Boots Loyalty Program Case Study

One of the longest-running debates in marketing has centred on the value, or lack of it, that service businesses derive from their loyalty schemes.

Retailers in particular have proved shy of specifying the cost/benefit ratio of running what have proved to be extremely expensive promotional and incentive tools.

Another criticism levelled at loyalty schemes is that they appear more obsessed with signing up new people (and hence acquiring new data) than actually rewarding loyalty.

This cannot be said of the Boots Advantage Card scheme. With 15 million households having one in their wallet or purse, it's one of the UK's most popular loyalty cards. Cardholders benefit from a generous reward scheme, getting four points for every pound sterling they spend.

Yet earlier this year the retailer acknowledged it needed to rethink the rewards it offers, and decide which customers should receive them, as part of an overhaul of the Advantage Card scheme. The card is seen as vital to Boots' efforts to fend off competition from supermarkets' expansion into health and wellbeing products and services.

"Customers have a very high level of engagement with the card programme, especially women who see the points as providing a treat for themselves," says John Wallinger, planning director at Boots DM agency Craik Jones Watson Mitchell Voelkel. "But we recognised there was a great opportunity to get a customer to buy a wider breadth of goods from Boots than they might be buying elsewhere."

Potential to buy

Boots' quarterly coupon mailings to cardholders, sent with the co-operation of Boots suppliers, typically selected the retailer's highest value customers, missing the opportunity to grow spend from the majority of the customer base. This left millions of cardholders, many with a high potential for Boots, receiving very little communication from the health and beauty retailer.

A new way of selecting customers was called for. Early in September, Craik Jones and retail analytics company 5One began work creating a targeting system that could identify potential customer spend across categories, brands and individual products. The solution needed to identify a person's potential to buy brands and make the offer selections.

"The objective is to reward customers to keep them coming back into the store and also to get them to buy in areas where they aren't already buying," says Ian Scholey, senior analyst and associate director at 5One. "We needed to work out which products they have most affinity with and how much we have to incentivise them to continue shopping."

Two models were created, looking at each individual's past transactional history, and their future potential (see box). The first model, named Peer Group Comparisons, calculates affinity to a product, brand or even category, based on demographics, product purchasing and, critically, the identification of related products. "If a customer was spending heavily in skin care but not in makeup, this would tell us to incentivise them with vouchers for make-up," says Scholey.

A key feature of this model is to stop unnecessary incentivising, because of the cost to suppliers. "It's great to continue incentivising customers to keep them buying one product, but also to encourage them to purchase products they're not buying," Scholey adds. The Peer Group Comparisons model would identify so-called secondary products - those that could be bought in conjunction with a customer's regular products.

The Share of Wallet model identifies and scores customers who are not purchasing at their optimum level, based on two years of purchasing history. It looks at purchase history within various product categories, working out potential spend and comparing this with actual spend.

Used together, the models allow communications to be tailored for each customer. The system runs through the database to select customers according to pre-set criteria and the value of the incentive they are then sent is personalised based on the customer's model score.

The new targeting system sits on the desktops of Boots' analytics team based in Nottingham. A key benefit is the help Boots can give its many suppliers, all of whom have vastly different propositions. "We might have an objective for a supplier or for Boots itself to cross-sell within a brand or steal sales from another retailer," says Wallinger. "So we look at customers' current spend within product lines and work out, looking at other customers, the average they spend and the potential to grow. For instance, you might be buying x amount of product y, but we know the average customer is buying 10 times that."

The project partners delivered the models within two months. Boots says it's too early yet to quantify the results, but 5One has conducted analysis on previous campaigns that didn't use the model and has discovered uplifts of 30-35 per cent in response.

"We're putting a huge amount of investment behind the Advantage Card," Helen Jeremiah, head of customer insight at Boots Advantage Card, explains.

"The direct marketing element is about making the most of that investment for our customers and for Boots' business. The models are the core part of this, helping to make relevant offers to customers that benefit them and our suppliers."

CLEVER STUFF

The model build was done using a five per cent sample of Boots transactional data, refreshed every month, with a lengthy model and IT testing schedule applying it back to the Advantage Card database.

SAS software was used to develop the models, combining various statistical techniques, including regression. For the Peer Group Comparisons model, 5One used the Yule's Q statistical technique to deliver accuracy.

"Yule's Q is a statistical measure of sequential association which says how well products relate to each other so that, for instance, two competing brands of skincare will be shown to have a weak relationship," says Ian Scholey, senior analyst and associate director at retail analyst 5One.

The share of wallet model looked at two years of purchase history within the various product categories stocked at Boots, to see if customers were spending to their full potential. "Every customer's share of wallet and therefore potential spend was calculated - how much are they spending now compared with in the past," says Scholey.

The result is a set of parameters for every product line and mailing, in terms of objectives and volumes of mail. The system is driven by SQL which runs through the database to select customers who fulfil the parameters and selects them for mailing.

With over 2,500 stores across the UK, Boots is one of the country’s most popular chain of drug stores. However, unlike some other retailers with a strong physical footprint and a history that relied upon footfall for sales, Boots has managed to keep pace with the rapid developments in online purchasing and was also an early adopter in using data to harness customer loyalty, via the Boots Advantage Card.

Ruth Spencer, the company’s director of digital and loyalty, has been with the company for six years, where she started in the customer insights team, and in 2010 was also put in charge of Boots.com.

Speaking at a recent British Retail Consortium event, Spencer said:

People were saying ‘you’ve put the insights woman in charge of the website, why have you done that?’. It’s interesting how fast things change, with the degree of personalisation on the web and omni-channel, people are now saying it makes perfect sense.

