Artificial Intelligence has become embedded into our everyday lives – every time we ask Alexa for the weather, or watch a movie recommendation, what’s actually happening behind the scenes is that a vast neural network is analysing millions of datapoints to give us useable information. Retail is no exception with AI transforming the way retailers operate today.

  • iVend Retail Analytics

iVend helps retailers to analyse and report on their data.

We’re positioning retailers for the future of AI in retail.

AI is all about analysing data to solve problems – it uses existing data to learn how to spot patterns, understand behaviours, and predict future situations, then applies this learning to new situations.

AI in retail

There is a massive opportunity for retailers to harness the power of AI. The industry lends itself to AI:

Firstly, effective AI depends on having massive amounts of ‘training data’ from which to learn. Retail already captures vast quantities of data, so has the training data that an AI in retail application needs to be effective.

Secondly, much of the value of AI (69%* according to McKinsey) is in the way it can extend the capabilities of traditional analytics. Retailers understand the value of analytics, so moving to AI is a natural step.

Thirdly, in terms of business processes, AI drives the biggest benefits in supply chain management and in sales and marketing – two functions that are at the very core of retail.

These factors combine to offer a potential value of AI in retail of $400-$800bn**, with an opportunity for retailers to improve operational efficiency, and dramatically enhance customer experience.

The future of AI in retail

AI has a host of possibilities for transformational change. Let’s take a look at some AI in retail examples:

  • Forecasting – AI engines can use data including previous sales figures, weather patterns and customer sentiment to predict product demand. This AI in retail application allows retailers to optimise operations, including adjusting inventory keeping, purchasing and staffing schedules to balance efficiency with meeting customer demand.

  • AI and robotics in retail warehouses – using warehouse training data, AI robots can learn how to perform key warehouse functions such as sorting, putaway, picking and packing, freeing up staff to focus on higher value processes.

  • Customer profiling – one of the highest value functions of AI is categorising customers, based on common characteristics, demographics, purchasing preferences or behaviours.

  • Personalised promotions – customer profiling will enable retailers to deliver highly tailored personalised promotions and offers to shoppers. This use of AI in retail can drive a very significant 10 to 15 percent revenue lift

  • Cross sell up sell –Shoppers love ’you bought this, so you’ll love that’ recommendations, and are 40% more likely to look at them than other products. Online stores can use AI to personalise each shopper’s home page, with products and cross-selling suggestions based on their profile and preferences.

  • Visual search – this AI in retail application enables shoppers to use pictures, not words, to find products. Smart AI can analyse the image and direct the shopper to the retailer’s website to purchase it. The visual search application of AI in retail is particularly popular with the under 34 demographic, with (as of August 2022) 34% having tried it, and 12% already using it regularly.

  • Cashierless stores – This use of AI offers retail customers the ultimate in fast and convenient shopping. The Amazon Go store, for example, uses visual data to identify customer actions (picking up goods, returning goods), along with smart fixtures to sense which products are on/off the shelves, and entry/exit gates that detect shoppers and scan QR codes for contactless payments and receipts.

  • Customer service management – a rapidly growing application in retail of AI is for customer service management, where chatbots and virtual assistants answer frequently asked questions and direct customers to answers and information. Conversational AI in retail uses natural language process to interactively ‘chat’ with customers, delivering rapid service to customers with fewer human staff.

The future of AI in retail is exciting, taking the shopping experience to new levels, whilst at the same time helping retailers to operate more effectively and efficiently, streamlining processes and saving costs. And we’re not talking distant future – many of the AI in retail applications are starting now, and are delivering real benefits to retailers and customers alike.

References:-
*https://www.mckinsey.com/~/media/mckinsey/featured%20insights/artificial%20intelligence/notes%20from%20the%20ai%20frontier%20applications%20and%20value%20of%20deep%20learning/notes-from-the-ai-frontier-insights-from-hundreds-of-use-cases-discussion-paper.ashx
**https://www.mckinsey.com/industries/retail/our-insights/grocers-can-fuel-growth-with-advanced-analytics
+ https://hbr.org/2018/01/ads-that-dont-overstep?autocomplete=true
++ https://aimagazine.com/articles/visual-search-engines-the-role-of-ai-and-machine-vision

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