3 Key Steps to Effective Shelf Placement

Research has consistently shown that the majority of purchase decisions are made in the store. Clearly, how a product is displayed on the shelf is one critical component in determining how effectively it attracts attention, wins a spot in the consideration set, and ultimately finds its way into the shopping cart. No one would argue that shelf placement is key to product success. However, opinions often diverge on the strategies that best achieve optimal shelf placement. There are a wide range of varying viewpoints around which variables most impact success on the shelf—and what truly influences which brands get noticed and chosen.

For category captains, understanding what drives effective shelf placement can simplify and strengthen decision making—and can give retailers confidence in their recommendations. For those with less influence over displays, understanding placement can be just as important in providing ammunition for defending a brand against decisions that can hurt its performance on the shelf.

There are three key steps to evaluating and identifying the optimal placement approach for a brand.

Represent the environment

When evaluating shelf options, it’s important that test shoppers are met with a true-to-life shopping scenario. In order to get a read on how customers will react to various shelf placements, you have to get them in front of each of them—and the more realistic the retail experience is, the more realistic the shopper behaviors are.

Creating an environment that takes into consideration the other nearby products, the displays and signage a customer might see, and the path they take to get to the shelf are all going to be important aspects of an accurate evolution.

Measure what’s happening

Any tools used for placement research should include a visual tracking component. Fielding an eye-tracking study is one way to learn how different shelf concepts will resonate. A visual attention service–a model-based approach that looks at what the human eye is likely to be drawn to in any given picture—is another effective way to measure shopper interest.

The visual attention model determines the unconscious response of the human eye to a particular stimulus. It can then predict the percentage of people who will look at different elements in a particular scenario. The model is proven to be about 90% as accurate as eye tracking without the added fielding expense.

Create a framework for interpreting results

Lastly, it’s important to have a process in place to decipher the feedback from testing. By using a test and control group design, researchers can integrate and evaluate shopping behaviors in the category with attitudes gathered in a shopper survey. They then can isolate the variables that determine why different consumers may be drawn to different places and different items.

3D and virtual store simulations can support each of these important steps to effective shelf placement.

Testing through the use of virtual simulations provides the most cost-effective way to represent the store environment. It’s critical to choose a virtual approach that includes 3D capabilities, so consumers can navigate through the shopping space and interact with the environment just as they would in a real store. It’s also critical for virtual tools to be easy to manipulate. Researchers need to be able to change things around, play with different variables and test a range of hypotheses to see which really have an impact on results.

At InContext, we incorporate 3Ms visual attention model into our store simulations, called Visual Attention Analysis (VAA). This tool can quickly show how the way products are arranged on the shelf may change what people look at—and cause them to consider shopping differently for products than they have in the past.

For optimal insights, it is useful to combine virtual store research with a shopping exercise that includes an online survey. Consumers go online to take a survey and, in the middle, are given a shopping mission in a particular category. By using a test and control group design, researchers easily can integrate and evaluate shopping behaviors in the category with attitudes gathered in the survey.

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