Perhaps you’re familiar with Scratch, a programming language developed to teach children as young as 8 the basics of learning to code software. Young coders create animated stories and projects by snapping so-called coding blocks together. They can then share them with others creating projects in the Scratch community.
In talking about the MIT Media Lab project in a TED Talk, there’s an interesting moment in which its leader, Mitch Resnick, muses that perhaps the audience isn’t all that impressed that children as young as 8 can create animated and interactive cartoons with the software. After all, they’re digital natives, he says.
But, he goes on to explain, “I’m sort of skeptical about this term. Young people today have lots of experience interacting with technologies, but a lot less so of creating with new technologies and expressing themselves with new technologies,” he said. “It’s almost as if they can read, but not write, with new technologies.”
That statement offers lessons, I think, for our purposes in product management. How are we ensuring that our users are more deeply engaged with our technologies – such that they’re not just interacting with them, but using them to create value for their own businesses? How do we encourage fluency with our software?
Reaching our users while they’re using our software – and delivering a contextually relevant message that would resonate with them at that particular moment – is crucial to more deeply engaging them. It’s something that in-app messaging helps us to achieve.
But what type of in-app messaging strategy are you relying on to reach your audience? By “hard-coding” messages to be delivered at specific thresholds, you are only scratching the surface and can miss opportunities to truly meet the needs of our users, and drive deeper engagement with the technology.
Consider a message that asks new users for feedback, “How do you like the application?” but since it is hard-coded it automatically displays two weeks after a user first runs the product. The same message is delivered to all users whether they used the application for two hours, 20 hours, or more. Without the data that would lend insight into the users’ level of experience with the software, feedback received from the user is difficult to put into context. It’s hard to gain actionable insights that will help internal stakeholders do everything from define content and marketing campaigns, to sales strategies to informing feature development that will enable the end-user to derive even more value from the product.
Now consider the same scenario, but the in-app messages are driven by software usage analytics. Instead of choosing a fixed window of time, you can trigger the feedback question to display when a user crosses a certain usage threshold, or perhaps, more importantly, fails to do so within a specified time. But the power of dynamic, in-app messaging driven by usage analytics doesn't stop there. It enables your team to leverage any data point you are collecting and implement a strategy to both learn from and educate users. By leveraging usage data, in-application messaging can instantly target users that fit certain criteria – by geography, runtime, system attributes, feature usage, your own custom properties, and more. Messages hard-coded into the software, on the other hand, require new builds each time to update messaging content, and do not allow for the sort of experimentation in campaigns that can be used to see what works, and what doesn’t.
Dynamic, in-app messages can both push and pull more contextually relevant information to your users – providing deeper dives into functionality for power users, and more instructional content for users who seem to need encouragement.
If you are hard-coding your in-app messages you are taking a “set-it-and-forget-it” approach that is as outdated as the Ronco product that made that catchphrase famous (if you do not remember that commercial or catchphrase you have proven my point). When you are competing for user engagement and product adoption, you need a more data-driven, dynamic in-app messaging platform to effectively communicate with your users. You need to set it, measure it, iterate it, and improve it while also evolving the messaging campaigns based on user behavior within you application.
Keith is Revulytics’ VP, Software Analytics and was the co-founder and CEO of Trackerbird Software Analytics before the company was acquired by Revulytics in 2016. Following the acquisition, Keith joined the Revulytics team and is now responsible for the strategic direction and growth of the Usage Analytics business within the company. Prior to founding Trackerbird, Keith held senior product roles at GFI Software where he was responsible for the product roadmap and revenue growth for various security products in the company's portfolio. Keith also brings with him 10 years of IT consultancy experience in the SMB space. Keith has a Masters in Computer Science from the University of Malta, specializing in high performance computing.
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