“What Brings You in Today?”

Is this the missing link?

One of the challenges facing operators in a post-COVID-19 world is that consumers may not go back to pre-pandemic norms. Increasing numbers of people will continue to work out from home, and many users will choose online rather than in-person services. Not only this, the cost-of-living crisis is having a significant impact on the financial priorities of the general public.

As operators have begun to navigate the post-COVID-19 world, the use of data analytics tools is extremely valuable in helping them adapt to the changed attitudes of the customer, and ways in which people want to be active. Operators are being presented with the challenge of getting to know a very changed market; it is essential that the changed attitudes and habits of the customer are recognised and understood as thoroughly as possible. Because of this, data analytics tools are more valuable than ever before.

Both Big Data and Thick Data should be used for detecting new purchasing patterns and the behaviour of the customer, which in turn can assist in delivering a greater personalized experience.

What is Big Data?

Big Data is quantitative in nature; it is the numbers and figures that are scrutinised and analysed at the end of the day, week, month, and year to see what has been achieved or not achieved. This comes in the form of figures including sales, clicks, leads, enquiries, visits, and class attendance, and is a gauge for many operators to measure their level of success.

It is also how future trends and purchasing habits are predicted, which can indicate what products and services operators can offer, where to spend resources and how to market themselves. Big Data can also indicate where current resources are best spent and where the focus of marketing activities should be in order to achieve maximum results; this could include looking at which social media channels work well for certain promotions using analytics, and whether the use of print is of benefit to the business.

What is Thick Data?

Thick Data is qualitative information such as observations, feelings, and reactions that offers insight into users or prospective users daily emotional life. Thick Data can be difficult to quantify since it aims to discover people’s emotions, stories, and is a representation of the environment they live in, and cannot be quantified with numbers.

Thick Data is usually collected in small samples and can come in many different forms, such as a in a quick chat with staff in the gym,  Facebook comments or surveys. Although it is usually only collected in small amounts that doesn’t make it inconsequential or insignificant; this data gives clear insight into the opinions and feelings of the customer, which is an exceptionally valuable resource for operators.

Why we need both

While Big Data produces the numbers, figures, and the black-and-white detail of how operators perform, this information can be greatly enhanced by Thick Data to help suggest why certain results were achieved. Thick Data fills in gaps in the numerical data with emotion, stories, comments and unquantifiable data to reveal the reasons behind the purchasing habits of the customer. This is key to making decisions on business, marketing, and operational levels. The provision of qualitative data inspires organizations to gather the insights and produce innovative ideas for the betterment of the users, operators and trusts alike.

How to collect thick data

One stand-out example that is commonly seen within sales is the following question;

“What brings you in today?”

From that simple question, a discussion is started, and Thick Data can start being collected. Asking a question like this is not just a standalone way of getting information; it’s an opportunity to expand further and continue a conversation to gain insight into the deeper opinions and feelings of the customer.

There are many opportunities to ask the customer “What brings you in today?” By adapting to the setting, Thick Data can be collected from all facets of a facility, including fitness classes, swim sessions, gym visits and even online classes. Interactions with people, and not necessarily about fitness, can provide valuable information about their likes and dislikes, their opinions and their feelings.

Social media is a fantastic resource for collecting Thick Data; it is common for customers to be more open about their opinions on social media, so checking comments and discussions about a facility can again provide quality Thick Data in a way that is time efficient and straightforward for the operator to collect. By engaging with the online community, operators can encourage a wider audience to participate in providing Thick Data, particularly through the use of polls and social posts posing questions.

The concept of combining these types of data is to help operators make the right decisions going forward. This mix of both Big Data and Thick Data provides information to help make more informed predictions about the future than Big Data alone.

Suggested Methods for Collecting Thick Data


  1. Get on the gym floor
  2. Offer guidance to instructors, and suggest posing the question “What brings you in today?”
  3. Run surveys on social media
  4. Investigate Facebook comments
  5. Ask reception about the conversations they have with customers
  6. Spend time in and around reception listening to customers and engaging in conversation
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