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Use Cases · 5 min read

Benchmark Email uses Data Destinations to automate workflows and activate data

Max Cobert
Posted December 01, 2023
Benchmark Email uses Data Destinations to automate workflows and activate data

Across industries, many businesses grapple with discontinuity between digital data sources. After all, not every product management, UX, engineering, or sales team is using the exact same tools and data sources day-to-day. 

To address this complex issue, FullStory offers Data Destinations—a way to merge and structure digital experience data from disparate sources into your data warehouse for easier access and deeper analysis. 

While there are countless potential uses for Data Destinations, we’re going to zoom in on one such use case here. Meet Benchmark Email, a global email marketing provider offering straightforward marketing solutions for brands worldwide. 

We chatted with Benchmark Email’s VP of Product Marketing, Allie Wolff, about how they’re using FullStory’s Data Destinations to compile behavioral data in Snowflake—ultimately streamlining everyday processes and growing revenue. (Click here to learn more about FullStory and Snowflake’s partnership.) 


The challenge

Benchmark began looking for a solution like Data Destinations out of a desire for a heavily product-led sales model. Because Benchmark offers a robust free tier, they experience large amounts of top-of-funnel traffic. For a time, Benchmark’s sales team followed up on every single signup, calling and emailing all free-tier users to promote expansion to paid accounts. 

How Allie sums up Benchmark’s challenge:

“We have a low deal size when people are first becoming customers, so we were trying to implement more of a product-led sales model where we’ve historically been very sales-led. Having our teams call every user who signed up just wasn’t scalable with the amount of top-of-funnel traffic we have. We wanted to tie in usage data to know where to focus our efforts, and that’s where Data Destinations came in.”

But with so many free accounts, this tactic proved to be inefficient and unscalable for their business and sales teams. Even when they moved to automated in-app communications for upsell plays, they struggled to see results with one-size-fits-all messaging. 


The need

Benchmark’s goal was simple: They wanted their sales and expansion motions to be as personalized and as automated as possible. 

However, personalization and automation can seem like oxymorons in the world of digital experiences. Benchmark’s vision was to be able to tie customer and product usage data directly into their communication strategy. This would allow them to train their Machine Learning (ML) models to provide highly contextual in-app messaging—intercepting users at the right place and right time inside the product.

How Allie sums up Benchmark’s need:

“We want to make sure all of our in-app messaging is super contextualized. We needed to get our data out of FullStory and use it to inform these ML models so that we could understand the actions that users were taking on the path to conversion. Once we understood those paths, we’d be able to replicate the journeys for more users.”

Previously, Benchmark had native events that were used to trigger user outreach through Intercom, but found that labeling in-app events quickly became too messy to keep up with. They needed a way to monitor behavior in their app without manual tagging. 


The solution

Benchmark evaluated several different analytics platforms in search of a solution to their messaging and expansion challenges. Ultimately, one of Benchmark’s partners, Toplyne, introduced them to Data Destinations from FullStory. Since Benchmark already had FullStory in their digital experience analytics tech stack, it was a natural move to begin leveraging this relatively new capability to meet their business’s evolving needs. (Learn more about Toplyne’s integration with FullStory in our partner directory here.)

How Allie sums up the solution:

“When we have this holistic view of our data between FullStory, Intercom, and Toplyne, we can identify commonalities in experiences of users who eventually converted to paid accounts. I can then use that information to build out playbooks for how we should message users to nudge them toward conversion based on their actions.”

With the integration between Toplyne and FullStory, Benchmark is able to gain a holistic view of their data and understand the actions users are taking on the path to conversion. By using ML to study the actions of users who eventually converted to a paid account, Benchmark set up playbooks for guiding users toward those actions.

The outcome

With Data Destinations, Benchmark is able to identify the specific users who are most likely to convert to paid accounts—enabling them to focus their sales efforts rather than treating every free user the same. 

How Allie sums up the outcome:

“We still have a standard onboarding flow for all free tier accounts, but Toplyne and Data Destinations identify, say, the top 20 most qualified accounts each day. Then, we push those accounts into personalized workflows—so a highly qualified account might receive a note from an account executive rather than a generic in-app message.”

Benchmark didn’t have the ability to identify those likely-to-convert users before, which left their sales teams casting an extremely wide, untailored net for account upgrades. In addition to providing more focused, personalized messaging, these automated processes reduce the amount of manual outreach the sales team has to do and gives them back time to work on expansion and retention plays.  

For example, Benchmark is also able to use FullStory data to identify users who are approaching the contact limits in their plans, so sales team members can contact them with personalized expansion offers. 

What else to know about Data Destinations

This is just one use case—there’s a world of possibilities for using Data Destinations at your organization. Here are a few other ways you can leverage this capability:

  • Define segments of users who were impacted by a bug, then push that segment into an in-app messaging platform to acknowledge the issue

  • Train fraud detection models on behavioral data to be able to predict contain, and block threats

  • Merge FullStory and CRM data to build a customer churn prediction model

See my complete overview of Data Destinations here.


Ready to customize your digital customer experience and save time for busy teams? Get in touch with us here.

Author
Max CobertProduct Manager

About the author

Max is accomplished product leader with a focus in data-driven software products. Interests include sour beers and using the world's data to make everyone's lives happier, easier and more efficient.

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