Host Analytics

Customer Success Snapshot

At a Glance


average deal size


MQL Volume


leads to MQLs conversion


ratio of bad leads

Our Infer model makes all the difference when it comes to sales and marketing alignment.

Infer infuses our best-of-breed technologies with predictive intelligence, creating powerful workflows that have helped align the organization, increase our average deal size, and boost our overall revenue within two years. That’s why Infer is one of our favorite solutions -- it helps us orchestrate smooth, seamless workflows across our entire martech stack.
Nick Ezzo

Nick EzzoVP of Demand Generation, Host Analytics


Location: Redwood City, CA

Infer Customer Since: 2014

Company Size: 201-500 employees

Systems: LeanData, Salesforce, Marketo, HubSpot(CMS)

Infer Products:Predictive Scoring (Leads and Accounts Models)


Host Analytics, a leader in cloud-based financial applications, knows a thing or two about making data actionable. Its executives run the company with a “math of the business” approach, determining the metrics they need to hit using reverse waterfall calculations. This starts with annual recurring revenue (ARR) and average selling price (ASP) targets, and cascades up to precise goals for how many deals, pipeline opportunities (at each stage), and ultimately MQLs they need to hit each month.

With the entire company focused on MQLs as a leading indicator of whether it will hit its revenue targets, the marketing team needed a better way to evaluate and prioritize good leads. This included reducing spend on marketing channels that deliver bad leads and gaining real-time insight into how marketing programs are performing. On the sales side, the team couldn’t risk spreading itself too thin by calling every lead that exhibited any type of interest.


First, Host Analytics implemented a fit-first predictive scoring model from Infer to identify what a good customer really looks like. Infer’s fit model leverages Host Analytics’ existing internal customer data from internal systems of record like Salesforce and Marketo, along with external data points from Infer, to predict how likely someone is to buy a Host Analytics solution.


This predictive-driven approach enabled the company to align around a new MQL definition in which only prospects categorized as Infer A, B and C-Leads (the company’s top 50% of incoming leads by volume) are sent to the sales development team for follow up.

The company also leveraged Infer to build an array of Salesforce dashboards, which provide predictive metrics that help guide decision making, track performance, spot trends and prevent looming problems.The marketing team uses these insights to understand how many high-quality leads a certain channel historically produced, as well as the typical conversion rates for each type of lead -- enabling them to accurately predict how many prospects will convert into sales opportunities in a given month.


Executive dashboards monitor lead quality across several vendors and programs (such as online retargeting, account-based advertising, content marketing, drip nurture emails and in-person events), so that Host Analytics can accurately view its cost-per-good-lead for each campaign. The sales development team also leverages its dashboard to monitor the volumes of Infer A-, B- and C-Leads across each team member.


Every company should use predictive analytics to gain clear customer parameters that the whole organization can agree on – now that we have predictive scores, I’ll never go back.
Nick Ezzo

Nick EzzoVP of Demand Generation, Host Analytics

  • Host Analytics was able to make a big impact on revenue by prioritizing the leads that are most likely to convert to customers.
  • The company clarified its murky definition of an MQL with proven data-driven criteria, building trust in the scores and bringing sales and marketing into deeper alignment.
  • Reps are able to prioritize and focus on the best-quality leads, boosting sales productivity and efficiency by aligning effort to impact where revenue concentration is the highest.
  • Marketing can test-and-invest in various marketing campaigns, optimizing marketing spend around the programs and channels that generate the hottest leads for sales to follow up on.

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