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Embedded Analytics

Are You Headed for the Analytics Cliff?

By Michelle Gardner | September 4, 2018
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When was the last time you updated your analytics—or even took a hard look? Don’t feel guilty if it’s been a while. Even when there are minor indicators of trouble, many companies put analytics projects on the backburner or implement service packs as a Band-Aid solution.

What companies don’t realize, however, is that once analytics begin to fail, time is limited. Application teams that are not quick to act risk losing valuable revenue and customers. Fortunately, if you know the signs, you can avoid a catastrophe.

>> Related: Blueprint to Modern Analytics <<

Are you headed for the analytics cliff? Keep an eye out for these clear indicators that your analytics is failing:

Sign #1: Long Queue of Ad Hoc Requests

Is your queue of ad hoc requests constantly getting longer? Most companies start their analytics journeys by adding basic dashboards and reports to their applications. This satisfies users for a short period of time, but within a few months, users inevitably want more. Maybe they want to explore data on their own or connect new data sources to the application.

Eventually, you end up with a long queue of ad hoc requests for new features and capabilities. When you ignore these requests, you risk unhappy customers and skyrocketing churn rates. If you’re struggling to keep up with the influx—much less get ahead of it—you may be heading for the analytics cliff.

Sign #2: Unhappy Users & Poor Engagement

Are your customers becoming more vocal about what they don’t like about your embedded analytics? Dissatisfied customers, and in turn, poor user engagement, is a clear indication something is wrong. Ask yourself these questions to determine if your application is in trouble:

  • Basic adoption: How many users are regularly accessing the application’s dashboards and reports?
  • Stickiness: Are users spending more or less time in the embedded analytics?
  • The eject button: Have you seen an increase in users exporting data outside of your application to do their own analysis?

The more valuable your embedded dashboards and reports are, the more user engagement you’ll see. Forward-thinking application teams are adding value to their embedded analytics by going beyond basic capabilities.

Sign #3: Losing Customers to Competitors

When customers start abandoning your application for the competition, you’re fast approaching an analytics cliff. Whether you like it or not, you’re stacked against your competitors. If they’re innovating their analytics while yours stay stagnant, you’ll soon lose ground (if you haven’t already).

Companies that want to use embedded analytics as a competitive advantage or a source of revenue can’t afford to put off updates. As soon as your features start to lag behind the competition, you’ll be forced to upgrade just to catch up. And if your customers have started to churn, you’ll be faced with the overwhelming task of winning back frustrated customers or winning over new ones.

Sign #4: Revenue Impact

All the previous indicators were part of a slow and steady decline. By this point, you’re teetering on the edge of the analytics cliff. Revenue impact can come in many forms, including:

  • Declining win rate
  • Slowing pipeline progression
  • Decreasing renewals
  • Drop in sales of analytics modules

A two percent reduction in revenue can be an anomaly, or an indication of a downward trend. Some software companies make the mistake of ignoring such a small decrease. But even slowing rates of growth can be disastrous. According to a recent McKinsey study, “Grow Fast or Die Slow,” company growth yields greater returns and matters more than margins or cost structure. If a software company grows less than 20 percent annually, they have a 92 percent chance of failure. Revenue impact—no matter how small—is a sign that it’s definitely time to act.

To learn more, read our ebook: 5 Early Indicators Your Analytics Will Fail >

 

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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