Focusing on an account-based strategy, marketing and sales operation pros need to build a credible account scoring model that relies on solid data and prioritizes the right accounts. Relying on clean data is key to crafting a reliable account score and determining company fit.
During the Account Scoring Webinar, panelists Jim McDonough, Colin Cheng, and Palen Schwab echoed these sentiments and discussed how account scoring materialized at Threat Stack.
Eric Martin of DataFox moderated the presentation and saw the conversation center around two major themes: the need for high-quality data and automation.
Leveraging Big Data
The foundation of any quality account scoring model relies on clean data. Enriching account data is an ongoing process and critical for evaluating company fit. In driving an accurate account score, data quality is crucial for indicating an account's propensity to buy.
At Threat Stack, account-based selling had already been adopted and an ideal customer profile was identified. The challenge was operationalizing data in order to evaluate the ideal customer profile and provide relevant indications to the sales team.
Developing a credible account scoring model is the basis of further automation, but requires a foundation of high-quality data to be reliable.
"For our account-based scoring, you know the score is only as good as the data that you put into it, so DataFox is huge in that respect. They're feeding our scoring engine the right information to actually spit out something useful - it's proven itself to be working." - Jim McDonough, VP of Sales at Threat Stack
Understanding an account score becomes easy when you can trust the data and can easily understand the scoring criteria. Expanding on demographic signals to also consider firmographic signals, account scoring provides a comprehensive evaluation based on more than just lead generated information.
McDonough explains, "we use DataFox to identify key signals that feed into our scoring model. Where we see the best value is with the information they had for behind the firewall, and also the compelling events that were happening within a company such as new office expansion, new key hire, new key customer wins. That was really a differentiator."
The key to a successful account score is the ability to work at scale and iterate regularly. Account data powered by AI enables you to prioritize the right accounts in real time as your scoring model evolves.
"We've chosen to double down on DataFox simply because they have the best data for our market sweet spot: small and mid-market businesses. They also provide us with what we're looking for in terms of account scoring. We're finding that their signals are the best indicator of accounts we'll win," said Cheng.
Automating the account scoring process allows your sales team to gain back valuable selling time and your marketing team the ability to target high value accounts. With a convergence between sales and marketing teams, all three panelists agreed on the importance of personalization at scale. "We want to be able to touch as many accounts as we possibly can, but not sacrifice the quality of that outreach," said Schwab.
An account scoring model powered by AI and controlled by you ensures that accounts are prioritized by best fit, while allowing your team to gain back valuable workflow efficiencies.
Interested in building your firm's account-based strategy? Check out how DataFox's account scoring can help.