Beyond Analysis: Big data touchpaper Dec 2012


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Beyond Analysis: Big data touchpaper Dec 2012

  1. 1. Big DataPutting you back in control of yourcustomer relationships
  2. 2. ContentAre you a Big Data believer? Page 3Data, data everywhere Page 3New data sources are appearing all the time Page 5So, where to start? Page 6Short term rewards reap long term gain Page 7Where to begin your Big Data journey? Page 7To data infinity … and beyond Page 8About Paul Hinds Page 9
  3. 3. Are you a Big Data believer? Do you remember when CRM was the next big thing? It was supposed to deliver ultimate customer engagement. In reality, it was all about software; and very expensive software at that. Sure, these expensive CRM software solutions did deliver a certain amount of segmentation, but they generally did not get to the heart of the issue – that the data itself was generally not very good in terms of quality. So what about Big Data? Is it the new CRM; the next Dot-com; the big brother of Web 2.0? If Google search data is anything to go by, maybe not:What the Big Data debate has done is ensured that Some organisations have been doing this for years,data itself has caught up with the aspiration of what but Big Data is all about doing it better and usingbusinesses would like to do with it. Technology is data to positively impact the truly an enabler to achieve this, both in the‘back office’ environment (which is increasingly in Data, data everywherethe Cloud) and direct customer touchpoints, such asmobile Apps. We are closer than ever to having truly The key challenges are the explosion of data andpersonalised customer engagement and how to collect it. The rapid emergence of newrelationships. payment methods, such as mobile wallets, together with digital technologies, have revolutionised aBig Data, however, is nothing new. It’s simply about business’s relationship with its customers. Longjoining the dots of all the relevant data sources. gone are the days when loyalty cards were the onlyWhether it is customer data, local market data or way to identify and collect customer data.communications data, every company out there has Increasingly retailers are using their online customerat least one data source at its fingertips. base as the equivalent of a loyalty scheme – they’re Page 3
  4. 4. using the same data and channels without the need huge increase in direct customer interaction andto maintain a separate currency for loyalty. feedback. For those who have been slow to embrace the brave new online world, the rise inToday, with multiple ways to identify a customer social networks has been a rude awakening. Manyacross a growing number of channels, it’s all about are now being forced to re-think their onlineBig Data; multiple data sources – both internal and strategies.external – being brought together to put thecustomer at the heart of business strategy. Amazon is something of a poster child for Big Data. They have, in essence, a very simple data model.Businesses everywhere are under pressure to better They don’t have stores and they don’t have a loyaltyunderstand, engage with and respond to their scheme per-se. Their version of Big Data uses thecustomers. This requires data, and lots of it. The huge volumes of customer and payment data thatgood news is that there is so much wonderful they have at their fingertips to personalise the onlinebehavioural data out there, ready and waiting to be shopping experience and offer products that areput to good use. The bad news is that although the related to what their data tells them about theopportunities for harnessing this data are pretty lifestyles and preferences of their customers.much infinite, the issues are also increasinglycomplex; particularly as the journey from need or Along with ebay they have set the standard fordesire through to purchase becomes less providing a forum for sharing customer feedback onpredictable than ever before. Analysing your data products (and now partner retailers) and measuringand quickly acting on the resulting insight is, customer satisfaction.therefore, crucial. Just knowing what a customerbought, whether a product or a service, is no longer They grow their data asset still further by promptingenough; businesses need to understand long term customers to share more information and confirmconsumer behaviour, what customers are doing the intelligent assumptions that they make based onbefore or after they make their purchase, and what statistical models. Just glancing at my one ‘Amazontheir interests and aspirations are. Betterizer’ page shows how well they know me from mining their version of Big Data - they know I am aDigital channels have added a whole new dimension parent, where I have been on holiday and targetto the data debate, with new streams of ‘live’ data incremental spend by offering further categories forcoming direct to a company from their customers. me to shop in:The advent of social media in particular has led to a Page 4
