Getting the Full Benefit out of Your Customer Research Data

May 8, 2018
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Customer experience has become an intrinsic element of every product and service. Data gathered from user research can inform the design process and provide insight to help teams evaluate the quality of the customer experience once the product goes live.

In parallel, the formalization of roles associated with data science and the advances in technology that enable advanced analytics to have created opportunities for data driven product design strategies. What I wanted to talk about in today’s discussion is the alignment of these two efforts, user research and analytics, and look at these from a systemic point of view that spans the product life-cycle. I thought we could also talk about a few insights gathered from implementation experiences that show practical ways to manage customer data so that you get the most out of the data you collect and retain.

What are some of the guiding principles when gathering customer data?

Throughout this discussion there are two points that I keep returning to. The first is that you need to define what decisions you are trying to make before you begin your research efforts; in other words, plan for how the data collected will help you to obtain the information you need to feel confident in your decisions. The second point is a practical point which is to make sure you know how the data you gather will be stored and how you will be able to retrieve that data and relate that data to other research data in the future.  For example, consider an e-commerce site. You may have customer data gathered during initial product design efforts and then once you go live with the site, web analytic data will be captured that provides insight into customer behavior on the website.

What are some of the other benefits of aligning user research and data analytics?

This is important both for opportunity as well as cost reasons. In terms of cost, some customer research efforts can require staff time as well as setup and operational costs. For example, if you are conducting field studies, there will be cost associated with travel and equipment as well as time spent by staff or consultants conducting the study.

It’s not only important to obtain results from these expenditures but you would also want to avoid having to repeat research efforts unnecessarily. From an opportunity point of view, organizing and storing information strategically enables subsequent use of data after the initial research effort was undertaken. You may want to calibrate the design decision making process later on in the product stage by comparing initial research results with actual product performance once it is released into the marketplace.

What is a good place to start to build you repository of customer data?

There are many strategies for collecting data about your customers. The methodology chosen is often influenced by the stage you are with the product or service. And quite frequently now, the capabilities of the technology used to develop and maintain the digital products.

To illustrate this, I’ll describe an example product development timeline and the associated user research efforts that typically take place along these well-known product milestones.

Living Comfortably with Data

April 11, 2018
00:0000:00

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Our host, Lee Silverman welcomes Mark Tietbohl. He is a growth strategies advisor and change catalyst at Growth Strategy Advisors. Topics today are about getting comfortable with data.

There is a great deal of data eveywhere today. So much so, that most organizations wanting to start the data driven decision process can easily become overwhelmed. There are numerous studies that show that companies that drive decision with data experience greater growth than those that do not.

But the key to doing this well for the long haul is to start with a "less is more" approach. Getting comfortable with data requires that you choose initially what matters to you rather than drinking from the firehose.

Some of the questions they'll cover include:

  1. What are the dangers of collecting too much data too soon?
  2. Data and technology makes it easier to change direction for marketing today. Is this a good thing?
  3. Are there downsides of data driven approach?
  4. If you are not a currently a data driven decision making organization, how do you get started?

In addition to serving as an adjunct instructor for Web Analytics/SEO and Mobile Marketing in the IMC program, Mark Tietbohl is currently engaged in providing marketing and business development strategy support to technology industry clients.