Take the Guesswork Out of Product Management Building Better Applications with Software Analytics, Part 1 As a product management professional, you have ambitious plans for making your software application successful for your customers and for your business. But turning those plans into reality is easier said than done, especially when you lack critical insight into product runtime and customer usage patterns.
Your strategic product decisions have far-reaching effects that ripple throughout the customer journey. These decisions should be based on fact — not just anecdotal evidence or gut feelings. However, if you’re like most product managers, you might not have the tools required to make informed decisions based on how customers are actually using your product. Given that 45% of product managers spend the majority of their day deciding what should go into products1, this lack of insight could be standing in the way of successfully meeting customer needs.
Product managers spend the majority of their day deciding what should go into products. The lack of insight could be standing in the way of successfully meeting customer needs.
1. Pragmatic Marketing, 2014 State of Product Management and Marketing Survey, at 7.
2 Building Better Applications with Software Analytics, Part 1 Drowning in Data but Still Lacking Insight?
Chances are you’re spending long hours collecting data from multiple, disparate sources and trying to sift through and organize this data to learn about customers and how they interact with your product. You might be relying on some combination of:
• Download logs and call-home statistics • Feedback from the sales channel and customer support staff • Data from customer relationship management (CRM) systems and marketing automation frameworks • Web analytics reports • Ad-hoc surveys with customers or prospects
But trying to make sense of all this data is painful, time-consuming, and too often, inconclusive — forcing you to base product decisions on guesswork rather than fact-based analysis. It’s no wonder 28% of product teams are kept up at night worrying that delivered features aren’t being used by customers2.
According to a Pragmatic Marketing survey, product teams are kept up at night worrying that delivered features aren’t being used by customers.
2. Pragmatic Marketing, 2014 State of Product Management and Marketing Survey, at 5.
Building Better Applications with Software Analytics, Part 1 3 Gain Actionable Intelligence with Software Analytics
When you’re trying to keep up with pressing customer demands and rapidly changing markets, it’s risky to rely on anecdotal evidence, disjointed data, or non-actionable vanity metrics like download statistics for making key product decisions. Software usage analytics provide valuable business intelligence that helps guide your decisions and focus your efforts where they’ll have the most impact.
Software analytics and runtime intelligence tools help you build better applications by providing comprehensive, targeted reports that show where, when, and how your applications are being used by trial users and paying customers around the globe. Armed with these actionable insights, you can Software usage analytics help make data-driven decisions about your product roadmap, allocate engineering answer critical questions such as: resources more effectively, and develop more informed sales and marketing strategies that drive competitive advantage and increased revenue. • How often do users engage with your application?
With software analytics, you get the benefits of a continuous, automated • Which features are your customers using and not using? feedback loop, which helps you stay on the right track and avoid wasting • For how long and in what way are prospects evaluating time, money and resources on building, marketing, and supporting your product? features that aren’t widely used and valued by customers. These tools also enable you to identify usage patterns and trends, so you know which user • Are there underlying usage trends or behavior patterns related to user churn? experience (UX) or user interface (UI) design improvements are most likely to increase conversion and adoption rates. • When does it make sense to pull the plug on a legacy version?
• How would dropping an old feature affect your customer base?
• What software versions, OS platforms, and hardware architectures are customers using?
• What’s the optimal pricing structure for your product?
4 Building Better Applications with Software Analytics, Part 1 Select the Right Software Analytics Tool for the Job
We live in a big data world, but not all software analytics tools are created equal. Once you’ve identified the core actionable metrics you want to track, you need a solution that enables you to collect and visualize your product data clearly and seamlessly to guide smart decision making.
When evaluating software analytics tools to support data-driven product engagement decisions, look for a solution that:
• Collects meaningful data that deliver actionable metrics such as those • Provides out-of-the-box reporting to help you quickly understand related to user engagement, feature usage, and purchases versus and answer both basic and complex questions for rapid return on simplistic drop-off or uninstall numbers investment (ROI)
• Goes beyond data collection and delivers real insights in a highly • Allows you to easily customize dashboards and reports to meet graphical format that’s easy to access and digest your company-specific requirements
• Converts raw data into actionable business intelligence reports with • Integrates seamlessly with third-party business intelligence drill-down and segmentation capabilities and CRM tools
• Displays real-time visualizations that present high-level information • Adapts and scales to meet your evolving business requirements with the ability to drill down interactively when you need to learn more
Building Better Applications with Software Analytics, Part 1 5 REAL-WORLD RESULTS: Software Analytics in Action
Here are some examples of how product managers have used software analytics to solve specific business problems and make data-driven product decisions that yielded measurable results.
