BI Trends

3 Insider Secrets to Boosting User Adoption

By Mya Nguyen
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Acquiring a new customer can be 5 to 25 percent more expensive than retaining an existing customer. However, successfully making an app “sticky” is no easy task. This is exactly where embedded analytics can step up to offer effectiveness by delivering value in every use of the application.

Analytics are an indispensable tool and 82% of users consider it to be very to extremely significant to their role and 77% of knowledge workers claimed they would adopt a new analytics solution if it were embedded. However, you wouldn’t want your hard work and investment into analytics to go to waste on low user adoption.

Here are three insider secrets to keep in mind when trying to increase product adoption and usage with data analytics.

Step 1: Provide built-in data analytics

Granting users access to data alone isn’t enough to provide value that is useful for day-to-day operations. Instead, with the sheer avalanche of data that is being collected, providing end users with the ability to make strategic data-driven decisions within the current application is crucial. According to a recent report from Logi,  83 percent of business users seek the chance to work and stay in a single application when a decision must be made.

Users have an unmet and growing need for deeper interaction with their data. More contextualized insights can be gained when analytics are integrated directly into workflows. The easier you make it for users to access analytics, the more likely they are to continue to return to your application.

Step 2: Put the data in context

Embedding analytics is a good first step, but it’s important to think deeply about the context in which users need analytics when doing so. When designing dashboards and data visualizations, always aim to create a cohesive user experience that not only gives users access to their data, but the context they need to make data-driven decisions.

By providing data in context, you reduce the time to action and enrich the user workflow, increase interactivity, and boost productivity. It can also boost user comprehension of data when analytics are provided in a context they are already more familiar with.

Embedded analytics gives users the full view of their data with a consistent looks and feel, so users can contextualize insights and make a direct connection between your app and their businesses successes.

Step 3: Deliver intuitive and customized self-service

Demand for analytics is no longer for data analysts alone, every user within an organization has a need for data. From receptionists to senior leadership, and all the teams in between, everyone should be able to make data-driven decisions within your application. However, each user persona has unique needs and skill levels. If you can provide customizable self-service capabilities that match this range of skillsets, user adoption will naturally increase.

Modern BI with customized self-service helps increase reliance on an application and reduce requests for new visualizations as more users are able to leverage analytics. A bonus for developers is that deploying self-service frees up time and resources for more critical application needs because it decreases support tickets. When users already have the information they need in an intuitive format, they won’t feel overwhelmed or need assistance.

Final Thoughts

Overall, when developments teams focus on enriching the user experience and driving business value to their end users through analytics, it’s only natural for user adoption to skyrocket. Don’t just take our word for it. Customer experience platform provider Emplifi was able to grow customer adoption by 25 percent within the first 30 days of implementing Logi’s embedded self-service and customizable analytics.

Want to learn more about the key functionality of embedded analytics that supports user adoption? Watch our webinar, Insider Secrets to Boosting User Adoption, co-hosted by me and Seth Hutcheson, Product Manager.

Originally published September 10, 2021

About the Author

Mya Nguyen is the Product Marketing Manager at Logi Analytics. She has over 6 years of experience working in product marketing and product management. She has previously held positions at a number of technology companies, including Amazon, UiPath, Kognetics, and Hoiio, where she gained solid experience helping organizations make data-driven decisions.