Geomarketing and the Pitfalls of Bad Location Data 

image showing a customer browsing retail shops online

Geomarketing or location-based marketing has been one of the most innovative advertising and marketing solutions created by mankind. Powered by location data of consumers, geomarketing is a smart and proactive technique to influence consumers’ mindset and has especially affected the way retail companies acquire customers. 

Geomarketing for retail

Location-based marketing is being drafted in almost every sales and marketing process of major retail companies. The ease of access to location data and geomarketing tools has become a great incentive for marketers to implement location-based advertisement and geo-acquisition strategies. However, there is a big caveat, which isn’t highlighted and which can potentially turn this beneficial strategy into just another not-so-useful marketing gimmick. 

Image showing a shopping mall complex with numerous retail outlets to emphasize the idea of geomarketing
Location-based marketing has ushered in a new way in the retail world to execute sales

The biggest challenge in geomarketing

Let’s take an example to understand this better. Bob works as the regional sales manager of a leading retail company. In order to meet his regional sales targets, he started exploring geomarketing. Impressed by the relative ease of implementation, Bob decided to pivot his retail sales funnel on geomarketing. He hired a geomarketing solutions provider to implement this. 

The initial months of setting up the geomarketing strategy went like a breeze. The sales funnel started growing and Bob patted himself. A couple of months later, however, Bob encountered a big setback.

Bob noticed that the sales had become stagnant and the growth curve had almost flattened. With this trend, it wouldn’t be possible to meet his sales target. Bob was at his wit’s end. He was desperately trying to figure out what went wrong! 

Is it the process or the data?

It didn’t take Bob long to know what was going on. He had implemented all the processes with more than due diligence. There was only one way it could have gone wrong- the geofences created weren’t accurate. 

The problem was in the location data. The geofences were inaccurate and due to the large number of stores changing tenants, they were even outdated. Because of the inaccurate geofences, his impressions lost the benefit of precise targeting. Moreover, there was a mismatch between the messaging sent and the current need of the consumer it was sent to. 

The actual problem – inaccurate geofences

This is a classic example of why geomarketing strategies fail in the long run. It’s as much about the data as it is about the process. In fact, the inaccuracy of location data or bad location data is one of the biggest challenges in geomarketing recognized by marketers. A recent study found that 60 percent of location data is inaccurate. Moreover, during a  survey of marketers in North America, 25% of respondents said that there was a lack of clarity on location data collection.

Clearly, the quality and accuracy of location data like geofences and POI data are the most important metrics for defining the success of any location-based advertisement campaign. To understand this let’s delve deeper into the different types of location data involved in geomarketing. 

Location data attributes in geomarketing

It is important to understand three important attributes of location data to understand geomarketing better.

Icon of GPS for location data


Something everyone is familiar with – GPS or Global Positioning System is a way of tracking the geolocation of users through a global navigation satellite system by triangulating data streams. GPS location is used to locate stores, products, or routes in real-time. In fact, with the large scale usage of smartphones, GPS data acts as key inputs/triggers for in-app advertisements as mobile GPS data is tracked through various apps.

Icon of POI for location data for geomarketing


POI or Point of Interest denotes a particular location or geographical point that usually possesses some commercial utility. POIs can be retail stores, schools, stores, hospitals, residences, parks, stadiums, etc. For the retail segment, the POI data of retail outlets and stores become an anchor point to set up geomarketing. The POI data generally includes the name of the retail entity, area, location, opening and closing hours, etc.

Icon of Geofence for location data for geomarketing


The most important input for any geomarketing campaign is a geofence. Think of it as a boundary/fence that encloses a store. It can be of any shape and is visualized as a polygon. Typically, the accuracy of the geofence is critical since it is the single most important data point that triggers an advertisement. Exact store outlines and parking outlines are being increasingly used as geofences and have replaced traditional radial geofences.

Using the above three essential location elements numerous location targeting campaigns are being executed worldwide. But there are numerous pitfalls one should be aware of. 

What makes location data bad?

The success and ROI of an LBA or location-based advertising campaign depend upon the accuracy and quality of the location data collected. The biggest issue, in this case, is the accuracy of geofences and POI data. And this is a serious concern because unlike consumer GPS data which is pretty standard now, the quality of POI data and the associated geofences is not standardized and needs to be updated frequently. In fact, the single biggest problem is that many stores shut down or relocate. The gradient of the effect that a degree of error in POI data and geofencing has on the campaign performance is immense. 

Geomarketing solution providers gather POI data and geofences either through offshore teams or other geospatial vendors. Now, either way, the method of data extraction or feature extraction is mostly manual. GIS software is used to manually draft geofences around a multi-brand outlet and label it for identification. Moreover, POI data are derived mostly from the internet or historical data records. What are the shortcomings of this method?

1. Geofence accuracy & vintage

Drawing polygons around stores and parking lots is manually intensive thus leading to a high probability of human error. Often updates happen once in 2 years, leading to inaccurate and outdated geofences. 

2. POI vintage

Retail companies often find themselves running geomarketing campaigns on stores that have shut down or been relocated to some other location. This leads to low ROIs. In some cases, where the ground situation has changed significantly, the campaign may backfire completely.  

How to get good location data for geomarketing

One of the ways to solve the problem of updating constantly changing geofences is a well-engineered AI and computer vision pipeline that can auto-update precise geofences, resolving this problem to a large extent. As a matter of fact, at Attentive AI, we have developed models that can extract geofences with a positional accuracy of more than 99%. Moreover, the frequency of data updates can be quarterly instead of once in 2 years. 

Need accurate geofences?

Contact us to know more about how you can use Attentive AI’s solutions to boost your geomarketing solutions and offerings.

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