The Boots Advantage Card, the company’s hugely successful loyalty scheme, forms a key part of Spencer’s plan to combine digital, data and loyalty, where the points are earned and the offers are received wherever the customer shops – whether it is online or in store.

However, the complexities around designing a loyalty card system that works for your business are also completely unique to each business, Spencer warns. You can’t just design based on a system that’s out there or one that’s gone before – so forget going to your enterprise software provider and asking them to provide you with one off the shelf…

The Boots advantage card has been designed from the start so that it drives both loyalty, but absolutely recognises the enormous insight asset that it also provides us. When we developed the scheme we developed those two in parallel.

If you don’t think carefully about who you do the design for, how you operate and keep developing the scheme, you inadvertently end up with either one or the other, or neither. Don’t accidentally end up somewhere where you don’t want to be.

And don’t be stupid.

So how do you design it? People come up to me and say what can we lift from Advantage Card and where can we apply that somewhere else? That would be a really, really stupid thing to do. The design that’s right for your loyalty scheme has to be based on knowledge of your customers.

Understanding your customer isn’t easy

Spencer explained that she spent a good part of the early 2000’s as a management consultant, trying to help companies understand how their customers think by spending hours mapping customer journeys on large pieces of paper and post-it notes. This was at a time when customer experiences weren’t complicated by the increased use of mobile devices and the ease of access to speedy internet connections.

It’s becoming increasingly hard to predict how someone will shop. Customers no longer either purchase goods on a web browser at home, or go into a shop on the high street to get what they need. Now a customer may browse on a tablet on the way to work for goods, then do some research on their laptop when they get to the office, before going into a store to buy the product in person. Equally they may like to go into store to speak to a specialist before browsing online across a number of retailers to get the best price. The lines between physical and digital are blurred, as are the devices across which consumers are using to make their decisions.

What is important to customers now, according to Spencer, is creating a consistent experience across all platforms and environments.

It’s a bit academic these days to map those journeys, what you have to know is where are the key points and how do you show up to the customer for those key points. But the days of thinking that you could control which order anybody went through all those things is completely gone. But it puts an increasing emphasis on the fact that you have got to show up the same, everywhere. The opportunity that it’s given for us within customer insight, is that its given us a plethora of more places of where we can understand what’s going on with customers.

Here is an example of how Boots is adapting. It used to give every customer an offer based what they had in their basket during any single shopping trip. Spencer said that this was easy to do and just required a simple algorithm to analyse a shopper’s basket and then make a recommendation based on their goods at that time. Boots realised this wasn’t effective given that a shopper might need a quick purchase from its make-up counter one day and a different purchase from its pharmaceutical business the next.

Spencer believes that companies should be sensitive to how they use purchase data – given how annoying it is to be served an offer that relates to an arbitrary, one-off purchase you made five months ago. It can be perceived as an invasion of privacy, rather than a convenience.

You don’t want to annoy people and make them think that you don’t understand them and don’t know them. For us at Boots the concept of ‘average basket per customer’ is really, really unhelpful. You’ve got to be able to respond to somebody’s complete behaviour, rather than what they are doing in that transaction.

There are other retailers and industries where what you put in that one basket is a really good proxy for what you’re likely to do. I kind of envy those people because we could have saved a whole lot of heartache and IT work to make it happen, but in order to get what we needed for our scheme we needed something that was technically much harder to achieve.

We needed real-time calls going between tills and back-end databases, as well as prioritisation.

Retailers need to play single view catch up

Spencer believes that retailers have been given some leeway in getting to the point where they are able to establish a single view of a customer – rather than trying to match disparate silos of data from across the business when needed.

She said that this is particularly hard for a company like Boots, where it carries data that has additional privacy requirements within its drug store prescription business – consumers are particularly sensitive about their health data. Retailers need to create this single customer view, according to Spencer.

If you are in the banking sector you have had to work on your operational single customer view over the last ten years, because I expect when I log into my bank account that they can bring in all of my banking details from my mortgage, my current account and my credit card. Banks have had to go through this before we have as retailers.

Customer loyalty is progressing to a point that we need to make sure sure that we get that operational single customer view. It’s never going to be easy. It’s always going to be challenging. It’s particularly hard for us because we have got a pharmacy business, an opticians business, a retail business. The solution we are going to have to use is one that can manage both sensitive clinical data, as well as retail data.

However, she warns again that this single view needs to be used intelligently and without aggravating the customer out of purchasing goods.

How do we make sure that we are talking to customers in the right mode at the right time? If you are coming in to buy a lipstick, you don’t really want to be reminded that you have to go and pick up a script. You have to apply the intelligence and how you use it in the right way.

Be careful not to screw it up…

Do loyalty schemes drive insight or drive loyalty? The easy answer to get to is neither. If you set off without properly thinking or designing your scheme, that’s where you will get to. You can do both but it takes an awful lot of effort, but the rewards are that much great if you do.

My take

Boots has one of the most established loyalty schemes in the UK and is one of the leaders in the retail business in delivering personalised offers to its customers. However, Ruth Spencer’s presentation highlights that this isn’t an easy end result to get to and that the journey isn’t over.

The loyalty scheme requires a collection of data from a variety of streams – in store, online, through mobile, via feedback, location feeds, and who knows what else in the future. However, Boots’ success to date has been about understanding its diverse customer base and being sensitive to their needs – trying to deliver promotions and offers when its convenient for the customer and when they need them. If it sticks with this philosophy going forward, it could well also be a leader in next-generation loyalty schemes.

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