Adding the Customer Voice into Product Development with Usage Analytics Data

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Click to learn more about author Victor DeMarines.

Product managers, on average, spend just seven hours a month talking to customers in non-sales situations, according to data from the recently released Pragmatic Marketing 2018 Product Management and Marketing survey. That means, taking the average 46-hour work week reported by respondents, product managers are spending roughly 4 percent of their time every month meeting with customers. That might not seem so terrible until you consider that by comparison, respondents said they spent nearly half the month managing email and attending meetings.

Incorporating the customer voice deeply in the product development process is no longer a competitive advantage: it’s becoming table stakes. So why is there such a huge disconnect between expectation and execution? Because it’s hard. Customers don’t have a lot of time. It’s tough to get to the end user in the first place. And you and your team have so many other demands of your roles.

Customer-centric product development strategies will always require actually speaking with customers. But the most innovative organizations use data to augment the development process, and boost that 4 percent without sapping time from the other 96 percent. Here are some lessons on how three ISVs have incorporated usage data in their development processes offer innovative use cases on where to start.

  1. Designing a New User Interface

A CAD/CAM software provider wanted to revamp a 10-year-old user interface to make it more intuitive and attract newer audiences, while at the same time ensuring it continued to deliver robust functionality critical to the business processes of its existing customers, some who had been using it for decades. This was no easy task for a product that had shipped four major releases in five years, as well as contained some 1,200 features and a code base with both .NET managed components and unmanaged C++.

In designing the new user interface, one of the primary tasks was figuring out which features to group together, and how to promote them to different audiences. Runtime analysis enabled them to break down those 1,200 features, and further segment that by system attributes, geography and more to discover different usage scenarios. That’s a process the company said would have been impossible with manual analysis.

The entire redesign took 18 months, about half the time it would have taken without usage data. What’s more, because the company could track all enrolled beta testers, feedback came back better and faster. Saving those 18 months also freed time and resources to focus on other areas of the product.

  1. Focusing R&D Spend

Having launched long before any sort of runtime intelligence was available, a software provider that sells tools for creative professionals had very little visibility into what was happening with its long-term customer base, some of whom had been using the software for decades. Two things increased the imperative for data-driven product development. Recently, the company had shifted its development process toward Agile Methodologies, obviously necessitating that the customer’s voice be a more integral part of the development process.  What’s more, with decades of users, the company found itself supporting every different browser flavor and operating system, out of fear that it would damage customer relationships without blanket support.

It leveraged Usage Intelligence to break down feature use by system attributes – with the ability to segment and examine the customer base and its feature use by operating system, browser and more. With that granular view, it could redirect resources and support for operating systems and browsers with broad adoption, and reexamine and reduce support for edge cases and configurations that were rarely used. That amounted to a savings of $10,000 to $20,000 per release in QA time alone.

As an added benefit, Usage Intelligence gives the company access to information from the right users. Previously, it would survey customers on, for instance, file types for which they needed support. But those communications would often reach IT, not the creative users who actually work with the tools. Usage Intelligence lends a line directly to actual users, giving access to real-time information in a way that time and resource-intensive surveys never could.

  1. Designing Killer Features

One of the challenges a software vendor that sells Building Information Modeling (BIM) QA and control tools for the construction industry faced was better defining the needs of its broad audience of users, which spans professionals in multiple disciplines necessary for the construction of a building or space. By accessing information on use in real-time, some of the industry-leading features of its product could work even better for its users. For instance, analysis of events and system attributes helped the company see that many customers were using more powerful hardware than developers were designing software to work with. Using this information, the developers could design features that required more powerful hardware, in turn driving efficiencies for its customers.

Product managers can augment development strategies with technology, and drive the customer voice into development simply by examining and analyzing use.

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