How do I know when it’s okay to drop support for an old software version?
A developer productivity software firm wanted to figure out if it made good business sense to stop supporting a legacy version of its flagship product. Although significant engineering resources were required to support the old version, the sales team was concerned that its discontinuation might adversely affect a substantial number of customers.
Using software usage analytics, the product management team was able to see which customers — and how many users — were still running the legacy version and how actively they were engaging with it. It turned out only a small group of users were impacted, so the company decided to offer them an attractive discount to upgrade to the current version. The highly targeted upgrade offer was well received, enabling the firm to drop support for the old version and reallocate quality assurance and customer support resources — without causing disgruntled customers. Using software usage analytics, the product management team was able to see which customers — and how many users — were still running the legacy version and how actively they were engaging with it.
6 Building Better Applications with Software Analytics, Part 1 REAL-WORLD RESULTS: Software Analytics in Action
Should I dump an old feature that’s complicating UI changes?
An old application feature written in legacy code was creating big problems for the engineering team at a practice management software company.
5.5 Whenever the engineers made a change to the UI, the feature would 4.5
3.5
2.5 inevitably break — eating up additional time and resources. Despite this
1.5 0 extra cost and effort, the engineering team was reluctant to drop the feature altogether for fear of alienating existing customers.
To determine the best resolution, product management used event tracking to identify the unique number of users who actively engaged with the feature on a frequent basis. Reports revealed only a small number of active users, suggesting that elimination of the feature would not have major revenue impact. As a result of these findings, the company decided to develop a new feature that would better meet customers’ actual usage requirements while operating seamlessly with newer versions of the software.
By using event tracking to identify the unique number of users who actively engage with a feature written in legacy code, reports revealed only a small number of active users, suggesting that elimination of the feature would not have major impact on existing customers.
Building Better Applications with Software Analytics, Part 1 7 REAL-WORLD RESULTS: Software Analytics in Action
Why aren’t trial users taking advantage of our ‘killer’ feature?
Internal beliefs about a feature and its user benefits don’t always match the real customer experience. That’s why an accounting software company used software analytics to track all its major product features and how they were being used by customers. Event tracking uncovered interesting trends, including the fact that the “killer” rolling budgets feature — developed at a significant cost to the company — was not being used by customers until a month or more after product purchase.
To figure out the best way to promote the usage of this feature during evaluations, the engineering team ran an A/B test by deploying two separate builds of the software — each of which provided a different visible method to access and use this rolling budgets capability. Product management tracked and studied which version led more people to use the feature and adopted that method within the UI of the next product release. As a result, adoption of the rolling budgets feature increased dramatically among trial users, The engineering team ran an A/B test by deploying two leading to a higher conversion rate. separate builds of the software — each of which provided a different visible method to access and use the rolling budgets capability.
8 Building Better Applications with Software Analytics, Part 1 REAL-WORLD RESULTS: Software Analytics in Action
What impact will increasing minimum display resolution requirements have on my customers?
When developing a new user interface for its photo editing application, a graphics software company was trying to decide whether to increase its 1920 minimum resolution requirements from 1024px to1920px. The UI team believed the increase was critical to provide a better-looking UI that would drive competitive advantage, but the engineers were concerned that there were too many existing customers whose hardware did not meet this minimum requirement, which would lead to dissatisfaction, or even worse, churn.
1024 The product management team decided to settle the debate by backing up gut feelings with actual facts. They used their software analytics tool to run hardware architecture reports and determined that only a handful of customers were still using resolutions below 1920px. Based on this Using hardware architecture reports, the product management intelligence, the company made the strategic decision to increase its team made the strategic decision to increase its minimum minimum display resolution requirements, thereby providing a better user display resolution requirements, thereby providing a better experience for 95% of its customer base. user experience for 95% of its customer base.
