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Talking To HiPPOs: Easing Tough Conversations with Usage Analytics

Author
  • Keith Fenech

    Keith Fenech is vice president of software analytics at Revulytics and was the co-founder and CEO of Trackerbird Software Analytics before the company was acquired by Revulytics in 2016. 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.

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In a recent Pragmatic Institute survey, the ability to inspire others ranked high for product managers asked what they thought was both most important to career growth and most rewarded by their companies.

Crucial to the goal of inspiring others is ensuring that internal stakeholders feel heard during the roadmap development process. However, your responsibility is to properly balance what is best for the market in terms of product development with other internal perspectives. It’s like being a conductor: You must identify the elements and coach the musicians who make the music beautiful, and tone down or eliminate those that do not.

As you conduct, there is one particular sound that can overpower the others: the highest-paid person’s opinion (HiPPOs). Product teams must have a lot of difficult conversations, but the ones with HiPPOs are unique. You must listen to their input—which can vary in terms of validity and quality—and then thoughtfully incorporate it into your product roadmaps or tactical decisions where it makes sense. But you must also be able to confidently convey the results of your data analytics and your own experience and opinions when it comes to things that do not serve the product, customer or business.

Having hard data helps ease these conversations and enables the team to make a fact-based analysis about whether an opinion should be incorporated, making it easier to say “yes” and understandable to say “no.”

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Let’s look at how software usage data can help ease a series of hypothetical conversations with different HiPPOs, which are probably not so hypothetical to you and your team.

Top account manager: “Our big customer is not happy. They don’t want to upgrade because their favorite feature isn’t supported in the new release. Can we talk about supporting the legacy feature?”

Here’s a familiar scenario. A release that you’ve evangelized to customers about for months—during trade shows, at small meetings and with user communities—and which you thought they truly understood and bought into, is now in question because of the request of a single, albeit key, account. If you fulfill this request, key resources must be pulled off their current release work, jeopardizing the entire schedule.

Usage data can help you explore the value of supporting backward compatibility and avoid making a snap judgment. You can look at how users in the account leverage this particular feature—down to activity, runtime and machine architecture—and correlate that data with account information to help make a value-based analysis on whether the decision is actually good for business.

By looking at the way users move through a particular workflow, you can determine whether other functionality in the new release will meet their needs, and, if so, deliver targeted educational materials and training that will ease the upgrade.

The right content combined with the right training can encourage users to move and save you countless resources engineering backward compatibility and continuing to support it. On the other hand, if the data tells you it makes sense to support the customer request, your team has detailed information on the customer’s requirements to shorten the development cycle.

Marketing: “Twitter is blowing up with feedback about this bug. So are our customer forums. Can you put your team on fixing it right away?”

Your daily priorities can be sidetracked by calls from sales or marketing demanding immediate attention. How can you tell the difference between something truly urgent and something that affects only a handful of customers, but has been magnified by social media? With the ability to drill down to the operating system and architecture across the entire customer base, slicing and dicing it by geography, you can see how pervasive the problem is. Perhaps the issue only affects 10 noisy users on a specific Windows OS service pack. Data helps you make better decisions on where your developers’ time could be best spent and gives you the confidence to relay that decision knowing that it does not affect most of your customer base.

What’s more, you can have better conversations with other stakeholders in the company. Now marketing has specific information to communicate with the customers that have truly been impacted—to give them better information on when and how the problem will be fixed as well as dispel any myths perpetrated on social media.

C-level/executive: “I met with a group of industry analysts this morning, and they say we’re not focusing enough on ‘X’ new technology. What are we doing to build this into the current release?”

Most of you either participate in meetings between industry analysts and your executives, or are briefed by executives after the fact. Often, there is extremely valuable information conveyed, which illuminates and educates product roadmap decisions. But sometimes you may feel like Dilbert when his boss tells him, “I think we should build a blockchain.” Silently questioning that the boss even knows what that is, Dilbert asks, “What color do you want that blockchain?” to which the boss replies, “I think mauve has the most RAM.”

While you should always be mindful of incorporating new technologies into your roadmaps, data helps us answer the question of applicability and whether your customer base wants, or needs, the technology. Data helps you better answer these questions. With detailed information on machine architecture and use that you can slice by feature adoption, customer properties, geography, industry and more, you will know whether your customers want it, or are even ready for it.

What’s more, when you pair usage analytics with in-application messaging, you can not only pull information from your users, but also push questions to them based on specific characteristics. Robust filtering and segmentation allows you to drill down by geographical region, days installed, license type, OS details and much more to get real, actionable information from users that indicate they may be ready for it.

The ability to leverage data truly helps you hear the HiPPOs and allows you to say “yes” when their opinions add value to the product and confidently convey the reasons why when they do not. Data helps you better communicate and evangelize your final decisions among key stakeholders in the product development process—especially when it comes to addressing opinion. This ensures that everyone understands production direction and is invested in its success, while inspiring confidence in the decisions and processes for making them.

Author
  • Keith Fenech

    Keith Fenech is vice president of software analytics at Revulytics and was the co-founder and CEO of Trackerbird Software Analytics before the company was acquired by Revulytics in 2016. 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.

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