  5. 5. New data sources are appearing all the time SpendographicsTM which we’ve developed in partnership with Visa Europe, helps businesses toIn addition to all the data now being generated understand their customers on the basis that ‘theythrough digital touchpoints, new commercial data are what, where, when and how they spend’ – asources are also available which bring a third monumental departure from the traditional and,dimension to customer insight. Previously, some would say, outdated geo-demographic profilesbusinesses have been able to use their data to see generally used to drive customer segmentations.which customers are shopping through their storesand channels, and which of their products they are This new segmentation tool improves the resolutionbuying. at which consumer behaviour can be analysed and works at a market, brand and sector level.A recurring challenge is how to accurately determine Individuals are grouped into 10 different “spenderwhat their customers are doing when they’re not modes”, which comprise people with similarshopping with them. Which of their competitors are characteristics and behaviours who can bealso on their shopping list? How frequently and how communicated with in a consistent and targetedmuch are they spending with other brands? What manner. The segments have been given a name,does this behaviour say about their customers in tagline and pen portrait to help understand theirterms of preferences, lifestage, purchasing power spend behaviour and how to engage with them. Thisand brand loyalty? insight can be used to improve business performance at both strategic and tactical level. URBAN SPENDERS WORK HARD, PLAY HARDER CARD USE: 5 TIMES A WEEK SPEND BEHAVIOUR SALES METRICS CARD TYPE ATV £26 CREDIT 3% AV. AV. 97% ANNUAL SPC £6,908 DEBIT AV. AV. INT’L SPEND 2% AV. COMMERCIAL 1% AV. POS CHANNELS 64% 26% 10% 59%AV. 22%AV. 19%AV. 3% 4% CARDS - 1.9M OF 68M SPEND - £12.8B OF £335B FACE TO FACE ONLINE MAIL / TELE ORDER Urban spenders are very active, using their card a large amount (especially in the SHOPPING HABITS TOP THREE SECTORS BY SPEND afternoon/evening) for both cash withdrawals and card transactions across a wide range of merchants. Being commuter-types, they spend a significant proportion of their 8%AV. 18%AV. 3%AV. budget on TFL and rail tickets. Their social agenda is packed and these spenders often frequent bars, restaurants and clothes shops. They enjoy a high quality of life and are therefore likely to go to a gym or health-club and although they spend less than others in supermarkets (possibly because they like to eat out), when they do they will visit the high-end grocers. They are also active online and use their cards with online retailers ENTERTAINMENT SUPERMARKET TRANSPORT and budget airlines. 15% 14% 14% LIFESTYLE INDICATORS TOP THREE SECTORS DIFFERENTIALS MORE LIKELY TO... LESS LIKELY TO... COMPARED TO THE UK TOTAL, THESE CARDHOLDERS ARE MORE LIKELY TO SPEND MORE IN THE AREAS // WHERE CAN YOU FIND THEM BUDGET HOME SOCIAL YOUTH MATURE 8% 6% 3% IMPROVEMENTS ORIENTED MARKET 15% 8% 14% ENTERTAINMENT CLOTHING TRANSPORT 24* 8* 6* HAVE A CAR HAVE A PET HAVE KIDS GYM MEMBERSHIP CITY SPENDERS * NUMBER OF DIFFERENT BRANDS WITHIN THIS SECTOR SPEND BEHAVIOUR SHOPPING HABITS SALES METRICS CARD TYPE 8%AV. 18%AV. 3%AV. ATV £26 CREDIT 3% AV. AV. 97% ANNUAL SPC £6,908 DEBIT AV. AV. INT’L SPEND 2% ENTERTAINMENT SUPERMARKET TRANSPORT AV. COMMERCIAL 1% 15% 14% 14% AV. Page 5
  6. 6. Collecting, interpreting and acting effectively on your So, where to start?customer data can be a real differentiator in termsof developing positive customer relationships and It’s not as hard as some are making out to make Bigloyalty. It can provide the best possible competitive Data deliver a quick return for your business. Theadvantage; it is your chance to make sure that you mistake many companies make is trying to bring allput their needs at the heart of your decisions around of it together, all at once.product, price, place, promotion and people (yes,that old marketing classic). Take the time to understand what your version of Big Data needs to look like for your company and your customers; then pick one area of focus and put your energy and resources into that.From this... PRODUCT DATA www. Brand Style type Home etc. Purchases Reviews Searches Warehouse Store COMMUNICATIONS LOCAL MARKET DATA AND PROMOTIONS Geography housing Online Customer behaviour types competitors Financial Sales Customers Customer Care CUSTOMER DATA www. Voice of the Payment Cards Basket and trolley PRODUCT DATA Customer data overtime Brand Style type Home etc. Purchases Reviews Searches Service and product. Feedback and opinions Feedback, reviews price comparison Focus group Loyalty Cards E-mail, Address, NameTo this... Warehouse LOCAL MARKET DATA Geography housing Store COMMUNICATIONS AND PROMOTIONS Online Customer behaviour types competitors PRODUCT DATA www. Brand Style type Understand what your version of Home etc. Financial Sales Purchases Reviews Searches Customers Big Data needs to look like for your Warehouse LOCAL MARKET DATA Geography housing Store COMMUNICATIONS AND PROMOTIONS Online Customer behaviour business and your customers. types competitors Customer Care Financial Sales Voice of the CUSTOMER DATA Payment Cards Customer Customers Basket and trolley data overtime Customer Care Voice of the CUSTOMER DATA Payment Cards Basket and trolley Service and product. Customer data overtime Feedback and opinions Focus group Loyalty Cards Feedback, reviews Service and product. Feedback and opinions E-mail, Address, Name Feedback, reviews price comparison price comparison Focus group Loyalty Cards E-mail, Address, Name Page 6
