page 1
page 2
page 3
page 4
page 5
page 6
page 7
page 8
page 9
page 10
page 11
page 12
page 13
page 14
page 15
page 16
page 17
page 18
page 19
page 20
page 21
page 22
page 23
page 24
page 25
page 26
page 27
page 28
page 29
page 30
page 31
page 32
page 33
page 34
page 35
page 36
page 37
page 38
page 39
page 40
page 41
page 42
page 43
page 44
page 45
page 46
page 47
page 48
page 49
page 50
page 51
page 52
page 53
page 54
page 55
page 56
page 57
page 58
page 59
page 60
page 61
page 62
page 63
page 64
page 65
page 66
page 67
page 68
page 69
page 70
page 71
page 72
page 73
page 74
page 75
page 76
page 77
page 78
page 79
page 80

12 This customer data is real. It's honest and it can sometimes be brutal. When asked in a focus group a customer may say they like a new nutty cereal bar, or the widgets in the latest BMW, but that doesn't mean they will buy these products. It's a reflection of real life. It's not like BARB, the British TV viewing data analysts, where 5,000 households have to press a button before they turn TV channels. It's not like UK grocery panels, where 20,000 homes have to scan all their shopping when they get home. Or the US leading consumer panel where 60,000 households record all their purchases when they get home after a shop. Every retailer knows what they sold, but transactional customer data delves deeper. It also knows who these shoppers are. If a brand wants to know if a product launch has been successful, this data can reveal which shoppers are buying a new product again and again. This helps to distinguish between sales based on trial and sales based on repeat purchase - crucial information. Reality can be rather ugly. Transactional data will clearly tell a business, ' No they didn't buy that new product again.' So the customer didn't like it. Edwina says customer data, " has an honesty and an immediacy that historically marketing hasn't had." However, attitudinal research can still play a role today's world, especially if it's linked back to purchasing data. dunnhumby has a panel of 65,000 Tesco shoppers known as ' Shopper Thoughts' who can swiftly respond to online surveys, to tell Tesco in more detail what they want and to help dunnhumby better understand their behaviour. Crucially, Shopper Thoughts enables dunnhumby to talk to someone who bought Marmite yesterday, for example. Its ability to serve up the right respondent in a timely fashion is vastly different to most research, which is based on claimed rather than actual behaviour. Why is it good for customers? Fast forward to today's shopper's experience in a customer-focused organisation like Casino, Tesco or Kroger. It's a world where customers are rewarded for loyalty, where retailers shape their offerings according to demand, and where customers are sent targeted, relevant messages rather than junk mail. any colour you like as long as it's any colour you like

13 monochrome world Indeed, our ability to analyse customer data to the nth degree, to interpret it this way and that, enables huge, global retailers to reclaim a little piece of old- fashioned retailing. It takes us back to the time when the owner of the local store knew his customers and their shopping habits in intricate detail. This is something Clive calls ' mass intimacy.' Well- analysed customer data empowers retailers with the necessary insights to treat millions of different customers as individuals. It makes big business feel more personal. After all, there is no such thing as an average customer. Online retailers like Amazon have been educating customers about what good personalisation might look like for a number of years. When Amazon gets it right, it recommends relevant new products to its customers and makes the online buying experience as painless as possible. However, Amazon works from a small number of data points and sometimes falls into the trap of extrapolating too much from limited information, leading to a bizarre recommendation based on a single gift purchase. The beauty of analysing grocery data is the pure scale of the information to hand - hundreds of different data points from millions of grocery baskets on a weekly basis. Giles Pavey at dunnhumby is responsible for interpreting the raw facts and figures to draw meaning from the 4bn pieces of data from Tesco shopping baskets we analyse every week. He believes that our biggest success is: " helping a really big business feel more personal. How do you make something quite big and anonymous like a massive grocery chain more engaging? How do you make it feel personal without exclusively pandering to the 1% of Gold Card customers who might spend over £ 25,000 a year in a department store? How do you make it more personal for everybody?" Mick Yates, dunnhumby's Global Business Development Director, sees customer data as a way to reclaim some traditional marketing values. He recalls: " I grew up the old- fashioned way as a brand manager and I was taught that we were there to figure out how to give customers what they wanted. " People who see marketing as sales, who push stuff at customers, don't understand that marketing is about meeting customer needs. Our biggest achievement is adding some science to that and we are getting better and better results because customers are voting with their wallets." Well- analysed customer data empowers retailers with the necessary insight to treat millions of different customers as individuals