABM, marketing and sales teams facilitate everything from audience building, to content delivery, to setting automated triggers to fire off specific tasks. But it requires a data and technological lift to be efficient in these efforts and deliver a payoff that’s worth the effort and investment time and again. Data needs to be pulled and processed continually and then applied to the ABM list for dynamism. The right intent solution must integrate with ABM tools and efforts in real-time.
Locating and implementing the right MarTech tools is a critical step to getting the most value from an intent-driven ABM strategy. Effective, value-driving solutions will be able to activate data as signals occur and align to stages of the buyer journey. When account marketers are empowered with an intent data solution paired with an ABM platform that speaks to each other easily, account-based marketers can spend less time analyzing and organizing data manually, and more time activating the right data at the right time in ways that produce real results.
Go beyond the account list, and toward more marketing-derived revenue
For marketing to truly make an impact in a complex buyer landscape, ABM efforts and the account list need to reflect real-time intent, so that intent can effectively guide the ongoing development and engagement of the ABM list. Static lists are static because they’re based on historical wins – they share similar, unchanging firmographics with existing customers. By contrast, a dynamic ABM list takes intent into consideration, to drive dynamic orchestration. A dynamic list layers in data from various sources, prioritizes accounts for outreach based on data signals, and automates next best steps – or even helps the marketer create an altogether better ABM list. This makes marketers’ ABM efforts more productive, by focusing on both right-fit and in-market accounts.
By focusing on intent, account-based marketers can finally move toward a more integrated model that makes use of automation and actually reflects the holistic buyer journey. Automated ABM efforts that use intent signals, starting at the account list-building stage and progressing through 1:many, 1:few, and 1:1 efforts, will drive a lift in the business’s revenue from marketing. Businesses need to look to the technology that can support a dynamic, intent-driven approach – giving them the advantage in a competitive marketplace, and keeping their marketing and sales teams focused on strategic work across the whole funnel.
