Battle of the Sexes: Men vs Women In-store Behaviors
Rajeev Sharma
March 22, 2022

Data shows that gender impacts each category differently

Of course it’s not the battle of the sexes but it’s the battle for the sexes in retail – appealing to both demographics in a way that relates to them and engages them in-store. But do you know what percentage of your shoppers are men vs women?

Often, there are pre-conceived notions about gender composition or simply inaccurate self-reported data which does not stand up to factual data from actual observations. For example, many marketers still perceive grocery shopping to be dominated by women, whereas the most recent data from VideoMining Tracker (sample: 100 million store trips/month) shows that 52% of shoppers in grocery stores are male.

There are even bigger surprises when looking at the gender composition data for a given category. Men and women visit different parts of the store, resulting in wide and unexpected variation in the shopper profile for each category. Moreover, with the changes in household composition, lifestyles, gender roles, work from home patterns, and other recent trends, there has been significant shifts in the category shopper composition. It may be time to take a closer look at who shops your products in-store. You are likely to be very surprised!

Category Gender Index (CGI)

It is useful to have a category index which represents the percentage of men (or women) who shop that category, relative to percentage of men (or women) who visit the store. For example, in grocery stores, 68% of beer shoppers are men. So the male index for the Beer category in grocery stores is 131 (or 68/52 x 100). In convenience stores, on the other hand, 71% of store visitors are men, while 90% of beer shoppers are men, so the male index for the Beer category is 127.

Looking at another alcoholic beverage category, the female index for Spirits in grocery stores is 106, while surprisingly the female index for Spirits in convenience stores is 207. That, is in c-stores, spirits purchase is dominated by women even when they are a minority in the channel. Women are over-represented in many other categories; for example, the Frozen Breakfast category in grocery stores has a female index of 123 and the Crackers category has a female index of 125.

Thus CGI data allows us to quickly spot over-indexing (above 120) or under-indexing (below 80) of men or women in a given category and to track the gender trends in a given channel based on the latest in-store shopper data.

Why does it matter? It is because there are fundamental observed difference in how men and women shop, in how they make purchase decisions at the shelf, how they navigate the store, and how they respond to different promotions. Understanding these differences can help drive strategies for store design, marketing and merchandising that resonate better with shoppers and improve retail performance.

The gender differences can be objectively captured by in-depth analysis of behavioral data generating using AI from billions of store trips by men and women of all ages and ethnicity. (Of course, age and ethnicity also impact in-store behaviors but that is a topic for another time.)

Differences in how they navigate the store

As a starting point, there are distinct differences in overall in-store traffic patterns for men vs women. The traffic and engagement “heat maps” for women in grocery stores reflect longer trips, more often for “stocking up”, unlike men who make shorter trips directed to specific parts of the store. In general, men and women like visiting different store aisles. For example, cereal aisle sees 50% more women than men. A healthy snack category like snack nuts used to have 65% women shoppers, but during Covid-19 there was a 27% boost in men shopping that category.

Difference in at-shelf behaviors and decision making

Men and women are observed to behave differently at the shelf. This may reflect basic differences in their decision making process and even factors they consider in making their purchase decisions. For a given category, men may take more time to shop but may walk away more often. Women may read labels and consider more brands before selecting one. The shopper dynamics of each category is indeed quite different. For example, in Frozen Breakfast men took longer time to shop, seemingly confused by different choices. The net result was that only 43% of men who actively shop the category ended up buying anything, with 57% “walk away” rate. Understanding the category “shopper leakage” for both sexes and a detailed analysis of their at-shelf behaviors can be really helpful in identifying opportunities for improving category performance.

Differences in display interaction

Men and women engage with promotional displays, such as end caps and other secondary displays, quite differently. For example, women are 2x times more likely to make Beer purchases from a warm display, favoring 6-packs over larger packs. Men prefer displays with two brands, while women favor single brand displays. Similar gender differences are observed in display responses for each individual category and different types of promotions.

Difference in messaging response

Promotional messages often miss their mark because they may be targeted towards consumers and not the actual shopper, who in many cases make the final in-store purchase decision. In the simplest example, it’s a matter of getting the message right for men vs women. As a case study, we conducted A/B testing for a beverage company that was evaluating the effectiveness of multiple in-store display messaging for a big promotion tied to high school football and college scholarship. In that particular case even though the targeted promotion was for high school boys, since the shoppers were mainly moms, the female-oriented messaging proved to be almost 60% more effective than one oriented toward men. The case study also highlighted the importance of focusing on the actual in-store shopper vs consumer when the two are not the same.

Difference in impulse purchases, especially at Front End

Our data shows that women shop Front End in grocery stores 18% more than men. Women also favor traditional manned checkout lanes more than self-checkout lanes. This and other behavioral patterns are important to take into account as retailers attempt to reinvent the Front End of the stores. Likewise for each Front End category, the propensity for impulse purchase differs by gender, providing a basis for CPG manufacturers to build targeted assortment for optimizing conversion.


It is important to have factual data on not just gender composition but also how men and women shop a category differently. Only observed facts can help in uncovering the shopper dynamics for a given category. With so many factors in play, it may not be possible to predict how the shopper composition and behaviors have shifted in the post-pandemic and omni-channel retail environment. The big question that we should all consider: What is the cost of using old or incorrect shopper data? Imagine the scenario where you have a shopper marketing program that assume that 76% of category shoppers are women, while that number was only 44%, how much of your marketing and trade dollars will be wasted?

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