How Pusher Uses Customer Behavior Data to Drive Growth & Retention

Today, Hull hosted a webinar with Wes Bush of ProductLed and Chris Casey of Pusher to talk about a key component of executing a solid product-led strategy: leveraging customer behavior data.

As marketers, we all know the merits of demographic, firmographic, and technographic data by now. Third-party data vendors like ZoomInfo and Clearbit have become strongholds in our martech stacks for years. But what we've also begun to notice is that this type of attribute-based data can only go so far. To emphasize this point, I want to highlight this incredible quote from VP of product and innovation at Netflix, Todd Yellin:

It really doesn't matter if you are a 60-year-old woman or a 20-year-old man because a 20-year-old man can watch Say Yes To The Dress and a 60-year-old woman could watch Hellboy.

Todd Yellin, VP of product and innovation at Netflix

It's true. In B2B, just because someone has the the job title of your ideal customer profile or works in the industry of your ideal customer account doesn't necessarily mean they have a higher propensity to buy or upgrade their subscription with your company.

To combat false sense of hope in these types of scenarios, we are turning our attention to a different type of data source, one that is often underutilized in B2B, yet highly valuable: behavioral data.

Watch the replay and view the slides

What is customer behavior data? Where is it stored?

Customer behavior data is information pertaining to a customer’s interactions with your company, which can vary depending on the actions your company wants its prospects and customers to take. For Pusher, behavior they tracked included things like:

  • Did a user create an account?
  • Did they invite a user to join their organization/account?
  • Did they create certain apps?
  • How many apps?
  • Have they upgraded to a different plan?
  • Did they view certain resource, pricing, or “get started” web pages?
  • How many times did the user change their plan?
  • Have they added a webhook to their organization/account?
  • How much data are they using on a daily basis?

Behavioral data is often stored in backend databases; data warehouses like Snowflake, BigQuery, and PostgreSQL; javascript tracking tags; and data lakes.

Pusher's goals

Pusher had two goals in mind when it came to putting their data to use:

  1. Grow and acquire: Convert “freemium” users to paid self-service, and paid self-service users to enterprise customers.
  2. Retain and upsell: Generate incremental revenue from customers reaching plan limits, increase feature adoption, and prevent churn.

Growth & acquisition: The strategy, the stack, and the results

Pusher had hundreds of “freemium” users signing up on a monthly basis, without a scalable, efficient way for their go-to-market team to target and convert them. What they ultimately did to help prioritize these users was combine data that helped them identify fit and data that helped them detect interest to stack-rank individuals to focus on.

Pusher's Growth & Acquisition Stack

In order to generate data points that would help them in this prioritization endeavor, Pusher leveraged Hull's Processor, a real-time data transformation and editing tool, extensively.

With the Processor, Pusher was able to:

  • Compute new attributes: Generate a new customer plan ranking when customer changes their plan
  • Log and timestamp any behavior: Date customer first created a new app or instance
  • Log and timestamp key milestones: Customer created first 10 connections

Chris Casey, Senior Solutions Engineer at Pusher, has said that prior to implementing a customer data platform like Hull and executing on their strategy, the qualification process was tedious and manual. Now, he's pleased to share some promising early results:

  • Lead qualification has been made much simpler, automated, more manageable, and more efficient through focused efforts
  • Higher email response rates: 10% average response rate
  • Ability to personalize outreach with fewer leads to focus on
  • Ability to experiment quickly

Retention & upsell: The strategy, the stack, and the results

In addition to growth and acquisition of new paying customers, Pusher wanted to work towards their goal of retaining and upselling existing ones. Pusher started with a few smaller, "low-hanging fruit" efforts in the form of automated email campaigns designed to upgrade customers reaching plan limits.

Pusher's Retention & Upsell Stack

A key component of their strategy was to utilize Hull's segmentation feature, which allowed them to create highly-specific email audiences based on certain actions (like "Reached plan limit within X days").

Pusher Segmentation

While Chris admits they are still in the early stages of executing on their retention and upsell strategies, he sees a lot of promise in the ability to quickly experiment and iterate with the help of the Hull platform.

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Angela Sun

Angela brings over a decade of B2B technology marketing experience to her role as the Director of Marketing at Hull. Prior to Hull, she spent 5 years at utility data aggregator, Urjanet, where she held various roles in demand generation, marketing operations, and product marketing.