Nailing Down Target Account Selection: How Chorus.ai Informs Their ABM Strategy
If you ask five different people what Account Based Marketing (ABM) means to them, you’ll likely get five different answers. For some, it’s simply an iteration of what they’re already doing in the area of demand generation. For others, it signals a completely new shift in strategy. Or maybe ABM is what they’ve been doing all along. They just haven’t called it that.
As the Director of Marketing at Engagio, I’ve helped hundreds of companies assess how ready they are to do successful ABM—and we all see a lot of advice about that these days. But one of the most overlooked topics is data’s role in the overall strategy, and how it turns an often theoretical exercise into a measurable and justifiable one.
Data is the backbone of contemporary ABM. You can’t segment your accounts without it, can’t prospect without clean contact info, and can’t understand which outreach works without a solid measurement system.
In this post, we’ll learn how a marketing leader at a B2B SaaS company relies on data to do Account Based Marketing right. If you like this post on how Kristen Malkovich of Chorus.ai is doing amazing things with data to make ABM more precise and scalable, check out the Account Based Marketing chapter I write in Clearbit’s Guide to Data Driven Marketing.
Behind the Scenes: How Chorus.ai Selected Their Target Accounts with the Right Data
Chorus.ai creates conversation intelligence software for B2B sales teams. Kristen Malkovich, Director of Marketing, explains that Chorus.ai’s primary audience consists of sales leaders at large, high-growth tech companies. “We have complex, 90- to 120-day sales cycles for the customers we go after, especially compared to our competitors, who go after a broader market,” says Kristen.
To support their upmarket strategy, they decided to build their marketing program with account-based methods from the start. Since Chorus.ai is a 40-person company with a lean team of 4 AE’s at the time of this writing, it’s particularly interesting to examine their account selection process, as it’s prototypical for smaller startups.
Defining Account Selection Criteria
Kristen worked with her sales counterparts to look for sales leaders at SaaS companies. They evaluated potential companies in a third-party database based on parameters like:
- Company size
- Sales team: Do they have a minimum of 8 account executives? Is there a sales enablement function? Have there been any significant changes in the sales org recently?
- Existing tools/technology stack, to infer tech savviness and compatibility with Chorus
- Location (US only)
- In a specific set of sub-industries
Next, Chorus broke those accounts into Tiers 1, 2, and 3, with Tier 1 accounts meeting the most stringent, best-fit requirements.
She extracted the accounts into Salesforce. The next step was to find the key people at those accounts and their contact information.
Setting the Foundation with Fresh Contact Data
Even though it’s called Account Based Marketing, at the end of the day, you’re still marketing to people. Having up-to-date information about who works where and how to contact them makes your sales and marketing teams that much more efficient and effective.
To get great contact data for your target accounts, take an inventory of all the relevant decision makers, influencers, and executive sponsors at these companies. Generally, this requires going to a third-party data provider to quickly pull a list of individuals. You can also use manual research via channels like LinkedIn and even phone verification, but because this is very time consuming, save it for only your top accounts and outsource this when it makes sense.
The second step is to keep that data up to date—an ongoing task. People move into and out of companies all the time, so make sure you keep track of movements such as promotions, key new hires, cross-organization movements, and departures. According to a Biznology survey, changes in people’s titles, contact info, and company names are responsible for a 70% decay rate of B2B records over a 12-month period.
Streamlining the Contact Mapping Process
Back to how Chorus.ai did this. After choosing her target accounts, Kristen used a contact provider to acquire the entire set of relevant sales contacts at companies on her shortlist, including sales leadership, sales enablement, and sales operations.
From there, she imported the list into her Salesforce database as leads. She used Engagio’s lead-to-account matching (L2A) to connect those leads (the individuals) to target accounts (their companies) in Salesforce. She could now look at a target company in Salesforce and get a holistic view of all the relevant individuals to market to; their key contact information included business email, phone lines, and social media handles. Or she could view an individual’s record in Salesforce with data about their company, like size, industry, and technology stack.
Then she linked her third-party data provider to Salesforce so that it could refresh data nightly, keeping Chorus’s marketing database clean automatically. “About 96% of our database is consistently clean, refreshed, and ready,” said Kristen.
Quick aside: She also contends with the quick decay rate of B2B data by using SifData to look for people who’ve recently left a company and send them an automated outreach email to keep them in the Chorus universe. It also alerts their CRM.
The benefits of this exercise were immediately apparent to her entire sales and marketing teams. With L2A enabled in Salesforce, lead routing was streamlined and automatically sent companies to the right sales owner. All required background info was already in the system, so sales development reps spent less time doing manual research on their prospects. This freed them up to do more personalized prospecting.
And it’s a big timesaver for marketing. “Marketing ops teams are constantly troubleshooting with sales about why they were routed a lead,” says Kristen. “The biggest benefit I’ve noticed with our data system in place is that these back-and-forth conversations are gone. Marketing and sales teammates all have an account’s info from the beginning.”
If you want to take a look at the account selection process at another B2B company, where marketing relies on a more structured data model to select accounts for a much larger sales team, check out the Account Based Marketing chapter I write in Clearbit’s Guide to Data Driven Marketing.