To quote Forrester’s Laura Ramos, “Unless you have been living under a rock, you can’t have helped but notice the hype around ABM.”
Account-based marketing (ABM) is a hot topic in the business-to-business (B2B) world and, when executed well, it can help you achieve increased deal sizes, shorter sales cycles and increased pipeline.
My take on the hype? ABM is really just good marketing.
Account-based marketing depends on a simple process: B2B sellers concentrate sales and marketing resources on a clearly defined set of targets and execute personalized campaigns designed to resonate with each account. Marketers have been doing this (at least trying to) for nearly half a decade.
Today’s B2B Buyer
Buyers, not sellers, now control the flow of information, pace and preferred channel of communication during the B2B buying process. With a world of information at their fingertips, today’s savvy buyers are often resistant to engage until they’ve completed their own research and product comparison.
According to research by the Harvard Business Review (subscription required), the average number of people involved in the B2B buying process has increased to more than six. Add to that many buyers’ desire to remain anonymous for as long as possible, and revenue teams are floating around in a sea of unknown — something we call the “dark funnel.”
Made up of the research activity and buying signals (think anonymous website visits, competitor research, third-party research and false form fills) that go unseen by sales and marketing, this dark funnel has created a problem for revenue teams. Because buyers are often anonymous, fragmented and resistant, revenue teams’ efforts must be driven by real buyer intent and activity data. So, how do we get there?
Integrating AI Into Your ABM Model
Our solution for our clients at 6sense is to gain insights that improve orchestration by leveraging artificial intelligence (AI) — unlocking the secrets of the dark funnel, prioritizing efforts and engaging with buyers on their terms.
Based on real intent and the activity data buyers are leaving behind — research activity across publications, blogs, forums, etc. — you can use AI to score that activity against your current ideal customer profile, while continually learning what behaviors are leading to new opportunities. Furthermore, you can capture prospect buying signals and deliver insights into the account’s buying stage, who is on the buying team, and what they care about.
Orchestrating these insights ensures the right message is delivered to the right person through the right channel at the right time. And as account status changes, personas engage and opportunities bubble up, sales can be notified and provided details about what the revenue team has collectively done to progress the account in their buying journey.
By integrating AI with your CRM, marketing automation platform and activation tactics, you can ensure a single source of truth across the entire team. This enables tracking and reporting on a common set of metrics in a single platform for team alignment.
Creating The Right Foundation
An AI-powered ABM platform won’t do everything for you, but it will do a lot of the heavy lifting. As a revenue team, it’s up to you to define four key elements: your business objective, budget, collateral and activation channels.
When thinking about your business objective, think in terms of what will be most impactful to grow the business, not a “marketing campaign.” Sample business objectives could be taking market share from a competitor or breaking into a new region.
Prioritizing business objectives in terms of the financial impact makes the other steps easy. You can define budget, collateral and activation channels based on the size and scope of the business objective. If it’s a big competitor with huge market share, you may want to set a bigger budget and leverage more activation channels like display ads, personalized content, webinars, outreach to business development representatives (BDRs) and direct mail. However, if it’s warming up a territory before a new account executive starts, perhaps display and the cadence of outreach to BDRs are more appropriate.
Getting The Most Out Of Your Insights
The biggest factor to consider when integrating AI capabilities into ABM is change management. Are you and your team ready to put insights into action in your revenue function? This may mean not doing things you have always done, like database email blasts. You don’t have to disrupt every function and team, but you do need a plan for how you will start and commitment to the insights-to-action journey.
Here are three practical places to start:
• Field Marketing: While the appetite for executive dinners is always huge, you may not have the budget to run 500 Michelin star dinners. Use AI to heat map accounts, personas and buying stage based on geography so you know exactly where to prioritize.
• Content Development: Rather than trying to ascertain and interpret what your prospects and personas care about, use keyword intent data to really know. This, in addition to a persona map, can help shape much more effective content.
• Account Prioritization: Use AI to determine exactly when accounts are “in-market,” which personas are the most important, and what those accounts and personas care about to set BDRs up for more success.
ABM has been enjoying its time in the spotlight, but the process itself isn’t a cure-all to B2B buying woes. ABM must be backed with the right technology and practices so marketers can get back to doing what they do best: creating compelling content and programs that support prospects in navigating their unique buyer journey. Armed with the ability to collect, connect, and orchestrate data and functionality, ABM at scale is attainable.
