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Embedded Analytics

Is the Price Right for Your Analytics?

By Michelle Gardner | January 18, 2018
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Today’s organizations are embedding analytics in commercial software applications at an exponential rate—and with 93 percent of applications offering some form of embedded analytics, chances are your organization is among them.

But are you making the most of these valuable capabilities? As estimated by independent software vendors and SaaS companies in our annual State of Embedded Analytics Report, analytics can contribute 54 percent of the overall value of software products. However, this added value doesn’t always translate to increased sales revenue.

>> Related: Embedded Analytics by the Numbers <<

If you’re charging too little (or too much) for your analytics, you could be missing out. Here’s why (and what you can do about it):

Charging Too Little

Packaging and pricing decisions are fundamental to software monetization and should never be made as an afterthought. Customers who absolutely need advanced capabilities like embedded self-service and the means to pull new data sources into the application are more than willing to pay more for them. If you do not raise the price of your analytics application, or only increase it slightly, you are leaving enormous amounts of potential revenue on the table.

Charging Too Much

Different software users perceive the value of analytics features differently. For some, a customizable dashboard of real-time metrics inside their primary application is all they need. Because sophisticated capabilities such as write-back and workflow actions would rarely be used, if at all, customers aren’t willing to pay more for them. If you significantly increase the price of your enhanced product for all your users, you risk upsetting customers who don’t care about and may never use the new features.

What You Can Do

One of the best methods for handling this range of customer needs and their willingness to pay more (or not) is to create tiered offerings. These are packages of analytics enhancements comprising feature sets of increasing value, priced accordingly.

To do so, you’ll need to do some customization. This doesn’t mean building a different offering for each type of user you want to target. Instead, build analytics enhancements just once, and use them strategically. With this approach, you turn features off and on through visibility controls, conditional logic, and your application’s security model. It allows you to offer some features to everyone and limit access to more advanced capabilities only to certain (paying) customers.

Learn more in our ebook: How to Package and Price Embedded Analytics.

 

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.

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