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They’re only human: Big data made simple

Girl with a bar code on her neck, the protection personal dataBig data has become one of the big buzzwords of retail in 2017. But many retailers remain confused by what it means and how to use it.

Cue a team from Scotland who just three years ago founded a startup called Big Data For Humans.

They weren’t your typical team of ‘tech guys’ but by a group of highly experienced retailers with decades of shop floor customer experience under their belts. Their mission: harness the power of big data to bring an unprecedented depth of insight into customers – not just as lines on a spreadsheet but as groups of ‘humans’ with unique tastes, needs and spending habits.

“It’s one of those ideas that didn’t come to us overnight. It came to us gradually,” recalls co-founder and CEO Peter Ellen. “I was a retailer for about 20 years as a founder, and latterly as CEO, of a retailer in the UK which grew pretty quickly throughout the 1990s. One of the key rationales there was that we were really customer focused – we knew which customers delivered the most sales and we analysed carefully how we could use those relationships to drive growth in the business.”

In 2005 Ellen co-founded a business called Maxymiser, a cloud-based software solution that tests, targets and personalises what customers see on a web page or a mobile app, substantially increasing engagement and revenue. It was ultimately sold to Oracle in the US.

“We dealt with digital marketers as well as general marketers. What became very clear was that very, very few of those digital marketers actually knew who their customers were and some couldn’t even tell you what a customer was. One of them said ‘Is that like a non-unique visitor?’ And I said, no that’s like a human,” Ellen recalls.

“The dictionary definition of a customer is someone with whom you transact. The culture being created around digital marketing is such that people are starting to categorise anyone as a customer… Someone who rocks up to your digital store or anywhere else, rather than someone who actually buys something.”


Lurkers vs spenders

“When I was a retailer it was very important to differentiate between the people who hung around your store and the people who actually spent serious cash. Online, I think, that problem is magnified many, many times over. And with retailers facing increasing costs of acquisition online, under constant pressure of dealing with occupancy costs offline, and with all the other marketing costs they’re surrounded with in multichannel, it is economically critical that retailers build relationships with the customers they have. Those people deliver 80 per cent of your profits and if you leave that process to chance – or leave them to an email marketer to knock out a couple of emails here and there on a random basis – you’re probably missing out on the biggest profit and revenue opportunity your retail business has.”

Ellen is constantly amazed how many retailers have no idea who their customers are. “They guess who their customers are or they use technology invented in a bygone era to do the job.”

The problem identified, the solution was already there. Or was it? The technology required to measure and monitor customer behaviour meaningfully is very technical. Analysts use complex tools to understand it, then there is an uneasy transition to transfer that information in a usable format to the people running the marketing and managing actual stores.

“We realised retailers fell into two groups: One was retailers who didn’t bother doing anything with their customer data because it seemed like too nasty or scary a project to attack because of the technical challenges and the cost. Then there was a second group who had invested vast sums of money into customer analytics and employed analytics teams but often the rate at which they were able to get the insights into the hands of people who actually wanted to do something with it was really slow.

“And the cost associated with that process was really high. So it was almost easier for retailers to go on ignoring their customers and carry on acquiring them over and over many times with different methods and losing money in the process.

“So we thought: that’s not right. It’s economically unsustainable. We watched some businesses growing and growing through omnichannel where the costs got higher and higher the bigger they got. And their profit shrank as their sales grew. We thought: It’s time to do something about that. If we can simplify the process in a smart way, we could help a lot of retailers around the world.”

That’s how Big Data for Humans thus became the first company in the market to develop an automated customer insights platform which has transformed the way retailers understand their customers and sell to them, helping deliver deeper understanding of customers, more effective marketing, increased customer value and thus higher revenue. At its heart is the ‘Customer Graph’, which empowers business users at all levels to use automated customer insights to power their marketing.

“We realised that one of the best ways to understand people in the modern world is through networks and that’s how we understand our place in social [media] and professional networks as well. So why don’t we do something similar to understand customers in the retail business?”

Overcoming barriers

“We found there were barriers to achieving that goal. Most of them around the fact using graphs is a more complex and technically difficult thing to do for an analyst but we realised if we could automate the process, and do it well, we could produce incredibly powerful insights that anyone in the marketing team could pick up and run with. We spent about a year on the basics of that before we launched the company and since then we’ve been growing in Europe and Asia very fast and getting some amazing results.”