Building Better Applications with Software Analytics, Part 1 9 REAL-WORLD RESULTS: Software Analytics in Action
Why aren’t more of my trial users converting to paying customers?
A PDF software company was baffled by how few trial users were converting into paying customers — especially given all the innovative new features included in its latest product version. Seeking data-driven answers, product management ran a detailed conversion analysis study using its software analytics tool to better understand user behavior in the critical days after trial download.
The report revealed key usage patterns, showing that many trial users were getting stuck in the configuration wizard and dumping the product within just one hour of installing it. After making changes to improve usability of the configuration wizard, the company significantly increased its conversion rate as users spent more time engaging with the software and discovering its capabilities during the trial period.
Analytics showed that more than1,000 users were lost within the first 5 minutes of use. By improving the usability of the configuration wizard, the company significantly increased its trial conversion rate.
10 Building Better Applications with Software Analytics, Part 1 REAL-WORLD RESULTS: Software Analytics in Action
How do I find out what existing customers think about our new product feature?
5.5 4.5 An HR software company added a performance review workflow to its latest 3.5
2.5 1.5 product release and tracking showed that customers were actively using this 0 new feature. Given the initial success of the workflow, product management decided to invest more into this feature in the next release. But in order to prioritize what to do next, they wanted to augment the quantitative usage data with qualitative feedback from their customers.
The product management team used in-application messaging to solicit feedback directly from those customers who had accessed the new workflow feature ten or more times a month since upgrading to the latest software version. Using the company’s existing survey framework, they delivered surveys to end–users in the form of an automated HTML pop-up window directly within the HR application. Because the survey instantly appeared when end-users logged into the application, the company achieved a high response rate and collected valuable feedback for improving the workflow feature in subsequent product releases. The product management team used in-application messaging to solicit feedback directly from those customers who had accessed a new feature ten or more times a month since upgrading to the latest version. The survey instantly appeared when end-users logged into the application, and the company achieved a high response rate and collected valuable feedback for improving the feature in subsequent releases.
Building Better Applications with Software Analytics, Part 1 11 About Take the Guesswork Out of Product Management
We hope that you’ve found Part 1 of our Building Better Applications with Software Analytics series valuable. Take the Guesswork Out of Product Management provides an introduction to software usage analytics and shows how Product Managers (or anyone tasked with meeting customer needs and delivering revenue-generating products) have used this insight into customer usage behavior to make strategic and tactical product decisions.
We now invite you to read Take a Customer-Centric Approach to Product Management, Part 2 of our Building Better Applications with Software Analytics series. This ebook provides actionable insight into how you can bring Give Software Usage Analytics a Try Today software usage analytics and a razor-sharp focus on customer needs into — Risk Free! your software development process. Are you ready to take the guesswork out of You can find the ebook here: www.revulytics.com/Take-a-Customer- product management decision making? Centric-Approach-to-Product-Management-e-book
Visit https://www.revulytics.com/register to register for a free account and download the Usage Intelligence SDK with no commitment.
In as little as 30 minutes, you’ll be able to start tracking installations, user activity, feature usage metrics and conversion/ churn trends; sending in-app messages; and collecting user feedback to support data-driven product decisions.
12 Building Better Applications with Software Analytics, Part 1 Revulytics Usage Intelligence: Better Software Begins with Better Data
Revulytics Usage Intelligence provides valuable insight into product runtime and customer usage patterns to help you make data-driven decisions that drive user engagement and accelerate adoption. This powerful solution helps you understand user activity and conversions after your product is downloaded by gathering intelligence on what platforms and architectures the software is running, which product features are used or ignored, and how usage and churn trends vary by user segment.
Usage Intelligence does more than just collect data and map raw statistics onto colorful graphs. Our advanced analytics engine provides valuable business intelligence via real-time interactive visualizations — with the ability to drill-down into reports that answer specific product questions. With actionable insights at your fingertips, you’re empowered to shape your product strategy, roadmaps, packaging, and pricing models based on real- world facts about your software. Usage Intelligence integrates into your application development process quickly and easily for rapid ROI.
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