Gaining a competitive edge in retail with Machine Learning

Undeniably, retail has been one of the industries that have been impacted the most from the coronavirus pandemic. Today, the retail landscape is faced with changing consumer behaviours favouring online shopping, and fiercer competition as traditional ‘physical’ retailers are trying to recoup some of their losses leveraging digital commerce and new etailers are entering the field. In the UK alone, more than 85,000 businesses launched online stores or joining online marketplaces in the first four months of the lockdown, according to Growth Intelligence.

In such a competitive environment where consumers have all the power at their fingertips, price difference and timing of offers is more critical than ever. For retailers, missing out on important market intelligence is not an option, but, with information being shared in different formats (video, image, text etc), across different channels, monitoring competitors can be a challenging task.

Machine Learning can help retailers access valuable intelligence in real time, get accurate recommendations on the best plan to action and gain the all-important edge needed in today’s highly digitalised retail space.

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Early trend detection

So far, we have focused on new, more commercially viable applications of machine learning using existing algorithms. How are we evolving these algorithms today? One such new algorithm is ‘early trend detection’. Until now, we have seen some quite accurate algorithms that help analyse trends. Today, we are witnessing the emergence of new algorithms that are able to detect a trend almost in advance, giving tremendous competitive insight and advantage.

Time-to-Insight (TTI)

Time-to-insight or TTI means that a company can have access to relevant information, faster. In the retail world time is indeed of the essence and machine learning in combination with Big Data technologies, real time analytics and streaming technologies, accelerates TTI bringing a clear benefit to the business.


Decisions can be as effective as the accuracy of the data they are based upon. Machine learning algorithms can provide not only the speed, but also the much-needed accuracy of information, so that the business can make more informed and effective decisions. Especially in the B2C space, where there is an abundance of information for a business to extract insights, there has been a lot of research showing that machine learning algorithms are better at producing more accurate results and predictions than humans.

Improved customer loyalty

In such a highly competitive market, it is easy to lose customers to the competition if they think they are getting better deals. Having a real-time view of your competitors’ product launches, prices, special offers etc, and using the predictive models enable by machine learning, you are able to provide more timely, targeted and ‘fair’ prices and offers, increasing customer loyalty and share of wallet.

Cost efficiencies

At the end of the day, it is all about achieving a viable business operation and machine learning brings a number of benefits one of which is in achieving significant cost efficiencies. So far, we have implied about the cost of making a wrong decision -which can be detrimental. There is however another direct saving, and this is from automating the entire process and therefore the cost of 3rd parties that provide such services as mystery shopping, online price monitoring tools, social tracking, media monitoring etc. What’s more, internal teams can be liberated from mundane tasks and focus on bringing more value to the business.


By having a more accurate understanding of the market, the competitors and their prices, retailers are better equipped not just to successfully compete, but also to negotiate with their suppliers aiming at better, facts-driven procurement deals.

Final thoughts

A point to remember is that machine learning is first and foremost a business investment and not a technological one. Fail to prove a compelling ROI and the company might miss out on a great opportunity to be ahead of competition and create more revenue opportunities.

Think about starting small, experimenting with open-source tools and seeking expert advice to ensure early success and buy in from the business. 

If you would like to find out more about how our Data & Analytics experts could help you improve competitor intelligence while enabling you to open your digital horizons, email us at

Other useful links:

Machine Learning for Competitive Intelligence in Retail

Sentiment Analysis Accelerator

Rapidly respond to market changes in retail

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