SAAS

Why the difference between design and Design may make or break your data product.

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Commuters in a Terminal

Good Design–what I sometimes call—”Capital D Design”—has the power to make your data sing, delight customers/users, bring new/better ROI to your organization, provide inspiration to teams, reduce complexity, reduce engineering cost, save time for users, and expose new value in your existing service. However, the big gains usually don’t come from focusing on the surface level alone. Better data visualization cannot fix every data product and analytics problem.

Design KPIs – what improvement did you celebrate in your last analytics software release?

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I know to a lot of software teams, getting features/fixes/releases out the door feels like improvement. However, did you actually create or improve the value of your service? To to that, you have to understand what your users actually value, so you can align your efforts accordingly. Most of the time, these nuggets of useful … Read more

How to solicit *real* needs from users via UX research interviews

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Readers of DFA know that I’m big on not immediately giving customers what they asked for, and instead asking the question “why” to learn what the real latent customer needs are. And for you internal analytics folks, remember your employees, vendors, etc. are your “customers” whether you think of them that way or not! Anyhow, … Read more

The Easiest Way to Simplify Your Product or Solution’s Design

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Ok, you probably know this one, but let’s dig in a little farther. I recently started to explore using the TORBrowser when surfing on public wi-fi for more security (later finding out that using a VPN, and not TOR, is what will enable safer surfing). However, in the process of downloading and trying the TORBrowser … Read more

What internal analytics practitioners can learn from analytics “products” (like SAAS)

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When I work on products that primarily exist to display analytics information, I find most of them fall into roughly four different levels of design maturity: The best analytics-driven products give actionable recommendations or predictions written in prose telling a user what to do based on data.  They are careful about the quantity and design of the … Read more

Tips to help focus your analytics design/engineering efforts on results

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If you are starting out on a new feature design, or analytics effort, can you clearly state what the value will be in quantifiable terms at the end of the sprint? Are you building an “exploratory” UI, or one that is supposed to drive home conclusions for the customer? When clients come to me about … Read more

“Post-truth,” data analytics, and omissions–are these design considerations?

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Post-truth. The 2016 word of the year. Yikes for some of us. This got me thinking about UX around data, analytics, and information, and what it means when we present conclusions or advice based on quantitative data. Are those “facts”? If your product generates actionable information for customers, then during your design phase, your team … Read more

Think it’s hard building an analytics product or service? Try cutting features out.

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Try cutting features out of it. Apparently, that whole quote from Michaelangelo about “I just carve away the part of the statue that doesn’t look like David” is a myth. But, it’s a good myth for design thinkers. It helps me remember that you can add customer value by removing materials from a design. We talk a … Read more

A Venture Capitalist’s Take on Designing Useful Big Data Products

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I loved this quote: ”Identify 2-3 need-to-know insights, and make that the focus of the product. Rather than thinking about competing products, think about competing processes. The goal of the product is to be consistently used by all users, not just power users, and the only way to accomplish this is to make it as simple as possible to discover the … Read more