Ever since the financial crash of 2008, businesses around the world have struggled to grow at the same levels they once enjoyed – but big data and machine learning could help turn things around, and help companies reconnect with customers.
That's according to Waleed Ayoub, chief product officer at Rubikloud, a machine learning platform for retailers.
"The reality now is this plateaued, zero-growth type of world, where you're in the 0.5-1 per cent [range]," Ayoub said, speaking at WIRED Retail 2016. "That's very true for North America, very true for Europe and the UK. There's a lot of companies that do more small scale retail that are seeing enormous amounts of growth but in general, this is the kind of climate we're living in."
Ayoub isn't concerned so much with why this is happening, but rather how retailers are reacting to the change. One way businesses have tried to keep their costs down is by consolidating, then leveraging greater purchasing power to buy stock at lower prices.
"Big fish buy big fish, then bigger fish buy them," said Ayoub. "That allows them to pressure vendors to push down prices. That's really why they do this kind of thing."
Price has been the "main lever" businesses have traditionally had to pull to make buying more appealing, but consolidation also allows them to dominate customers' attentions, purely on the basis of having more locations than rivals. Even in an age of Amazon and Alibaba, physical presence remains important for retail, said Ayoub.
"[Retailers] set up e-commerce sites trying to make buying easier but that doesn't really help you address your sales problem that much," he explaind. "If you look at the sales percentages flowing through online versus brick and mortar, it's still orders of magnitude away from making impact."
However, the problem with constantly lowering prices is that it devalues a brand, something that can be impossible to recover from.
"We see this first hand, because we have so much data from product retail," Ayoub said. "A function of the shift in price [is] if you get someone in for the first time, to get them in the next time requires you to ramp it up a little bit. It's an unsustainable cycle, you'll never win. But what [retailers] were trying to do was to make buying easy, and that's essentially where we are now."
"If you're not making buying easy, and setting up platforms to do that, then you're doing something wrong, you're behind the curve," he added.
In the push for ease of access though, the art of selling has been lost. The knowledge of how to influence people or anticipate future needs, forecast demand to better stock shelves, or predict price changes has all but disappeared. As Ayoub put it, "retailers lost the way that they sold things."
That's where Rubikloud and its approach to machine learning comes in. The company uses the mountains of data a retailer generates and helps them apply it to restructuring their businesses, from distribution to direct sales. The process is tailored to each business, based on their individual needs and obstacles they face, to help them personalise their customers' experiences.
Such data is becoming as important a part of any retail business as stock and sales.
"Data is essentially going to be structured or leveraged to generate a return on investment. If retailers don't start thinking about data in that way, they're going to be stuck in the same kinds of cycles of doing things over and over again," Ayoub said. "Data is not about insights, it's about generating money."
"The opportunity is not necessarily to go back to basics, not the big data infrastructure, but the machine learning and the AI. It's 'how do I create curated one-to-one experiences for each and every customer?'", he added.
Rather than using the analysed data to optimise one of numerous stores - in terms of telling, say, Pepsi where best to place their product - Rubikloud's platform "optimises each and every person's individual journey through the next six to 24 months". An individual sales person can't handle the needs of millions of customers individually, but a machine can be trained to anticipate them, allowing businesses to plan accordingly.
"It's based on the premise of moving away from making buying really easy – we take that for granted – and start making selling the differentiator between you and a competitor," Ayoub says.
To those retailers who don't start realising the value of their business' data, Ayoub has a stark warning: "Data is now a revenue generating component of what you do. If you can't do that, you're in a position to fail in the next five to ten years."
This article was originally published by WIRED UK
