Using Better Data to Create Better Experiences

Data Visualization Graphic

Data and research are foundational components of what we do for our clients.

Our challenge is not creating a large volume of data to address a question, but rather finding and interpreting the right data.

When determining the right questions to ask, we naturally encounter research / data gaps which require a thoughtful approach to overcome.

Creating better customer experiences starts with using better data.

Better data starts with identifying potential data gaps.

Incorrect Questions

Every client comes to us with a question, problem or challenge, but the ideal client invites our firm discuss and explore the question with them — rather than simply recommend a self-diagnosed solution.

Good research is created in response to good questions.

Start with a basic test of your question, problem or challenge by asking:

How do we know that is the problem?

Once we have identified the right problem, we can find the right answers.

Too Much Data

Quantitative research is a helpful component to establish the size and scale of a project, but too often is set as a statistical bar to clear by incorrectly correlating the number of responses with the accuracy and viability of the solution.

If we ask more people to fill out a survey, then we can’t be wrong!

Background statistics can be useful, but they are not very actionable when trying to uncover the underlying issues.

In these cases, we like to move away from quantitative (or market) research and focus on insights research. Asking more questions to a smaller audience to discover and elaborate upon deeper insights.

As few as 5 participants will be able to identify 85% of usability and experience issues.

Market Research v. Insights Research

Deeper insights reveal a greater understanding of customer motivations in addressing the problem.

Irrelevant Data

Or data as defense. A poor decision, covered up by general data trends with no true relevance to the primary question.

Unfortunately a lot of irrelevant data exists — often passed off as a poor attempt at content marketing — which is confusing for organizations who recognize a need for good data.

General trends are certainly helpful in the early stages of a project, but should be utilized as a component rather than definitive justification.

Incorrect Methods

Data collected utilizing closed questions, poor sequencing or incorrect audiences is bad data.

The solution is rather simple. Ask more and better questions, while thinking critically about the answers.

A recent post by Matt Edgar offers 5 tips to avoid shockingly poor surveys:

  1. If asking a closed choice question, always offer an optional explanation field.
  2. Individual responses are a good thing — assume you will receive some and prepare accordingly.
  3. Gather customer feedback throughout the user journey with short, frequent and relevant questions.
  4. Be prepared to invite respondents back for another survey / interview at a later date.
  5. Keep an open mind to help you ask open questions.

(Paraphrased, emphasized and edited from Matt’s original list.)

Conventional Data

The goal of creating better experiences means reconsidering conventional data sources. Research repetition and depth does not take into account the possibility of poor methods and perhaps better data sources.

Mobile adoption provides potential for pioneering customer research opportunities as well as new sources of data.

AirSage LA Marathon Data Example

One of the most promising of these new mobile data sources comes from AirSage (client).

The map above highlights the recent AirSage analysis of hot spots or high activity levels — indicating large crowds — around the LA Marathon.

By utilizing anonymous mobile activity data, a new opportunity becomes available to measure customer behavior through real-world actions, rather than post-event or intercept surveys. Data which was previously unavailable or challenging to uncover, can now supplement insights research.

The goal is not omitting conventional data, but rather looking for and embracing new data sources.

Data Usage

Looking beyond the original intention of the data is a critical component of using better data.

For example, the AirSage data from the LA Marathon is helpful for a tourism organization or government agency to determine who visited the event, where they visited from and what the visitation patterns looked like (where did the customer go before and after the race passed by their location?).

But the data also holds additional insights as we thoughtfully and strategically zoom in and out of our original question.

Could these insights help the client improve the experience for future races? Information booth locations, parking recommendations, viewing area locations, etc.

Both from a macro and micro perspective, data not only reveals answers to the primary question, but also opportunities for additional questions and answers to improve related aspects of the service.

Overcoming data gaps helps create more reliable and useful data, which in-turn helps organizations better understand their customers while improving the overall experience.

Comment? @travel2dot0 or email.