Chief Marketing Officer Symphony RetailAI
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Marketing and the tyranny of choice

13th Dec 2019
Chief Marketing Officer Symphony RetailAI
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A staggering 87% of retail purchases are made online, and even the tech-resistant over 65s do half their shopping on the internet. There is no denying it, enticing people into stores requires some serious thought – and psychology.

Retailers need to continuously up their game to provide customers with an in-store experience that is convenient at least and pleasurable at best. How can they do that? By understanding the psychology of shopping, a science in its own right. From store layout to analysing how consumers make their decisions, and why they don’t make them, a lot of thought needs to go into store design and assortment. But retailers don’t have to go at it alone – both behavioural science and technology have come a long way.

Pulling on the heart strings

According to consultant practitioner psychologist Ingrid Collins, there are a plethora of factors influencing how we make decisions, ranging from price, whether we are hungry, a specific need (e.g. toothpaste or batteries) to how useful something is. Emotions also play a significant role in our shopping behaviour – someone who has just been dumped by their partner or who’s had a hard day at work, for example, may compensate themselves with new clothes or a good bottle of red. Marketers have long understood that appealing to a shopper’s emotional need to be cared for is an effective way to shift products.

The ‘Because you’re worth it’ tagline by a well-known cosmetics brand is a great example of associating a product with self-value. ‘We are not only purchasing the item, but also a sense of satisfaction and security’, says Ingrid.

Being emotionally attached to certain brands undoubtedly encourages shoppers to repeatedly buy the same item. Staying with a familiar product is comfortable and reassuring, as we know we derived pleasure from it in the past. When no such attachment exists, however, things become more difficult. Faced with a wide range of almost identical products, shoppers can find the decision making so daunting that they simply abandon the purchase altogether.

On average, a person makes about 35,000 decisions every day, equalling one decision every two seconds. That is a lot of deciding! Sometimes a shopper will feel that making yet another choice when picking up breakfast, especially when confronted with 25 different cereal boxes, is simply too much. “People become overwhelmed in the face of too much choice and feel that to choose one thing is by definition to reject so many others”, explains Ingrid. “When retailers offer an assortment with little difference between the products in the same category, they may find that they all stay on the shelf.”

AI and behaviour

This is where the “Rule of 17” comes in. Studies have shown that customers can cope with a choice between five to nine items. Combining this psychological reality with the work of assortment planning, it becomes clear why too many similar products in a category are a reason for less-than-stellar sales performance. According to our own research, 17% of items in any one category are duplicates. Keeping this in mind, category managers need to decide which product/brand has to be eliminated from a particular category to offer a digestible amount of products to customers. Doing so is no easy feat! Eliminating the wrong 17% can have serious consequences as Walmart had to learn in 2009. The retail giant cut 15% of its inventory, resulting in a decline of sales for seven consecutive quarters as shoppers took their business elsewhere. So how do you decide what needs to go?

AI can help by learning from sales and category data over time, enabling retailers to understand shoppers behaviour/signals – where they shop, why they shop, when they buy, when they don't buy, if something's out of stock what else they buy, if something is promoted what they don't buy, and how price affects behaviour. AI identifies the signal and relates it to the actual purchases, the demand. Over time, the machine can predict what would happen if a different set of conditions was given to the customer - if a store promoted differently, had different display case scenarios, or a different assortment. Because of AI’s ability to operate at a granular level, it can understand characteristics (eg is this diabetic-friendly?) and whether these attributes contribute to demand and align with customer expectations? AI is working hard to understand cause and effect – something Behavioural Scientists have done for a very long time.

Know thy customer

Using behavioural science to persuade and influence shoppers into buying things they never intended to buy or need has been a topic hotly debated for a long time. There are countless articles written about how supermarkets ‘trick’ unsuspecting customers to spend spend spend. While, yes of course, like any business, retailers need to make a profit, but they are also making a huge effort to get to know their customers and offer products that they genuinely want. Catering to the demand is likely to lead to a satisfactory outcome – for the customers, as much as for the balance sheets.

 

 

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