  7. 7. Short term rewards reap long term gain These offers were delivered to customers in 32 different campaigns over 8 weeks.Although true customer loyalty is about long termretention and engagement, in today’s challenging The results have been astonishing: an overalleconomic environment retailers need to act fast to redemption rate of 13% across all campaigns, withentice new customers and win back the lapsed. some cells getting as high as 54%. We won back 3%Customers are less and less likely to wait around for of customer who had not visited a store for 6their reward; they want instant recognition and months. And we identified the categories with thegratification. The trick for retailers is to deliver this best opportunity for retention.loyalty kick without devaluing their brand offering.We all know of high profile retailers that are all about Interestingly, new media channels were a keydiscounts and vouchers; savvy customers will rarely component part of the success of these campaigns,buy from them at full price when you can search including the use of optimised barcodes for for a 20% off code. And it doesn’t end there; the results of these data-led tests have formed the foundation for theFor example, Beyond Analysis is working with a business case to apply the benefits of insight to allleading South African retailer to use their loyalty areas of the business, from promotions to storescheme differently in order to: merchandising.- Drive more spend and visits from their top This is the power of data in action. shoppers- Win back dormant and lapsed customers, and Where to begin your Big Data journey?- Ensure customer retention in key categories and locationsWe used customer behavioural data to constructcampaigns which were both relevant to customersand met the client’s strategic objectives. Using 12months’ worth of data, we undertook a customerbehaviour analysis, identified core target segmentsand built tailored offers to meet their needs. Here’s the Beyond Analysis 6 point plan for getting started: 1. Be clear on your business objectives, and those of your customers 2. Understand what data you have right now (and what you don’t) 3. Align 1 & 2 and then create your own Big Data plan 4. This should NOT be a 3 year, all-singing all-dancing plan; plan in detail for the first 12 months, then in high level for years 2 and 3 5. Only include actions that can be tested and measured – so you can learn and develop proof points 6. Be committed to your data; if you’re in it for the long haul, so will be your customers Page 7
  8. 8. To data infinity … and beyondThe future is about intelligent customerengagement. It’s about marketing to and engagingwith the individual. To achieve that, we need toknow what customers think, and to understand whatthey do and why. In order to know all that, we needto listen.In today’s challenging and competitive economicclimate, we must reassess whose views matter. Ouremployees, partners and customers could just bethe best people to tell us how to make our businesssucceed.Do it right and do it consistently, and loyalty andengagement will be the happy result. Page 8
  9. 9. About Paul HindsSince graduation Paul has spent the majority of hisprofessional life working in data insight consultancyand customer strategy.His core skills centre upon strategy development,programme design and stakeholder engagementwith the focus on delivering actionable insight thatmake a tangible difference to the organisations withwhich he works.Paul is passionate about ensuring Beyond Analysisdoes everything possible to enhance clientunderstanding of their customers and maximise thevalue of their data asset to provide relevantinformation that has a meaningful commercialimpact.In his spare time Paul can be found persuading his 3year old son Lucas that Liverpool FC are the team heshould be supporting and serving charred meat atfamily barbeques, whatever the weather. Page 9
  10. 10. AuthorPaul HindsE-mailpaul.hinds@beyondanalysis.netLondon office0208 875 7099Please contact Paul Hinds for further information about the paper and for enquiries regarding how BeyondAnalysis can help your business.About Beyond AnalysisBeyond Analysis is a leading customer insight and strategy business. We believe that the customer should be at the heart of everything we and our clients do. And we’re passionate about using the power of data to achieve this: finding it; collating it; interpreting it; unlocking its value. We work with some of the world’s largest consumer brands to harness the power of their data and adopt a customer-led approach to their decision making. We bring together multiple data sources to interpret consumer trends and give our clients a clear line of sight to help them grow their business. We have offices in London, Sydney, Singapore and Denver. Beyond Analysis Limited. Registered Office: Unit 10 - 12, 116 Putney Bridge Road, London SW15 2NQ Registered in England. RGN: 06059028 T: +44 (0)20 8875 7020 W: F: +44 (0)20 8875 7099 Page 10
  11. 11. Beyond Analysis 2012Thought leadership series