4 Ways Retailers Use GIS and Geographic Data for Holiday Marketing

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The intersection of Big Data with place is making retailers more efficient this holiday season, at least they hope so. How can they use mapping, or location to make their operations more efficient? The answer is both simple and complex at the same time.

Store Performance Year over Year

This is data every retailer has, and it can be used to answer some simple questions. Each year, the stores are in the same location, except in very rare instances where there have been store closings and openings in the same general area.

However, just because the physical store location remains static does not mean that the demographics of the population around the store has not changed. So looking at store performance data from one year to the next, or even over a five year period is not enough. Additional data should be added.

  • Income Data: Is the income of those in the store’s neighborhood growing, shrinking, or remaining static? How about the unemployment rate?
  • Housing/Rent Price Data: Are commercial and residential rental rates rising or falling? What about vacancy rates?
  • Surrounding Business Performance: businesses can learn a lot from their competition. How are other businesses in the area doing? Are their closures or a lot of turnover? Are any of those businesses similar to yours?
  • Population: Is the area population growing, or shrinking? Are your customers moving away? Are new ones moving in? Who are they? What do they do?
  • Age: How old are the customers in your area? Age has a lot to do with how much disposable income they have, but also how interested they will be in the products and services you offer.

All of this data is readily available and changes can be mapped annually. This information informs decisions on what items to stock and in what quantity. But this is certainly not the only way that place and data intersect.

Map showing US per capita income distribution by county, 2009-2013. Data: American Community Survey Estimates. Map: Jajhill.
Map showing US per capita income distribution by county, 2009-2013. Data: American Community Survey Estimates. Map: Jajhill, January 2015.

Using Demographic Data to Analyze Price vs. Volume

Retailers need to evaluate margins and determine: is offering 30% off a certain item going to generate enough sales volume to make the reduction in profit worth it?

What did customers buy last year? How did they pay? Did they buy mostly sale items, or those that were full price? How has the demographic of your buyer changed in the last year?

This is a area to make careful analysis. Who bought things on credit vs. debit or cash? Do you understand Apple Pay and similar NFC payment methods? What are those most commonly tied to, credit or debit accounts? Are customers buying items regardless of whether they are discounted or not? Are they buying more discounted items with debit, and using credit for full price purchases?

All of this customer information can be mapped as well, and laid over demographic data that may reveal some useful trends. Over time, certain pieces of data are revealed to be relational. Renters in a certain income bracket are more attracted to discounts than homeowners in a higher income bracket.

As the demographics in a business’s area change, these data relationships can be used to influence discount offers, timing, and stocking levels of many items, especially during the critical holiday shopping season .

How Weather Affects Retail Sales

One of the most common location based pieces of data is the weather, yet retailers have not embraced the richness of this information on a regular basis. While they often plan seasonal sales and clearance times to coincide with the change in seasons, they are often missing critical facts that could influence not only ordering and stocking issues, but when and how to hold clearance and other sales.

Storms: Although this is more real time data, using coming storms to stock things like snow chains, ice melt, and shovels is a sales opportunity for traditional retail. Don’t dismiss them for other businesses though. Large storm coming to your area? Hold a special online sale and encourage your customers to shop from home.

Climate Forecast: Every year the National Weather Service issues a climate forecast. This is a broad forecast by region, but it can and should influence retail buying and sales decisions. Chances are that no matter what your business, your customers behavior is influenced by the temperature outside. Tracking these trends and adjusting expectations accordingly can have a great impact on profits.

Winter 2015-2016 Temperature Outlook
Winter 2015-2016 Temperature Outlook. Map: NOAA’s Climate Prediction Center (CPC).

Business Disruptions: Bad weather can result in disruptions to your business, including power outages and employees being unable to get to work. Planning for these things includes a few important steps:

  • Have a watertight data backup strategy, and a contingency recovery service just in case data you store on site is lost.
  • Develop a plan to inform your customers of the disruption. Remember, not all of your customers are local, and will even know about the storm. Social media is often the answer.
  • Determine alternate locations or develop a satellite office. What would happen if your business location was compromised indefinitely? Have a backup or alternate location in mind.

Mapping can help you plan and mitigate all of these disruptions, first by enabling you to be informed so that you can prepare for them ahead of time.

Geographic data impacts every aspect of business, and by combining  huge sets of big data and place, you can increase profits by tracking store performance and demographics year over year, determining price vs. volume, and even keeping track of the weather.

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