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Customers as Advisors: How Customer Feedback Shapes Product Development

Written by GoodData Author  | 

Customers as Advisors: How Customer Feedback Shapes Product Development

Editor’s Note: After our Customer Advisory Board, our VP of Product, Gaurav Agarwal and our Director of Product Marketing, Cory Vander Jagt, sat down to debrief on the key insights we shared and gained from our customers.

Gaurav: I recently had the great privilege of spending two days with a wonderful group of customers for our second Customer Advisory Board meeting. In beautiful Portland, OR, I was able to meet and discuss GoodData’s direction, product roadmap, and recent feature releases with customers like CSC, Walgreens, and ServiceChannel in a casual yet productive setting. It was great to truly understand their pain points and gain deeper insights into their day-to-day challenges with analytics, its adoption and engagement. Of course, it’s always exciting to see how customers are using your product, their passion for it, and how they add value to their organizations with data.

In the spirit of that discussion, I sat down with our Director of Product Marketing, Cory Vander Jagt, to swap our favorite insights from the two days of intensive customer feedback. My first thought: How amazing was it to hang out with such a fun group of customers?

Cory: It was great to gather everyone in one city, so we could truly build face-to-face relationships. It’s also FAR easier to discuss the company and product direction in a collaborative setting with our customers. I was most excited to learn how they are building their analytics teams, which have key similarities across industries.

What was your favorite insight?

I was pleasantly surprised to see that a several of our product initiatives were already aligned with customer needs, even before we presented them to CAB members. I was really surprised to see so many customers interested in predictive and prescriptive analytics! We hear those terms as buzzwords so often, but it’s nice to see that large enterprises actually understand and want to implement them.

So true. Even if organization-wide understanding of those terms varies, it’s nice to see the recognition that analytics depth and maturity matters, and to see our customers actively trying to move up the analytics maturity curve. We spent a lot of time discussing the steps most customers still needed to take to reach org-wide analytics maturity.

Yes, and we learned a lot about the challenges companies face when trying to become fully data-driven. For most of the customers we talked to, the barriers to analytics maturity fell into three main categories:

1. A Culture of Data

Many organizations (even large and Fortune-500 organizations) are still having trouble switching from intuition to data-driven insight as the driving force behind their organization. The idea that a dashboard or data visualization will show you how you should run your company is still a relatively new concept, and it can be a tough sell to senior staffers, as well as the C-suite.

Especially the C-suite. Data-driven decisions really ARE more efficient, as shown by…more data.

2. Goals, Goals, Goals...but No Execution Strategy

Even though the C-suite may have a tough time switching their overall decision-making mindset, there is also what Gartner calls “strong interest” in analytics adoption. Even if a CEO is highly motivated to get data-driven, they might not have the internal resources to implement org-wide analytics. Additionally, many analytics users need to make fast and accurate decisions, but may not have the skills required of a traditional BI tool to gain insights from their data. Our customers need the training and tools to drive BI adoption from top to bottom.

I’d agree with that point, and add that luckily, we’ve found that our award-winning Services and Support teams have been helping our customers along this often rocky road. We knew they were great, but it’s wonderful to see that customers value those teams as partners, or as several said, extensions of their own team.

3. Big Data Ambitions, Small BI Vocabulary

Many of the customers we talked to also admitted a lack of organizational knowledge about analytics in general. Although analysts and data scientists know the true meaning of terms like “Big Data” and “data cleansing,” an everyday business user will have trouble if forced to adopt that nomenclature. That’s why it’s so important to set out on an analytics implementation with business goals and proven best practices in mind, and to train your users in simple, easy-to-understand language.

In a world where it’s more important than ever to allow more users in the organization to access, analyze and share data and insights, it’s important to map every action to a business goal.

But what if our customers don’t know how to set that up?

Luckily, we have thousands of projects worth of experience getting our customers to insights.... We have our own community for customers called GoodFriends, and our award-winning support team is ready with best practices any time.

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Image used with permission from Death to the Stock Photo.

Written by GoodData Author  | 

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