Development Tips

Choosing an Analytics Development Approach: How to Optimize Your Business Benefits

By Michelle Gardner
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The question of embedding analytics in an application has moved from “Whether to?” to “How to?” But on the road to embedded analytics, many companies get caught up in the “build versus buy” debate. This inevitably stalls projects and delays time to revenue.

>> Related: Why “Build or Buy?” Is the Wrong Question for Analytics <<

As it turns out, “build or buy” is a false dichotomy. Application teams searching for an analytics solution have a third option: They can take a combined approach by purchasing an analytics development platform and customizing it. This method lets companies get to market faster than building and supports more sophisticated features than buying a bolt-on analytics solution.

How do these three development methods—build, buy, or the combined approach—compare?

The first instinct for many software teams is to build exactly what they want using open-source code libraries and charting components. This may work well, at least until customers began expecting more sophisticated capabilities. According to the 2018 State of Embedded Analytics Report, end users are less satisfied with homegrown analytics compared to a combined approach. In addition, application teams that build analytics on their own using custom code and components see worse results in terms of user experience, differentiation from the competition, and attracting new users.

If building analytics on your own is no longer a realistic option for long-term success, application teams must buy a solution. But they still have two choices: Either embed a bolt-on data discovery tool or take a combined approach and leverage an analytics development platform.

At first glance, buying a solution from a third-party vendor may seem like the way to go—especially if you’ve fallen behind the market and need a way to quickly update your analytics. But time and again, companies that choose a bolt-on approach suffer in the long run. The 2018 State of Embedded Analytics Report shows that teams that buy a bolt-on analytics solution see far fewer business benefits than those choosing to build their own solution or take a combined approach by purchasing an analytics development platform.

Compared to buying a bolt-on solution, a combined approach supports a more differentiated product, improves win rates, reduces customer churn, and boosts overall revenue. It also positively impacts the end users, resulting in better user adoption, user satisfaction, and user experiences.

In particular, a large gap exists when it comes to increasing overall revenue. According to the survey, application teams that took a combined approach when embedding analytics were 19 percentage points more likely to increase revenue than those that bought a bolt-on solution.

This revenue gap may be due in part to an unintended price cap that results from bolt-on solutions. Seventy-four percent of commercial applications taking a combined approach are able to do so. This is significantly more than the 60 percent of commercial companies that bought a bolt-on solution.

Why does the combined approach enable companies to charge more? Because bolt-on solutions tend to support only limited capabilities and focus on commoditized features such as standard interactive dashboards and data visualizations, while taking a combined approach means companies are more likely to embed sophisticated analytics capabilities that set their applications apart from the competition.

It’s clear that companies with the most successful analytic applications have one thing in common: They don’t build OR buy, strictly speaking. Instead, they leverage an analytics development platform to quickly deliver the most robust capabilities to the market.

Read the 2018 State of Embedded Analytics Report >



Originally published June 26, 2018

About the Author

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