Artificial Intelligence and Machine Learning in the Retail Sector

Artificial intelligence (AI) and machine learning (ML) are disrupting the entire business landscape across the globe. The retail industry is no exception.

Leading retailers from across the world have started experimenting with Artificial intelligence (AI) and machine learning (ML). There has been an influx of various technologies into the sector in order to shape the shopping experiences as well as the retail operation.

Retailers all across the world are already spending billions of dollars trying to stay ahead of their competition by incorporating these technologies in their day-to-day operations.

In this article, we will have a closer look at what Artificial intelligence (AI) and machine learning (ML) are in the context of the retail industry as well as the benefits that these technologies can provide.

1. Demand Prediction: Predicting demand is a very important function for the retail sector. This is because the working of many other departments depends upon this prediction.

   Prior to the introduction of Artificial intelligence (AI) and machine learning (ML), retailers have been using complicated spreadsheets in order to forecast their demand. As a result, their ability to generate such forecasts was limited.

   Leading retailers have now started utilizing AI and ML in order to mine their database, perform complex analytics and come up with a more detailed and highly accurate forecast.

   Artificial intelligence (AI) and machine learning (ML) based tools are able to quickly analyse past data provided by the stores as well as the current trends in the marketplace to come up with a more accurate prediction. An accurate prediction helps retailers avoid stockouts as well as having their money tied in inventory, both of which are detrimental to their finances.

2. Supply Chain Prediction: The accurate demand forecasts which have been generated above can then be used to streamline the production as well as the distribution process.

   Retailers tend to have complex supply chains wherein their goods are sourced from all over the world. These operations can be very complex to manage. Also, the inability to manage these operations on a day to day basis can cost the retailers a lot of money. This is where Artificial intelligence (AI) and machine learning (ML) come to the rescue. They are able to create an optimized schedule for supply chain operations. These technologies are also able to adapt the data in real time based on the current situation of the supply chain.

3. Recommendation Engines: Personalized shopping and recommendation engine are another important use case for Artificial intelligence (AI) and machine learning (ML). This technique has been successfully used by online retailers since they can monitor the purchasing behaviour as well as browsing history of the buyer to recommend products that the buyer may be interested in.

   The online retailers have witnessed an increase in their sales because of such recommendations. Offline brick and mortar retailers are also trying to use recommendation engines. They try to collect behavioural and financial data about the customer and then try to come up with personalized offers for them.

   Offline retailers generally lag behind because of the paucity of data. However, they have now created their own applications which they try to get the end customer to install on their phones. This helps them obtain access to the data that they need.

4. Dynamic Pricing: The use of Artificial intelligence (AI) and machine learning (ML) technology has enabled retailers to price their products in a dynamic way. This means that retailers can dynamically review the demand and raise the prices of certain products if they find the demand to be inelastic.

   However, it is important to note that many retailers did implement this strategy during the coronavirus pandemic and faced a backlash. This is because these retailers increased the prices of goods related to hygiene creating an impression that there was going to be a shortage. This created panic amongst the consumers.

   Once the consumers understood the real situation, they labelled the retailers as being opportunistic. The end result was that the brand value of many retailers took a significant hit.

5. Video Surveillance: Artificial intelligence (AI) and machine learning (ML) are also being used in the retail sector in order to increase the security of the retail store. Security software has been trained in order to identify suspicious behaviour of customers and staff who are involved in shoplifting.

   The software can identify such people and immediately send a report to the security personnel. Retailers which have implemented Artificial intelligence (AI) and machine learning (ML) based security systems have reported a drastic reduction in shrinkage. However, these software tools are currently very expensive. Their price needs to be rationalized so that retailers all over the globe can deploy such software in their stores.

It is certain that Artificial intelligence (AI) and machine learning (ML) are very important for the future of the retail industry.

It is expected that retailers all over the world are likely to spend upwards of $50 billion trying to implement Artificial intelligence (AI) and machine learning (ML) in the industry. However, these technologies are just new tools which will be used to play an old game.

There is no doubt about the fact that these tools provide unmatched benefits to retailers. However, the decision to deploy these tools needs to be done in a strategic manner in order to ensure that the retailer can get the maximum advantage from the same.