Since opening a Singapore office last October, the company has signed up Philippine Seven Corporation – the local operator of the 7-Eleven convenience store network – adding the brand to an international list already including AirAsia, Tesco, Selfridges and Jelmoli.

“We are new to the region, but we have been talking to businesses in Thailand, Malaysia, Singapore and the Philippines. Hong Kong is definitely one of our next steps and we are speaking to some great businesses there.”

Big Data for Humans works within retail sectors ranging from convenience stores to luxury and in size from small businesses to multinationals. The concept is easily scaled to fit different sized companies.

“The smallest retailer we deal with would have tens of thousands of customer records, whereas the largest might have 60 million.” Data sources the company starts with range from loyalty-scheme information, or data collected from e-commerce receipts. “You generally find a retailer has some degree of data coverage.”

The business hosts workshops in Europe and Asia in a bid to ‘demystify’ big data, the most recent held in Kuala Lumpur in May. During the two-hour sessions, retailers are challenged to rank their needs for information using a ‘playbook’. The retailers rank goals in order of priority, such as upselling, cross-selling, retention and win-back. They then drill down into subcategories like (within retention) seasonality prediction, implementing a VIP program, improving the conversion from first to second order and enhancing customer sentiment during the purchase process. There is no hard-sell at these seminars – rather they help retailers understand where their business is at and how using their own data can make a difference.

For example, Tesco used data to cross-sell customers making weekly shops for shelf-stable foods into more regular shoppers buying fresh foods where the margins are higher. “Obviously they were buying fresh food, they just weren’t buying it from Tesco,” explained Ian Webster, chief customer officer at the Kuala Lumpur workshop. Using big data to drive a tailored marketing campaign, Tesco converted 15 per cent of ‘family supplier” shoppers into fresh food shoppers.



“In analytics there is something called a train-of-thought analysis where you sit an analyst down in front of data and everyone says: well that’s amazing – but what are we going to do now?,” explains Ellen.

“Often they come up with interesting things that nobody can use. So in our software and our playbook we take a highly prescriptive approach to how you turn the data results you have in your business into money. Because that’s really all we are interested in. We guide people down that path and our software looks at what is the most important data you need in retail – we believe that’s mainly around people, products and money. And then we guide them through that process so that the output tells them who the customers are, what they want, what they might want in the future, how much they are worth, how often they shop, where they shop and all the main things they need.

“And then through our methodology we help them plan a customer marketing program across their business and channels that should deliver an increase in annual revenue.

“Big data provides a massive competitive edge because now retailers can actually plan their customer marketing communications and strategy in their overall business rather than in one channel. A lot of marketing is done in channel now where the company says: ‘I might send them an email on a Monday, an SMS on a Tuesday and a flyer on a Wednesday’, whereas our solution enables our clients to see what the opportunities are within the retailer’s customer base and how they can sell more.”

Once they’ve worked that out, explains Ellen, they can calculate which channels are the best to contact the customer groups. It might mean direct relationships in the luxury sector, or reaching out by emailing special offers in high-volume businesses.”

After only a matter of months in Asia, Ellen and his team are already seeing differences compared with European retailers.

“Because Asian retailers often have experience running multiple locations and brands across multiple [territories], a lot have developed large databases for cross-brand marketing activities.”

Big data is clearly in retailers’ lives to stay – and Ellen argues there is a need to understand it and make the most of it if retailers are to build a competitive edge – and more importantly optimise their sales.

“It comes down to the economics of how you’re going to get more revenue from your customers. Retail is all about selling more to the customers you have.”

“Embrace data,” adds chief marketing officer for Asia, Helen Wasserman. “You have to embrace it.”

And study your customer life cycles, adds Webster. “A retailer might have customers who shop every week, every month or every five years. Treating those customers the same is not a good idea. If someone buys from you every three years and you don’t see them for a month, that’s not an issue. But if you normally see a customer every week and you don’t see them for a month, you should be worried.”

This story first appeared on sister site, Inside Retail Asia.

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