Geospatial Analytics

 

The new wave of data analytics and artificial intelligence advances is seeping into business and opening new possibilities for retailers. At a time when store closures and tight margins pose challenges on both side of the Atlantic, new applications of techniques like geospatial analytics present opportunities.

 

 

 

In a book on the topic, authors Bill Day et. al. define geospatial data as data with location information. Geospatial analytics, in a business setting, is the application of analytical techniques to such data.

 

 

 

Geospatial analytics, by itself, is not a new field, but big data, automation tools, and large scale data warehousing is now allowing enterprises to do more with it. It is in this vein that it can be applied even by smaller organizations that might not have been able to create expensive geospatial deployments in the past.

 

For retailers, using geospatial analytics with cutting edge analytics platforms allows you to do some or all of the following

 

As you can see, the range and scope of what you can do with geospatial analytics is quite broad. While it may appear daunting, the best way to get started is to jump right in.

 

 

 

One of the possible, and timely, applications of geospatial analytics has to do with the wave of store closures in the last several years. Since 2015, the scale of store closures in the UK and other countries has reached alarming proportions.

 

According to the Retail Gazette, in 2019, the UK faces as many as 23,000 store closures, a figure associated with 175,000 lost jobs. 

 

In such a bleak environment, it’s hard to see any positives, but applying geospatial analytics can help retailers alleviate some of the challenges.

 

 

 

Part of the problem when a retail chain is having to consider store closures is that it often cuts the bad along with the good. In the absence of geospatial analytics, poorly performing stores that have the potential to be turned around get cut along with those that have no such prospects. 

 

In this way, a struggling retailer can destroy the good part of the business that could have brought future improvements in performance.

 

 

 

A geospatial approach looks at the performance data of a struggling retailer’s stores at a fine-grained level. Stores that are performing badly are categorized based on location and a host of other characteristics. 

 

The data is modelled and run through complex algorithms that normalize for features in the data that may be hidden from a casual, linear, analysis. Instead, stores that are contributing to sales through other means, such as driving shoppers to the retailer’s online properties, get that traffic credited to them.

 

A store that might have seemed like a loss maker in conventional analysis, in a geospatial analysis, might emerge as a crucial driver of online sales to shoppers in its immediate geographic area. 

 

This typically happens, for example, when shoppers use a brick and mortar store to window shop, then actually purchase the product from the retailer’s nationally-available online store. For a variety of reasons, such as indecision, or simply being busy with other things, shoppers often space out researching and buying a product.

 

Geospatial analytics allows retailers who use the data and run rigorous analytics on it to make more insightful decisions than those who only look at performance data in aggregate.

 

 

 

Another area in which the use of geospatial analytics can help retailers is in planning and executing advertising campaigns. 

 

Big budget ad campaigns almost always require some level of geospatial analysis due to the potentially enormous costs and risks associated with such campaigns. 

 

Geospatial analytics will help in the research phase as you analyze customer responses to product satisfaction surveys and other important customer data. In the process, you will gain insights about who your ideal product users are and what their current perceptions of your product are. 

 

Knowing perceptions and attitudes towards your product in each of the geographic areas you target will be critical data in the campaign design stage. The campaigns you design, as a result, can address perceived product weaknesses or make a case based on the strong points. 

 

Even if you are operating with a smaller budget, there may be savings or optimizations you can achieve by utilizing geospatial analytics in the process.

 

 

 

Because culture and societal trends differ from place to place, the effectiveness of advertising campaigns often shows big geographic differences. The same piece of creative will not always achieve overwhelming success regardless of where you run it.

 

Geospatial analytics allows you and your team to identify values or attitudes that have a material impact on how your campaign will be received. For example, you might be able to come up with a ranking of factors most important to each region or city where your ads will run. Based on which factors are important to the target market, you can then design and run localized campaigns that connect with the population.

 

 

 

Another beneficial application of geospatial analytics in ad campaigns for retailers comes in the decision of how to deploy ad budget for a campaign. Especially for national campaigns, there might be multiple cities, metros, and rural areas that could potentially be covered. 

 

Deciding where to deploy the ads, and what fraction of the budget to allocate to each area, blindly, will lead to lacklustre results. Instead, crunching the data and running the numbers using proper geospatial analytic techniques will yield the answers as to what your best moves might be.

 

 

 

Any retailer can benefit from applying geospatial analytics in their decision-making matrix. While the techniques of geospatial analytics are often more appealing to large enterprises with huge benefits, even smaller companies can benefit. 

 

Using big data techniques and platforms that have brought down the cost of analytic computing, smaller retailers can get in on the game. 

 

Whether your goal is to survive the current wave of store closures or to design effective ad campaigns, among others, you could gain a practical advantage with geospatial analytics for retail.