Deciding when to eliminate old features and versions that make it harder to evolve your product.
Using usage analytics to quantify the impact of removing legacy functionality.
For: Product Management and Software Development
Engineers at a leading practice management software provider were struggling to manage a feature written in legacy code with obsolete tools. Whenever engineering upgraded the UI, the feature would break -- costing scarce time and resources. Software product management wanted to drop the feature, but decision-makers were reluctant to do so for fear of alienating existing customers. The team didn’t have reliable information about how many customers still relied on this feature, so it kept delaying the decision to abandon it -- and its maintenance costs and frustrations continued to grow.
Engineering needed insight to more effectively manage software roadmaps and versions for maturing products. By accurately tracking software feature usage, they could ensure that valuable features could be maintained, low-value features abandoned, and resources freed to build new features customers will pay for.
By tracking software events with Revulytics Usage Intelligence, the company quantified the number of unique users who actively engaged with the legacy feature in question, discovering that few still did. Product management could now support a decision to abandon this feature with accurate, reliable data demonstrating that doing so would impact few customers.
Implemented continuous usage feedback loop to define better product roadmaps.
Using Revulytics software analytics and reporting dashboard, the company has implemented a continuous, automated feedback loop which helps them better manage eliminating old features and planning new ones. Software product management teams have detailed information they can use to eliminate time, money, and resources wasted on features that aren’t widely used or valued by customers. Since they can recognize shifting feature usage patterns more quickly and reliably, they are more effective at identifying UI design improvements that increase conversion and adoption rates.
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