A Customer-Research Method You Can Do Easily: Observe Them
Emory University Professor Susan Hogan says any garden retailer can better understand how customers interact with your store by using a simple method: observe them shopping your store.
Although it’s a simple concept, it’s important to execute it carefully to get results that you can use.
In 2012, as part of our brand’s 10% Project, we recruited Hogan to work with Massachusetts-based Lakeview Nurseries’ Michelle Harvey as she tried out the observational research method.
Harvey recruited two women to track 40 customers over two weekends. Harvey was confident she understood who her customer was, and did not anticipate any surprises. Not only did using the observational study highlight some problems she needed to address, she learned that her most valuable customer group was not who she anticipated.
She felt women in their 50s and 60s were her key customer. But tracking customers showed that 30-something couples spent more money at Lakeview. The results were so surprising, Harvey and her husband Richard Bursch conducted the same study again that year and the years following. The results were the same.
These results changed their marketing messages and helped them identify a need for training and moving displays. The results were so helpful, the couple saw increased sales from one weekend to the next from the changes they made.
If you wish to copy their success, here is how the method works:
Step 1: Recruit Observers
Finding the right people to observe customers can be tricky. The observer’s job will be to track a customer from the moment they walk in, and follow them through the store as they shop until they exit the store.
This observer needs to be someone who will not alarm shoppers, nor call attention to themselves. As Harvey noted in her diary, employees also make poor choices. After all, they should all be serving customers. And they are too well known to regular customers to be inconspicuous.
Harvey hit on ideal observers by recruiting ladies from a local gardening club. First, the two volunteers she recruited were older, and so would not worry most shoppers even if they noticed she was following them. Second, the women did not have a vested interest in the outcome. A bonus for Harvey was that the two she selected had an attention for detail.
Step 2: Decide What To Observe
The data you can collect simply from observing customers is vast.
There are the basics: Age, gender, whether they are shopping alone, with family or with friends, the quality of the clothing or car driven. Another basic observation is the length of time a customer spent in the store.
It’s important to gather these basic observations, since they will help you analyze your results later.
Then there is behavior. Do customers walk purposely to a department or look at only one product category? Or do they stroll through the store, picking up several items to buy? Do they use a chart? Do they speak to staff? Do they read signs? Which displays draw the most attention? Which path do they take through the store? Do they make purchases? And how many of those purchases were made after speaking with staff? How many were added to their carts during check out? And, most importantly, what did they buy?
One last area you will want to include on your list is a general comments section. Some of Harvey’s most valuable information came from observations that did not easily fit into any of the preset categories she assigned to her garden club ladies.
Whichever of these items you select, make sure that your observers are consistent in recording what happens in each category.
Step 3: Record The Results
Harvey collected the notes from her observers and organized them in a spreadsheet. Doing so allowed her to sort through her data easily, finding important patterns like which groups were most likely to buy.
It wasn’t until the data was compiled in her spreadsheet that Harvey realized that the customers most likely to make purchases, and large purchases at that, were 30-something couples, not the 60-something females, as she expected.
Below is a sampling of the data that Harvey’s garden club ladies gathered.
|Customer 1||Customer 2||Customer 3|
|Time In Store||35 min.||45 min.||20 min.|
|Female, 1 child||Female||Couple|
|Cart?||No||No||Yes, needed help with the brake.|
|Followed action alley, but stopped before trees and went back to perennials||Followed action alley all the way||Followed action alley all the way|
| What Was
|Window boxes, plants to fill, bagged soil, hummingbird feeder and perennials||Gift pansy basket||Shrubs and perennials|
| Add Ons At Check Out
||Hummingbird feeder||No add ons at register||No add ons at register|
|Observations||Seemed to pick up an item from every department. Staff worked with her to find plants and soil to fill window boxes. She picked out the rest of the items by herself.||Picked up several flowering plants and read tags before making purchase.||Several-hundred-dollar purchase in what appeared to be a short time spent at the store.|
Step 4: Analyze The Data
If knowledge is power, not acting on what you learn is power wasted.
Harvey learned several things from her data and acted quickly on the most urgent. She called an emergency training meeting when she learned tie-in sales were not occurring. She built a display at a point on her action alley or racetrack where customers regularly took a short cut.
She did both of these the same week she got her results in a spreadsheet and was able to analyze the research.
It’s easy to analyze your data. Simply choose key data as your sorting standard. For example, if you want to see which customer group was most likely to talk to staff, use the “Talk To Staff?” column or row that.
Consider doing your own observational research this weekend. What you learn can change how the rest of your season performs.