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Are Demographics the Key to Predicting Retail Shopping Habits

Mike Mack

There is a science behind predicting consumer behavior – literally. Customer behavior scientists forecast consumer buying habits by estimating how different segments of the population will respond to, use and purchase specific products and services. This is based on a black box model. People respond to a stimulus, which is the core of the black box model, but how do retailers create the right stimuli for their brand?  Demographics play a big role. How can you put demographics to work enhancing your sales potential?

How Demographics Factor Into Consumerism

Who is most likely to go online and shop – the grandma looking for a birthday present or the college kid who wants to decorate his dorm room? A hip grandma may very well turn to her tablet to shop, but common sense dictates that more college kids shop online than octogenarians.

Consumer behavior changes from generation to generation but groups tend to have similar habits. This is why knowing your target audience is essential to marketing. Once you boil down your perfect shopper based on demographics, you can predict trends within that group and create targeted marketing campaigns.

Big Data is Big Business

There is an intersection between data and consumer behavior. Retailers want to know what their customers are doing because it allows them to understand consumer shopping habits. It is easy to predict that a family with a new baby on the way will look to buy certain products. A kid that just graduated high school will shop very differently, though. This type of predictive analytics allows for more efficient marketing.

Demographics are the backbone of big data analytics. Statisticians group behaviors into key segments such as:

  • Age
  • Education level
  • Household income
  • Location

A study conducted by Duke University found that habits were the basis for most decisions. People use habits to shape around 45 percent of their choices. If you follow these choices by group, you can predict how they will shop. Where do they eat regularly? What kind of searches do they do online? Big data fine tunes the information based on demographics, looking closely for trends in daily habits.

Turning Demographics into Smart Marketing Choices

How a retailer uses demographics will depend on where they are in their business evolution. A store opening a physical location will look at different statistics than a big box retailer wanting in increase online sales, for example. Marketers create a demographic profile based on the needs of the store. It provides information about the type of customer a retailer can expect.

Demographics are the heart of retail trends and predictions, too. In 2015, many experts predicted the both Boomers and Millennials would influence shopping trends for the year. Drug store chains that cater to the Baby Boomer generation took this information and used it to create strategies for their store designs. They reset counters, so impulse buys were easy to reach and put carpet in areas where people stand like the register line or at the pharmacy window. This was all geared to making older people more comfortable in their stores.

The other side of that coin is Generation Y. These are the young people walking around with smartphones glued to their hands. Retailers made sure they had a presence in mobile searches and in local directories. They created store plans designed to expedite shopping efforts because young people don’t like to wait. Google used this information as the basis for their last algorithm change. They increased the ranking for websites that adapt to mobile usage.

Predicting Shopping Trends

Even the smallest retailer benefits from demographic analysis and big data to stay ahead of the trends. It starts with creating a process to collect the data. Things like inventory tracking and customer loyalty programs help you harness the information that comes with each sale. Use this data to look for fluctuations and changing behaviors. For example:

  • Do you see a shift in online purchases in the 40 to 50 age group?
  • How about income households? Are they buying more stuff online?
  • What type of products is your target audience buying each month? Does it change by season?

The key to effective predictions is asking the right questions based on demographics. From there, you can make assumptions that affect your marketing at every level. Better marketing means more effective stimuli and enhanced sales.

Here’s another article you might like: Key Demographic Insights That Can Be Provided by Big Data and Cloud Services

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