Using Machine Learning To Understand Your Customers Better

Using Machine Learning To Understand Your Customers Better

When retailers aim to collect more data about their customers, they follow larger sources of market information. Here are some notable examples of technological advancement in machine learning allowing retailers to understand their customers better.

As the global retail market is expanding, the industry has become capable of growing and competing with challenges, such as infrastructure, competition, and above all, the absence of efficient analysis tools and tracking retail execution methods in the stores.

Here are some notable examples of technological advancement in machine learning that has allowed retailers to understand their customers better: 

Image Recognition: ​Thanks to this technology, retailers, and manufacturers are now capable of grasping an accurate picture of their existing marketplace to react in real time. Data collected by the manufacturer’s sales reps can be transformed into actionable intelligence in real time. This converts sales execution into a new science. 

By employing image recognition, retailers can save up to 60% of audit time in stores with 98% auditing accuracy. This implies retailers will be able to get their hands on accurate and reliable data on their distribution, knowing which items are out of stock. It also makes the wealth of other actionable insights readily available and accessible by retailers.  

Through the output from predictive analytics and machine learning, the image recognition technology has come a long way in the retail world. Many retail stores use technology to track customers when they are in the store as it contributes to a positive shopping experience. Moreover, the fine-grained image recognition engine evaluates the image or video capture of any product on the shelf and successfully differentiates between minute design changes in brands and SKUs (stock-keeping units). 

For instance, consider all the different Coca-Cola bottles that were promoted and exclusively branded for the World Cup. The technology will update its SKU in the database automatically and will not require any manual updates from the sales reps. 

Geo-Fencing: With geo-fencing, a retailer successfully targets location-specific information to a set of ZIP codes. This allows more chances of accessing premium inventory. The audience and marketing content will be more relevant to trigger higher conversion rates.

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