Product Teams

Target, Target, Target

Published Jan 10, 2017

In the old joke, a musician lost on the streets of New York asks a stranger, “How do you get to Carnegie Hall?” The answer—“Practice, practice, practice.” When it comes to in-app messaging, we see interaction rates anywhere from 2% to 50%+. To paraphrase, how do you get (closer) to 50%? Target, target, target!

The difference in results between well and poorly executed in-app messaging efforts can be huge. Tools like Pendo give you flexibility and the power to get something in front of your customers within seconds, without burdening your engineers with small content tweaks. That power is exciting. But, in the excitement, it’s important to remember that the goal of in-app messaging is not “impressions,” it’s outcomes.

It’s important to remember that the goal of in-app messaging is not “impressions,” it’s outcomes.

When teams first implement in-app messaging, they often get a little trigger-happy and inadvertently start spamming users. But good in-app messaging should never feel like spam. It should feel natural and contextual, like a useful part of the product. Some of your in-app efforts will be marketing-type campaigns where a little bit of disruption is necessary. But when you’re dealing in the product it’s vital to take an integrated perspective that considers the customer’s needs.

Your customers are in the product to get work done and to get value. Knowing that presents a challenge and an opportunity: How can you make your in-app messaging a net positive for both your customers and your business?

The power to seize this opportunity lies in targeting. Data—including data on prior interactions with in-app messaging—is the key. We know this already to some degree from our marketing efforts, sales efforts, and training efforts. But in many organizations, the product is the last to get this treatment.

It’s hard to have too much targeting and segmentation. The list of types of information that can be used to refine your targeting goes on and on. Here is just a sampling of the types of data we see used to target in-app messaging:

  • Most recent NPS response
  • Length of time using the product
  • Use of feature(s)
  • Prior exploration in specific part of the product
  • Depth of exploration (how far did they get?)
  • Milestone or goal achieved
  • Prior access of knowledge-base article
  • Device type, operating system, or browser
  • Custom product settings and product version
  • Use of power-user oriented features
  • Days since prior visit
  • Visit frequency
  • Engagement level (measured in time per period, clicks per period, etc.)
  • Support ticket volume and support ticket severity
  • Current stage in sales cycle
  • Number of co-workers active in the product
  • Prior feedback and feature requests
  • Prior interaction with messaging
  • Attendance at customer conference or webinar
  • Customer health score or current churn prediction
  • Sales representative or customer success representative assigned
  • Annual revenue
  • Recent upgrades

Depending on your goals and your product, you’ll probably have more examples to add. So, get started!

In short, with in-app messaging, less is often more. It’s better to reach a small number of people with a message that’s truly valuable to them. Segment, segment, segment, and target, target, target, and then reflect on how your message is performing. Repeat as needed and you’re on your way to better-performing messaging.

John Cutler is a product management and UX consultant. His passions are UX research, evidence-driven product development, and empowering the front line to solve business and customer problems. For more of John’s writing visit his Medium profile or follow him on Twitter.  He is honored to team up with longtime friend and editor Katherine Maurer, a freelance editor and poet whose work has appeared in many pretty good literary journals. She is also a graduate student in clinical psychology, and drummer in the band Again is Already.