Deploying Business-User Friendly Analytics

March 19, 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.

This is part one of a 10-part series focusing on key challenges for deploying analytics and recommendations for addressing those deployment challenges.

Since our recent webinar with Aberdeen, I’ve been thinking a lot about the values and priorities that the respondents referenced. The majority of respondents cited their top purchase criteria are ease of use and relevance for non-technical users. In addition, a key driver of the need for analytics was competitive pressure that respondents faced from their peers. Clearly, they were feeling some sense of urgency and understood the importance of deploying embedded analytics.

However, it’s not enough to implement analytics; you need to be producing analytics that can be understood and actioned by everyone in your organization, regardless of technical skill. If business users aren’t supplied with analytics that are actionable, contextual, and easy to understand, adoption rates are likely to be low as users struggle to find value from the analytics. With that in mind, what steps can you take to ensure that you’re deploying analytics that are business-user friendly?

Personalize analytics for every user regardless of their role

Don’t fall into the trap of creating a “one size fits all” analytic application. Of course, some of their needs or pain points may overlap, but each department, function, and role has their own unique challenges.

A sales and marketing department is a great example. Within this organization, you may have someone in charge of lead generation, someone who goes out to sell to customers, someone who focuses on marketing campaigns, and someone overseeing public relations. While they’re all under the same general umbrella of marketing, each of these people would have vastly different needs from their analytics. Companies who chose to treat all of these users the same would soon find that they’ve provided analytics that are useful to no one.

To avoid this pitfall, take the time to really dig into each of your personas. Who are they? What are their pain points? What questions are they trying to answer? What decisions do they need to make on a regular basis? By doing this work up front, you can ensure that each individual user or persona receives insights and recommendations that are tailored to their needs and delivered in a way that’s easy to understand. The only thing left for the user to do should be to quickly review the recommendation and take action.

Ensure insights are intuitive to use

For analytics to be truly business-user friendly, intuitive insights will need to be easy for a non-technical person to understand and use. Ideally, analytics would be so seamlessly integrated into the workflow process that users don’t even realize that they’re using “analytics.” Not only does this eliminate the need for extensive user training, but it also helps improve adoption rates. Business users wind up using analytics and improving their decision making, which makes them more likely to continue using the recommendations they receive.

If you’re looking to partner with a vendor for your analytic application, start by looking for one that specializes in embedding analytics into business processes or customer-facing applications. If you’re looking to build an analytic application yourself, make sure you do your homework first. Building an application this robust is a serious undertaking and will require you to think carefully about how you design, build, and launch the application.

Deliver analytics to 100% of your workforce or customers

Finally, business-user friendly analytics need to be accessible to business users, not just data scientists or the C-suite. Forrester found that extending the use of analytics to the rest of the company could yield 30% annual company growth rate and an estimated $1.8 trillion in earnings by 2021. This makes perfect sense to me. If analytics have value for one CEO who uses it for strategic decision-making, then how much value would analytics have for front-line employees who rely on analytics to improve operational decision-making every day?

In the deployment planning process, make sure that you’re not limiting the use of analytics to just a few select users. By making the use of analytics more pervasive across your organization, you’re ensuring that those business users are getting access to the insights and recommendations they need to be successful.

By deploying analytics correctly and in a way that’s friendly to business users, you can ensure that your users get the most value out of it and that you get the return on your investment that you’re expecting. Give it a try and download a free trial of GoodData today. If you’re already a GoodData customer, we’d love your feedback on your experience so far.

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