Integrating the analytics capabilities into your application can be easier than you think
Today, the ability to create and explore dashboards and reports, embedded directly into the apps your customers use every day, is no longer a luxury but a necessity to keep your product competitive and deliver value to users.
Embedded analytics brings many benefits for different groups. For end users, it’s a valuable tool to explore their data and discover new insights. For analysts, it’s an integral capability for advanced performance analysis. For product managers, it’s the best way to enrich and cultivate a data-driven experience for your customers with the latest analytical capabilities, built-in.
Moving away from decisions based on instinct toward decisions based on analytics and metrics delivered by centralized systems is one of the most impactful changes you can drive today. But for product managers in the business of delivering software or utilizing an application to drive customer interaction, the choices available for embedding analytics is a looming challenge.
This article covers the key challenges, scenarios and checklist considerations product managers need to tick off before implementing any type of embedded analytics solution.
Embedded Analytics: A Business Case for Buy vs. Build
Typically, the decision around embedded analytics boils down to build or buy.
Even with a need for fast technical integration and time-to-market pressures, many product teams first lean toward getting in-house developers to build embedded analytics into their app.
It’s an understandable first thought, given many have a specific vision for their app that a third-party might not �?get’ immediately. But opting to build-in analytics more often than not leads to long-term challenges that aren’t always initially obvious.
The fact is creating an analytics platform from scratch is a complex task that takes years of work to create and refine. Aside from the advanced data expertise and technical integration required, having your developers focus on embedding analytics means they now have to:
- Face a very high investment cost to recruit the necessary skills for implementation.
- Provide all support, maintenance and upgrades for your homegrown BI functionality.
- Replicate the look and feel of your core application to ensure UX consistency.
- Match the analytical features of specialist BI solutions—a near impossible task.
With the time and skills needed to build your own analytics into your app from the ground up, you could face higher costs, increased risk and delayed time-to-market for your product—not to mention less time innovating and improving the core product experience for your users.
Your users ultimately expect to have data accessible to them for their day-to-day work. When they use your product, they will demand a certain level of reporting and analysis comparable to the BI tools they may already use in their own businesses at the moment—and yes, it will go beyond just having basic dashboards. If you don’t have confident answers for the most common questions required before building an embedded solution in-house—do you have the expertise, the manpower, time and knowledge—it’s not advised to pursue the build path.
So, what about buying an embedded analytics solution for your application?
What to Look for in an Embedded Analytics BI Solution
Buying an established embedded analytics solution often does away with many of the problems of building it.
You can shift away from home-grown reporting to a proven platform that can seamlessly integrate custom analytics into your app, amplify the reach of your product by engaging new and existing users with the latest analytical features, and even automate data discovery and analysis so you gain competitive advantage—though the last capability depends on the particular vendor.
However, buying comes with its own very important considerations that your product team and business as a whole need to evaluate and answer before making a decision. Below, we list the most important things to look for in both the embedded solution and the partner behind it.
Does it include everything I need to meet end-to-end operational reporting needs?
Your users will have a range of functional needs from the embedded analytics solution you buy, so the first thing you must answer is whether it can cater to their day-to-day work and provide access to advanced analytics. For instance, your customers want to know what to do next: Some might only need tabular reports (traditional), while others will demand richly visualized and interactive dashboards that drive action (modern). Eventually, some may look to use automation and AI in their analysis (augmented). The best options are those vendors that let you embed it all—dashboards, authoring, charts, collaboration, data preparation and modelling, admin and security. How each element is embedded (iFrames, JavaScript libraries with REST API calls) and where embedded code can run (cloud, desktop, mobile, web) is just as important to factor in, too. It’s not just about having dashboards in your app, but ensuring you have future-proof capability that continuously scales with your users as their data needs grow.
Can the solution be embedded seamlessly?
It’s not just all about having the best and latest features. A cohesive, seamless user experience between the analytics portion of your product and the core software itself is a big part of delivering an exceptional product, so when choosing to embed analytics, ensure the solution allows your team to have exceptional control to make it look like a part of your app rather than like one different app hosting another. Many modern embedded solutions allow you to white-label; this is recommended to allow for consistent design across your platform, as you will eliminate your users’ potential concerns around security, performance or support with using another product.
Can it help me ensure faster time to market?
A common problem with creating an embedded analytics solution in-house is the investment in time and money it takes to get your product to market with the new capabilities. It’s also difficult to ensure the integration process can be done as quickly and efficiently as desired. The embedded tool you buy should accelerate that process and significantly reduce the development cycle, so your team is able to begin using your new analytics within days instead of weeks and your devs stay focused on improving your product’s core value instead of configuring reports.
Next Steps
Selecting an embedded analytics product can be a difficult task, but so long as you keep your product and analytics objectives aligned and follow best practices checklists, integrating the latest analysis capabilities into your application is not as far-off a future as you may think.
