How Usage Analytics Support Agile Development
As we enter the spring trade show season, the mantra “go big or go home,” characterizes the directive for product managers preparing for events. Whether it’s helping executives make big splashes with product announcements, facilitating live demos that leave big impressions, or simply mastering the newest jargon so we can tally its usage for our amusement during executive keynotes, this mantra extends across our space.
But chances are, as you’re walking show floors over these next few months, meeting with customers one on one, or talking with users in educational sessions, you’re more concerned with finding the small things—the details and feedback you can leverage to make tweaks here and there to drive irresistible product releases.
This is the time of year when I think the value of agile development is really on display. With its focus on delivering working software in iterations, agile accelerates product delivery to give executives cool stuff to talk about, or even demo, at big events. And by those same means, it lends developers and teams the ability to more easily fix or change things according to customer feedback.
But it doesn’t always work. Cultural roadblocks are often the chief culprits, as organizations may find it difficult to adopt the flexibility that agile demands. However, as you seek to further evangelize and gain greater success with agile development in your organization, elevating the importance of something concrete can help: usage data.
Developers and teams surveyed by VersionOne in its State of Agile report indicated that their organizations adopted agile methodology in search of three benefits: to accelerate product delivery, enhance their ability to meet changing priorities and enhance their teams’ productivity. Let’s take a look at how software usage analytics can help achieve these agile goals.
Accelerate Product Delivery
In agile development, work takes place in cycles and is tested in two- to four-week periods to create a product increment. The goal is to develop shippable product increments, according to Agile Velocity, a leading agile advisory firm based in Austin, Texas.
Software usage analytics help speed these development cycles. Product managers can measure effectiveness and adoption in a live install base, gaining feedback across an enormous number of parameters in real time. Having the ability to segment data by operating system, machine architecture, platform type, language, geography, etc. and collecting usage data in real-time from the latest release, empowers managers to make fast, data-driven decisions on where to focus the next agile development cycle.
This allows the team to quickly prioritize and facilitate everything from small changes, like moving a button or changing a color scheme, to enabling bigger changes in workflow or function.
Manage Changing Priorities
One of the chief reasons organizations adopt agile development methodologies is to better accommodate changing priorities—whether those changing priorities are driven by customer demands, sales requests, marketing needs or other stakeholders and influencers.
Having usage data helps validate requests coming in through various sources, and enables you to make a strong case for or against including a change, improvement or even legacy functionality in a development cycle. Consider how often you field requests to support a legacy feature that is incompatible with an upcoming release. Being able to quickly identify which customers are leveraging that functionality and how, allows companies to make insight-driven decisions about moving forward. Getting a complete picture of use lets you determine whether it makes sense to funnel development resources toward porting the feature onto the new platform, or whether functionality in the new release will suffice, while gaining knowledge to create data-driven offers that encourage customers to upgrade.
By automating feedback collection, usage analytics can facilitate the productivity increases borne of agile development in two ways.
First, with a combination of usage analytics and in-app messaging, you can test your assumptions in real-time within hours of actually deploying new functionality. Usage analytics allow you to pinpoint where in the workflow you need more user feedback and reach the user within the context of that workflow using in-app messaging, soliciting targeted and relevant feedback. This saves time and resources of an already taxed team.
Second, ensure that the user feedback is valid. Often, in personal customer outreach, those who are willing to provide feedback tend to sit at two ends of the spectrum: they are either very happy, or very unhappy, with your products. In turn, there is a tendency to report only on what worked well or failed, painting an incomplete picture to inform further development. By leveraging usage analytics, you can pull the experiences of a broader customer community and get unbiased feedback along the spectrum of product use.
Data-Driven Agile Processes
Agile Velocity frames the product development dichotomy well. Often the assumption is that customers already know what they want, developers know how to build it and nothing will change along the way. In reality, customers often discover what they want, developers discover how to build it and many things change along the way.
Software usage analytics accelerate and help you evangelize agile development, maximizing your ability to manage competing interests and all the pressures associated with product cycles to deliver products that resonate with customers and features they can’t resist.
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