ML in the retail industry – Use cases, applications, and the future Part 5
As we touched upon in the previous parts of this multi-part blog series, we saw that conventional analytics have been perfectly functional for the data-intensive, and data-driven retail space. But, emergent technologies such as Artificial Intelligence (AI) and Machine Learning (ML) have put forth a completely new level of depth to data process which provides in-depth business insights. Professionals in data science could potentially open up a plethora of avenues to business owners, extraction of anomalies and correlations from several AI/ML models.
AI’s presence in retail today
We have entered head first into 2022 and AI-based solutions still have a lot more prospect to grow, even taking into consideration the massive progression that has occurred during the lockdown period. This part of this multi-part blog series will further explore instances of real-world AI applications which serve as concrete value additions.
Leading 12 Uses of AI in Retail
- Outlets can go cashier-less
Automation and robotization have several positive outcomes for retail.
- Chatbots to help with client servicing.
Chatbots have become commonplace during the time of the COVID-19 pandemic.
- In-store help
Emergent tech makes lives easier for both the customer and the staff member.
- Price Adjustments
Outcome analysis of pricing strategies is a possibility
- Price forecasting
Price predictions is a nuanced process
- Supply chain administration and logistics
Botched execution in this sphere causes losses for retail outfits, internationally, to the tune of approximately $1.1 trillion annually. Leftovers and out-of-stock situations can be eradicated. Deployment of AI within the retail supply chain can be leveraged for the purpose of restocking – quantifying the demand for a specific product or item by taking into consideration a detailed history of sales figures, trends, weather, locations, promos, and other parameters.
- ML in Retail: Product Categorization
Lovethesales.com is a brilliant instance of ML within the retail space. It leverages ML models to categorize more than a million inventory objects from assorted sellers. Systems driven by Machine Learning undertake tagging of goods and classify them in a differing classification for clients who are looking for a specific variant of product. Sellers on Lalafo, for instance, can merely upload pictures of the products they desire to sell and ML retail software driven by Computer Vision would identify it, categorize it, and even make a pricing suggestion. This platform already undertakes processing of >900 requests/second enhancing sales figures with appropriate content harnessing ML models.
- Visual Search
Visual Search systems and applications based on AI facilitate clients to upload pictures and identify similar products on the basis of shapes, colours, and patterns. Image recognition technology from certain vendors promise approximately 95% accuracy. IR tech deployed by American Eagle leverages Visual Search – which not just assists individuals obtain the same or similar clothes but however, indicates what would be appropriate for it.
- Voice Search
Retail heavyweights and several other major brands leverage Amazon or Google AI tech to furnish clients with easy to access and quick voice search. Now clients can just query Alexa for the item that is wanted and its delivery status without any inputs. As a matter of fact, 27% of individuals around the globe leverage voice search on smartphones, and more than half have a preference for them over smartphone apps and webpages.
- Virtual fitment rooms
This is yet another amazing deployment we are required to talk about. Virtual fitment rooms are an amazing way for clients to save time and identify the perfect outfit with all the aspects matched in the best way possible – within a few minutes! Businesses like GAP, Levi’s, Old Navy, and Brooks Brothers setup scanners that have the capacity to undertake scanning within the span of 20 seconds and measure 200k points of our bodies in this timeframe.
- Client satisfaction tracking
AI has the capacity to detect the disposition and mood of your clients during the course of the shopping experience. Walmart has already put forth a facial identification system for this function. Cameras are setup at every checkout lane and if a client is not satisfied, a store rep will assist them. Mood tracking will certainly assist in developing more robust relationships with clients.
- Client behaviour prediction
AI platforms on the market facilitate business leadership to leverage behavioural economics and develop an individual approach to every client. Algorithms undertake processing of the client’s emotional reactions and behaviour during prior shopping experiences and attempts to come up with optimum pricing offers for a specific visitor.
AI within the retail supply chain
The supply is a sphere that could be revolutionized massively through the implementation of AI. There is always a requirement for faster product delivery and enhanced inventory control. AI can furnish an obvious vision of how a specific supply chain functions, identify inefficiencies, and develop ways to make it better.
There are several use cases available, let’s take a deeper look to point out to the major benefits of AI within the supply chain.
One of the major AI vendors makes the claim that the implementation of Artificial Intelligence in inventory management had the outcome of a 32% expense reduction across all operations.
- 49% (approximately half) of survey respondents predict that AI will reduce expenditure within the supply chain.
- 44% predict that AI will enhance and drive productivity.
- 43% are certain that AI will be a dominant factor in enhancing revenue.
- 40% identify the leveraging of AI in retail decision-making as the primary advantage of the technology.
AI/ML-based solution can greatly benefit your retail business. Emergent tech infuses a much-needed freshness into operations that help you keep up the pace with the contestants in the market. Automated processes, improved insights for your organization, and enhanced client engagement will have the outcome of improved revenue. AI retail solutions such as chatbots, visual search, or voice search can drastically revolutionize your bottom line.
The next part of this blog will take a deeper look at ML use cases, its applications, and the future.