Top Purchase Criteria for Analytic Applications

January 31, 2019
Kevin Smith's picture
VP, Product Marketing
Kevin Smith is Vice President of Product Marketing for GoodData. Prior to GoodData, Kevin was responsible for delivering consulting services such as analytic product strategy, data monetization, and go-to-market services at NextWave Business Intelligence. He is the author of numerous ebooks, articles, and webinars on embedded analytics and building data products. In addition to NextWave, Kevin has held leadership positions heading analytics teams, designing SaaS products, and performance and managing product teams for both small start-ups and Fortune 500 companies such as SAP, ServiceSource, and Qwest Communications. Kevin holds a B.S. in Finance, as well as an M.B.A. in Quality/Process Management, both from the University of Maryland, College Park.

Understanding the factors that matter to businesses buying analytics can give us a better understanding of where the industry should be headed, and it’s what drove research group Aberdeen to conduct a recent survey on embedded analytics. Aberdeen joined us for a webinar to discuss the results of their survey, which asked companies about their analytics strategies and what matters most to them when it comes to analytics. One survey question, in particular, caught my eye: Which factors have the biggest influence when a company is deciding whether or not to purchase an analytic application?

With the array of options for analytics vendors today, how are companies deciding which vendor to partner with? What’s most important in the evaluation process? You’d probably expect to see something like cost or ease of integration into the company’s infrastructure be the top factor. While those are certainly important considerations that showed up in the top five responses for the 259 companies surveyed, there was a clear surprise winner: ease of use and relevance for non-technical users.

The importance of analytics for non-technical users

I was delighted to see that the top purchase criterion related to the users rather than the infrastructure. At GoodData, we’ve been talking about the importance of a seamless user experience for a while. We want to make analytics embedded within the users’ workflow and so easy to use that the average non-technical user doesn’t even realize they’re using analytics. We’ve been focused on bringing analytics out of the exclusive domain of the expert and helping the front-line of business users make effective, faster decisions. Based on the results of the Aberdeen survey, it seems that buyers are starting to realize how crucial this is as well. They’re acknowledging that they need to create an analytically enabled workforce, and they’re looking for ways to make the process of using analytics intuitive. But what led to this shift?

Realizing the value of bridging “the last mile”

To follow up, Aberdeen asked survey respondents about what was pushing them to explore the world of advanced analytics. Unsurprisingly, nearly half cited competitive pressure from other companies who were successfully using analytics, with workforce demand as a close second. With these kinds of numbers, it’s no wonder that relevance and ease of use for non-technical users took the top slot in purchase criteria.

These businesses have likely seen the recent flood of research showing the importance of making analytics easy to use and bridging the gap that exists between analytics and the users who need to interact with them. (That gap is usually referred to as “the last mile”—and that alone should tell you where users had historically been on the priority scale!) In particular, a recent McKinsey report showed that 90% of organizations that are significantly outperforming their peers are devoting more than half of their analytics budgets to bridging the last mile. Clearly, these organizations have uncovered the “secret sauce” that had been there all along. Investing in users, giving them access to analytics, and making it easy for them to take action based on those insights, has serious business benefits.

What do these numbers tell us? For starters, it shows how critical user experience has become. These results are also a great example of the mindset shift that coincides with the third wave of analytics.

Focusing on users in the third wave of analytics

I’ve talked before about the third wave of analytics, which refers to analytics that support non-technical users while still being deeply integrated into the company’s architecture. These results from Aberdeen are a perfect example of this. No longer just for the C-suite or power users, analytics are finally being recognized for the value they hold for non-technical business users. With companies like the ones surveyed by Aberdeen understanding the importance of making analytics easy to use, those users are that much closer to being empowered with insights gained directly from the application. Decisions that save the company money, that bring in new business, that improve customer experience. Talk about a win-win for everyone involved!

Personally, I’ve gone through many steps of the build process before, and in my experience, it was always a struggle to convince decision-makers  to get the users involved. It looks like what we're seeing today is that the users are at that very first meeting and that their needs are being considered from the start. It’s become perhaps a bit less of a question of whether an application fits into a company’s architecture and more of a question of whether or not the application will be useful and relevant for non-technical end users—a promising shift.