Retail AI - Friend or Fiend

Much has been written about artificial intelligence (AI) ranging from warfare robotics to smart home systems. There has been an increasing concern that developing AI without some form of control, even by Governments, could lead to a proliferation of systems and equipment that can be used aggressively and/or improperly against the individual or even the country's infrastructure. The general public, therefore, often believe that AI will not only take over jobs but also our confidential data and even our lives.

Perhaps it was in 1914 the Spanish engineer Leonardo Torres y Quevedo demonstrated the first chess-playing machine, capable of king and rook against king endgames without any human intervention.? Or in 1925 when Houdina Radio Control released a radio-controlled, driverless car, travelling the streets of New York City.? However, I am more driven to believe that the real origin of AI was based upon Alan Turing’s?“Computing Machinery and Intelligence”?published in 1950, in which he proposed “the imitation game” which later became known as the “Turing Test.”

How many of us use an iPhone to “ask Siri” a question or use GPS in the car to find our various routes.? These are both examples of us using AI in practical applications today.? Another example are the various “bots” (why on earth are robots called bots?!) Anyway, these ?robots or internet robots, use a computer program that operates as an?agent?for a user or other program or to simulate a human activity. Bots are normally used to automate certain tasks, meaning that they can run without specific instructions from humans.? A typical example would be a chat box to be used as a help agent on a web site.? For those of you, like me, who find most of these typically frustrating and useless, this is because they have yet to be developed to full completion. ?

However, a rule-based chatbot interacts with a person by giving pre-defined prompts for that individual to select. Whereas an intellectually independent chatbot uses machine learning to learn from human inputs and scan for valuable keywords that can trigger an interaction.

As I have spent almost all of my career in the retail sector I will now focus on Retail AI which is an area of technology that certainly concerns all of us very directly. These various internet robots, such as those used on online shopping sites, will become more developed and prevalent and in time should certainly help both the shopper and the retailer as more and more data is collected and computed within various systems.

So are we to believe that internet robots are here to help the customer and the retailers and suppliers or are there evil ideas, thoughts and actions driving them?? A short answer is “yes” as there will always be people, companies and countries that use any means for evil intent. ? These “malicious bots” are used to automate some actions which we would term as “cybercrimes.”? We most commonly hear about “hackers” which distribute malware, attack websites and gather sensitive information, such as financial data.? These bots, created by hackers, can also open?backdoors, which accesses a computer system to install more serious malware and worms.? Furthermore, that are some “spambots” which post promotional content to drive traffic to a specific website, usually for criminal purposes.? There are also other types of malicious bots such as those that overloads a server's resources and prevents the service from operating, a major concern for a country’s infrastructure, such as the electricity grid, or defence systems.

There are, therefore, many areas of concern that would fall under my heading of “Fiend” but here I would prefer to focus on “Friend” as there are so many applications and solutions currently in operational use or in development, for the benefit of customers, retailers and suppliers.? Retail AI as a “Friend” is here now but how is it being deployed and for whose benefit?

When I talk to retailers in buying and merchandising departments, I find it interesting how many of them cannot answer this simple question.? “When you launch a new product or run a promotion, do you know the impact that this had on other products?”? The answer is usually that they just want to know if their new product or promotion was successful.? Anyway, they say, it is just too time consuming and complicated to look at all our other products to see the effect.? All we look at is the results of our particular area of concern.? This flaw in category management is not untypical as there now such vast volumes of data, including supplier, product, sales, profit and customer data to name just a few areas.? In addition, the merchandiser has to deal with, perhaps, hundreds of stores across a large region, each with their own demographics and sales patterns.? Category management allows procurement and supply professionals?to create opportunities that will drive value for the organisation,?such as?reduced?prices and costs, supply chain risks and timescales. In addition,?improved?service to customers, quality, brand, reputation through sustainable supply chains and compliance to regulation.? It also helps?organisations to help align their strategy to customer requirements?and?the supply market.

It is clear, therefore, that retailers will have to go through the headache of de-cluttering all the data from multiple sources into strategies that ultimately benefit the company. Dealing with such data and analysing it properly is a challenge for retailers. This is where Artificial Intelligence comes in.? By being able to address and overcome retail and CPG’s biggest challenges by harnessing the power of predictive and generative AI.? What are predictive and generative AI? Generative AI applications empower users with deep insights and productivity boosts to enhance workflows and decision making. Predictive AI is tuned for each retail submarket with the right supervised, semi-supervised, or unsupervised machine learning which is optimised to address specific user cases.? In essence, the key is to combine generative and predictive AI, which will enable quick, accurate responses while maintaining data privacy and access through a natural language interface.

Taking out some of this technical jargon, developing Retail AI through machine learning will enable retailers to meet shoppers’ requirements in real time visibility, delving into complex insights and recommendations by marketing as well as improving forecasting, collaboration across the supply chain.? All of these benefits fall within the realm of omnichannel retailing where having this deep Customer Insight, together with all the product, location and sales data, will enable effective Category Planning.? Retailers are in business to generate profit and in essence, this is achieved by providing products the customer will buy at the right price generating profit whilst, at the same time, controlling costs.? As well as helping to generate sales by effective category planning, retailers can reduce costs, as well as improving the customer experience, by exploring the power of? combining cloud-based analytics,?machine learning?and?artificial intelligence. Granular insights allow retailers to create innovative solutions, transforming both costs and customer experiences.

AI?can also help customers to locate the right products online, despite vague search terms or inaccurate “fuzzy logic” spelling. This helps create a better experience whilst, at the same time, reducing the billions lost to abandoned baskets every year is a major concern for retailers.

Launching and progressing AI within a business does not come without its challenges: getting buy-in from senior management (who often do not have a technology or data background), choosing the right partners and finding staff with the appropriate skill sets, can all present significant hurdles.? None of this is helped by the hype surrounding AI. On the one hand, there is confusion caused by the fact that AI is an umbrella term for multiple technologies; such as natural language processing, machine learning and computer vision.?On the other hand, there is a lack of data on the return on investment in AI, which can make it difficult to progress. In an industry where management are under pressure to deliver returns on short timescales, designing and getting buy into investment in AI can be very difficult.? Of course there are the “leaders and laggers” in retail as in any industry.? We can all remember the “first mover” of Tesco’s Clubcard and the effect that this has had on customer loyalty over the years.? We can already see some “leaders” taking advantage of solutions and support from leading Retail AI suppliers.? As an independent retail industry advisor, I do get asked which supplier to use.? Of course it really depends on the particular area of business concern that needs to be addressed and the commitment of senior management.? There are several really innovative Retail AI suppliers, for example, SymphonyAI has even re-branded the company name to include Retail CPG which shows their commitment to our market sector, particularly grocery, convenience stores and DIY as examples.

In conclusion, AI for retailers can mean exceptional customer service, revenue growth potential, technology growth and smart processes which enables the retailer to stand out from their competition. Retailers who want to stay ahead of the competition should delve into artificial intelligence in the retail industry and read about some of the retailers who are already benefitting from such technology.?