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Understanding Data: The Pros and Cons of Observational Data

Understanding Data: The Pros and Cons of Observational Data

Originally Posted in June 2018. Updated September 2021.

KEY TAKEAWAYS:

– Observational data focuses on understanding customers’ emotions and intentions.

– Observational data allows marketers to explore why and how their customers do what they do, but relied heavily on accurate and attentive observaiton.

– Bias can be present in observational data and observations can be unreliable.

– The best way to use observational data is to combine it with objective data.

Observational data tells us a lot about what our customers want and need, as well as how they put those impulses into action. One way to really understand observational data is to listen to Tricia Wang’s TED talk. Wang’s employer, a large cell phone company, had a question many business owners face: was it time to expand their business, and if so, was the market they were considering the right one to try to enter? Wang spent months making observations in the target marketplace, having conversations with people and developing a deeper understanding of how they lived and what was important to them. Her employer didn’t listen to what Wang had learned through this process, but it turns out that she was right: when the competition tried to enter that same market, they met with resounding success.

What is Observational Data?

Observational data is also known as Thick Data – data that focuses on understanding the customer’s emotions and intentions. While objective data tells us what customers are doing, observational data focus on the why. Many retailers, who are highly motivated to understand what will lead someone to visit their store and make a purchase, have superior observational data capture and analysis skills. The information gathered from observation can be helpful to understanding ongoing processes or situations because it provides context to a series of events, actions, and behaviors. Observational data answers the Whys and Hows of our research.

Examples of Observational Data in Marketing

  • Cookies
    Using cookies to see how often customers visit and view your website is a way to observe what content your audience prefers.
  • Heat Maps
    Many email marketing platforms and landing page systems offer heat maps that show you where people click and how often, helping you to see where people look and what they are looking for.
  • Focus Groups
    Putting a bunch of opinionated comsumers in a room to use or review a product provides a wealth of observational data regarding how real customers interact with your offerings.
  • Rough Counts
    Even retailers simply glancing out into the parking lot and thinking “wow it’s busy right now!” is observational data that can inform when to offer additional appointments or ensure more staff members are present.

Observation is a market research technique in which highly trained researchers generally watch how people or consumers behave and interact in the market under natural conditions. It is designed to give precisely detailed and actual information on what consumers do as they interact in a given market niche.

– Laura Lake, The Balance Small Business

The Upside of Observational Data

Observational data relies on the observer’s ability to discern important details and draw accurate insights based on what they see. This is a skill that can be learned, and individuals become better at it over time, especially if they focus on doing a good job. Observational data can be very detailed and is a rich source of material for creative content. In a perfect world, observational data will be recorded and organized, so the insights gathered can be used for a long time.

The Downside of Observational Data

When it comes to observational data, we’re relying on an individual’s perception. This can be unreliable or even prove useless to your research. If an observer isn’t skilled, is distracted, or is having their judgment influenced by outside factors, the insights gathered are of questionable value. After all, bias can exist in market research regardless of whether the data is qualitative or quantitative. Data consistency between individuals varies: the observations an experienced business owner makes can be very different than those made by a new employee. Finally, observational data is seldom, if ever, recorded or organized.

Making the Most of Observational Data

To get full value from your observational data, use it in combination with the objective data collected by your website, social media, POS system, and other data capture tools. This is called Smart Data and it’s what you need to grow your business! Want more help collecting and understanding data? Check out these offerings from our experts.

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