AI in Retail – The Advantages of Machine Learning in Point of Sale

The age of machine learning and AI in retail has come. While artificial intelligence is doing its best for automated data analysis, we can enjoy a talk on how it can help us win a never-ending competition for tech-savvy modern customers. This time, through Retail Point of Sale (POS).

Retailers have been collecting information about customers via their POS terminals for quite a while now. It used to be a way to analyze the behavior of individual clients. However, many important questions remained undetermined.

What was happening once the product was sold? Did the customers speak highly of their purchases or lambasting them? Once unintelligible, today, the pieces of the retail puzzle are easy to assemble and interpret by AI algorithms.

Today POS data can give so much more than many of us expected

Apart from handling their primary function, advanced retail POS systems enable retailers to sharpen the business effortlessly (if expertly, of course) and magically do two great things at the same time:

  • Asses and anatomize human networks of product distribution
  • Improve ROI significantly without substantial investments and extra expenditures

The good news is, there’s no actual need to go back to school to score a hit and make sales skyrocket with a knock-on effect. No new hires and no budget-unfriendly strategies are required whatsoever. Machine learning draws the future nearer through digital tools for all backstage retail activities: gathering competitive data, price scraping, price management, and more.

Hard to imagine how much real human energy might demand that type of insight, but it is also unnecessary. The most impressive disruption lies in the fact it can all be achieved through smart software, which accumulates and processes information for a profound analysis.

Once considered sci-fi, today, Artificial Intelligence offers an opportunity to create prognoses with the rate accuracy reaching 86%, a recent study reveals. Deep learning turns out to be strikingly suitable for multi-variable environments that modern markets are known for in the retail industry.

Machine learning raises the bar for players of all calibers

Getting your data in order and putting it into use has become critical for business growth, no matter whether that is a bigness or a single retail outlet. It allows all the marketers to:

  • Increase sales revenue
  • Personalize customers’ experiences and win way more returning customers
  • Plan a supply chain more effectively and enhance inventory turnover
  • Prevent losses
  • Take advantage of dynamic pricing
  • Foresee possible changes in the market and take timely measures

Experience personalization deserves a special mention; almost four-fifths of 21st-century customers see it among shaping factors that might make them return for more. Over half of respondents claim personalization to be on their customer engagement principles list. At the same time, more and more shoppers insist on profound omnichannel experiences. And that’s where AI covers all the grounds.

We’re also seeing this applied for all-encompassing customer journey orchestration. The latest platforms can join the dots to connect every part of a path which was previously too disjointed and siloed for retailers to map. This allows for entirely tailored experiences to be rolled out consistently at every conceivable touchpoint.

POS + AI concerns

As it usually happens, every answer raises new questions. This time, security. Intelligent information has always been under the spotlight, and with many examples of how the trust circle can be broken by leakage or attack, matters of concern are still up-to-the-minute.

Luckily, human network analytics can be performed without a breach of privacy, and various arrangements can be made to ensure the data is kept secure and inaccessible to unauthorized users. Encryption, application whitelisting, regular software updates, secure password…trust your developer and keep your powder dry.

While the retail environment is changing (and preparing for even bigger changes than the ones occurring right now), competitors ought to keep pace with the challenges and spit-polished their digital weaponry through careful tool selection and bold moves meant to disrupt the market with more innovations.


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