Embedded Analytics

3 Pitfalls to Avoid when Modernizing In-App Analytics

By Michelle Gardner
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Updating the analytics features in an existing application can be tricky. Oftentimes, it ends up being one of those constantly pushed-off projects – that is, until you start feeling the pains of customer churn and diminished revenue. That’s when enhancing analytics goes from “nice to have” to “needed yesterday.”

By establishing a deployment plan for modern analytics, you’ll set your project up for success. A blueprint provides the framework you need to develop a product that works and which users are excited to adopt. Because after all, why offer analytics if no one actually uses them?

>> New Findings around Analytics Adoption: 2017 State of Analytics Adoption Report <<

But even with a perfect blueprint in place, you’ll still have a few risks to watch out for. Watch out for these three common pitfalls when modernizing analytics – and follow our tips to mitigate them.


Risk: Nice Dashboard, But No Data

Resolution: Don’t let your app get ahead of your data. Structure your project to ensure there’s always something to show and validate at each stage of the review process. Remember that when it comes to updating embedded analytics in an existing product, you may have some work to do to develop a data tier that will ultimately support your solution.

Also take care to stagger your project timeline so the data architecture is ready before development begins. Start validating data early, and do it often. No one loves doing this, but if the first thing your users see is numbers that are off, your analytics project will launch with lower user adoption than you’d like. Find people who can validate data and get them to participate early to make sure you launch with accurate data.


Risk: User Count = 0

Resolution: It’s a product manager’s worst nightmare: You launch a product update with gorgeous new analytics, but no one’s using it. Fortunately, you can prevent this by involving your audience early and often.

Start by identifying the different personas who will be using your solution and interviewing them. In your interviews, you’re looking to see how people use information or how they’re unable to use information. Consider who will be using the analytics, in what context they need the information, and how they prefer to work.

Conduct frequent reviews with your users. They’ll serve as ambassadors to the rest of your user audience, helping to ensure high adoption as soon as the product hits their desks.


Risk: User Count = The World

Resolution: This problem may be a good one to have, but it can still be daunting. If you launch and have more users than you expected, you risk being buried under enhancement requests and suggestions for new features.

Just don’t take on the whole world at once. The blueprint method can help you even after you’ve updated your analytics features. Keep a log of your users’ feedback, then go back and interview everyone who submitted requests to find out what they really need. Prioritize enhancements across future project phases. Then set up a new blueprint for each set of enhancements.

Ready to modernize the analytics in your application? Start your project plan with the ebook: Blueprint to Modern Analytics: A Step-by-Step Guide to Enhancing Your BI Offerings


Originally published January 26, 2017; updated on August 9th, 2017

About the Author

Michelle Gardner is the Director of Corporate Marketing & Communications at Logi Analytics. She has over a decade of experience writing and editing content, with a specialty in software and technology.