In his book, “What Do You Want Your Customer to Become,” author and MIT Research fellow Michael Schrage challenges his readers to think beyond the traditional criteria that go into calculating what is agreed upon across industries as one of the most important metrics to measure – customer lifetime value.
It’s a sort of “ask not what your country can do for you,” paradigm that he introduces into the customer lifetime value conversation. “Making customers better makes better customers,” he writes. As such, he challenges leaders to measure “how effectively innovation investment increases customer health and wealth,” and to view customers more as “value-creating partners than as value-extraction targets.”
In fact, in workshops, he asks people to complete this sentence: ”Our customers become much more valuable when...” It’s a question that when thoughtfully contemplated prompts such answers as: “they give us good ideas, they evangelize for us on social media, they reduce our costs, they collaborate with us, they try our new products, they introduce us to their customers, and they share their data with us.”
What makes your customers more valuable?
It’s likely that your software is a component (or perhaps even the crux) of many of the initiatives that are driving long-term value for your customers’ customers. How are you ensuring that you are a partner on their innovation journey and that you are helping them innovate their products and the business models they use to sell them?
Usage analytics lends a unique window into how customers use our software that allows us to partner in a non-disruptive manner to continually innovate it – something that ultimately increases customer lifetime value.
Consider how you currently gain insight into your users’ journey with your product. Perhaps you seek input from a few customers with whom you’ve developed strong relationships over time. You may think that balancing that insight with user surveys and market research is enough to ensure you’re meeting the innovation needs of the majority of the customer base – but it’s more than likely not telling the whole story.
Here’s a real world example of this problem our customers have encountered. Insight from a few key (and vocal) users, coupled with sentiment on social media is pushing your team to lean toward engineering backward compatibility for a feature in a new release. It’s a costly decision, one that would take away development resources from pushing new functionality into the release.
By tracking software events with Revulytics Usage Intelligence, your company can quantify the actual number of unique users who actively engage with the legacy feature. Product management can support a decision to either support or abandon this feature with accurate, reliable data quantifying the total impacted customers (which is often just a few when dealing with legacy features).
In this scenario, many of our customers find the in-application messaging feature in Usage Intelligence to be beneficial in a few ways. It can launch surveys within the product so you can collect specific feedback (both quantitative and qualitative) from highly targeted users. In the case where the decision to sunset a legacy feature is reached, you can gracefully communicate that and give plenty of notice and opportunities for your customers to prepare for the transition. By incorporating these approaches, you’ve found ways to focus your budget and resources more wisely, while creating a more streamlined, user-centric product lineup.
In turn, using the Revulytics software usage analytics reporting dashboard, your company can implement a continuous, automated feedback loop which helps them better manage the process of eliminating old features and planning for new ones. Since you can now recognize shifting feature usage patterns more quickly and reliably, you are more effective at identifying UI design improvements that increase conversion and adoption rates.
You wouldn’t want to end support for a product that is being used by many customers, but moving them to a new version can save valuable maintenance resources. Having detailed data on customers usage helps create targeted information messages or upgrade offers focused on new features and capabilities. This customer obsession increases satisfaction and retention.
Keith is Revulytics’ VP, Software Analytics and was the co-founder and CEO of Trackerbird Software Analytics before the company was acquired by Revulytics in 2016. Following the acquisition, Keith joined the Revulytics team and is now responsible for the strategic direction and growth of the Usage Analytics business within the company. Prior to founding Trackerbird, Keith held senior product roles at GFI Software where he was responsible for the product roadmap and revenue growth for various security products in the company's portfolio. Keith also brings with him 10 years of IT consultancy experience in the SMB space. Keith has a Masters in Computer Science from the University of Malta, specializing in high performance computing.
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