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The Trading  The Trading Intelligence Quarterly. Big eCommerce Data   Contents                                            ...
24-25Customer data and decisions:How the social data revolutiontransforms everythingAndreas Weigend, Professor, Stanford U...
The Trading Intelligence Quarterly. Big eCommerce Data• For individuals there are new opportunities to        Social data,...
The Trading Intelligence Quarterly. Big eCommerce Data                                              26-27b) Design to enco...
The Trading Intelligence Quarterly. Big eCommerce Data Rule #2: Become part of your customers’                 cards face ...
The Trading Intelligence Quarterly. Big eCommerce Data                                                   28-29 Rule #5: Le...
Amazon’s mastery of dataAmazon’s unique approach to data                        New algorithmscan be most fully understood...
The Trading Intelligence Quarterly. Big eCommerce Data                                               30-31Input driven tra...
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Customer data and decisions: How the social data revolution transforms everything


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Published journal in The Trading Intelligence Quarterly (issue 5)

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Customer data and decisions: How the social data revolution transforms everything

  1. 1. The Trading The Trading Intelligence Quarterly. Big eCommerce Data Contents • Making sense of online data 04-09Intelligence • Using data to deliver 10-14 online targets • Why most eCommerce 15-17 businesses stop growingQuarterly • The tyranny of averages 18-24 • Customer data and decisions: 25-29 How the social data revolution transforms everythingIssue 5 • Amazon’s mastery of data 30-31BigeCommercedataEverything you everwanted to knowabout turning datainto profit but wereafraid to ask.
  2. 2. 24-25Customer data and decisions:How the social data revolutiontransforms everythingAndreas Weigend, Professor, Stanford University & former Chief Scientist at AmazonHighlights• The explosion of social data has revolutionised retailing• For businesses, it is influencing everything from how they create and sell products to how they acquire and lose customers• For consumers, behaviour has radically changed: – Individuals are empowered as the co-creators of information – Purchasing decisions are being made differently• To participate in the revolution businesses should develop a customer-centric mindset as well as encouraging and embracing the use of social data in their business design and strategic decisions.Today’s customers freely share information onthe Internet about themselves and their friends What is social data?that even the KGB could not have extracted under Quite simply, social data is the information thattorture. This explosion in social data is the most people freely create and share online. There areimportant driver of innovation in the past ten years: two types of social data:people post their CVs on Linkedin; they answerquestions on Quora; they share their photos on 1. A social share: attributes about a person,Flickr; and they comment on their friends updates such as their geolocation or informationon Facebook. Similarly, unofficial information that they post, such as a status update or aabout a company, its products, its services and its review of a product.competitors is readily available on sites like Yelp,Jigsaw, Glassdoor and Vault. 2. The social graph: networks of interactions between individuals. Now, any FacebookThe availability of this information, and our desire app can ask to access the list of friends ofto contribute, permeates almost every aspect of a user. Beyond this friend network, socialour waking lives – from Googling someone before data includes tagging friends in photos,agreeing to a date to reviewing a film or updating recommending people on LinkedIn oryour Facebook status. following influencers on Twitter.This marks a transformation to the age of theindividual. It is no longer just official bodies andcorporations that have the power to ‘create’.Gone is the passive audience who once sat in receiptof a monologue of communications. Individuals arenow empowered as ‘creators’ on a mass level; theyare in charge of the conversation and it is
  3. 3. The Trading Intelligence Quarterly. Big eCommerce Data• For individuals there are new opportunities to Social data, on the other hand, is raw information express opinions , to get attention, to belong to created and shared by individuals expecting to ‘clubs’ and to collaborate with other people benefit from its socialisation, aggregation and• For businesses, the revolution means adopting analysis. For example, geolocation shared by a a customer-centric mentality, giving genuine woman via Google Latitude is social data, not attention to those who want it and offering a media, because she is hoping to find out if a friend social playground in which people can mingle, of hers is nearby, or if a local store is having a sale. converse and co-create. As a result, a company’s social data strategy will beThis article offers some practical suggestions for completely different from a social media strategy.brands and retailers grappling with the implications For years, companies have tried to push tiredof the social data revolution. marketing messages through new channels, viewing them just as additional entries in their marketingWhy do people share? mix. Social media strategies that try to find better,In this world of fragmented selves, where your cheaper, faster ways of drumming a message intoonline reputation may matter more than your people’s minds are doomed to fail given the plethoraoffline ‘real’ self, the individual needs to construct of alternate sources of information consumersan authentic social identity. We share our consider when making decisions.experiences and emotions to obtain that mostscarce of commodities – attention. We share to The foundation of a social data strategycollaborate, to coordinate, to get more done inless time, or to get things done that we could not a) A customer centric mindsetaccomplish alone. The social data revolution, for companies, isWhy is this a revolution? about a adopting a new customer centric mindset.It is a global consumer revolution because: it Customer centricity is crucial because delightingis happening in the minds of a billion people the customer leads to more loyalty, increased salesworldwide; it democratises the means of and positive recommendations to other consumers.production; and it makes previously hoarded Customer centricity is about addressing eachinformation freely available. For businesses, social customer as an individual, not as a target. Fakedata is a revolution because it fundamentally alters customer centricity comes in many forms, such asthe relationship between buyers and sellers. an automated voice saying “Your call is important to us”. This delights no one.Managing social data – not social mediaLike mass media, social media is designed to In the early days at Amazon, we aggregated salesbroadcast content in one direction. On YouTube data and used sophisticated algorithms to generateor a blog anyone can become a publisher, but recommendations for our customers: customersconversations are one-way, not a dialog. So as a who bought X also bought Y. At the time that wascommunication tool, a video uploaded to YouTube indeed revolutionary, but it was only the no different to an advertisement shown during We constantly worked to make recommendationsthe World Cup. more relevant, to increase the genuine customer- centricity of the entire shopping experience, and to ensure that the promises we made were kept.
  4. 4. The Trading Intelligence Quarterly. Big eCommerce Data 26-27b) Design to encourage the sharing of social data Rules for revolutionariesA sound social data strategy starts by making iteasy for customers to create and share information Generally, most organisations haven’t kept upwith the company, other customers and the with individuals when it comes to embracingworld. Furthermore, incentives for customers to social data’s transformation of opennesscontribute need to be designed well, such as giving and individuality. These rules, adapted fromthem bragging rights and empowering them to Stanford University’s Social Data Intelligencecollaborate. Most importantly, the value to the Test, provide guidelines for how tomorrow’scustomer must be clear, such as personalisation successful businesses can participate in the new,and better purchasing decisions. relationship-centred world.c) Use social data to make decisions Rule #1: Treat your customers as individualsKnowledge about customers’ relationships can Empower your customers to make better-help a company to focus its limited marketing informed decisions as individuals, and to shareresources effectively – what worked for a potential their data with friends and peers.customer’s friends is very likely to work with themas well. For example, Allstate Corp., an insurance Marketing executives often salivate at accesscompany, uses Rapleaf data on a customer and to a great deal of data because they see it is antheir network to determine how carefully to opportunity to segment their customers more.investigate a new claim. “We want to reach single mothers between the ages of 21 and 35 years old living in northern *** Ohio,” is a typical refrain.For companies in tune with the transformation, But this bigger segmentation response to havingsocial data is influencing everything from how more data is far too limited. Segmentation –they create and sell products to how they acquire not long ago the holy grail of marketing – isand lose customers. becoming an anachronism. Most people don’t want to be anonymous. Customers want to beSo, don’t waste any more time crafting a social treated as individuals and they are heading formedia strategy. Your customers, and your platforms and companies that understand this.competitors, have already seen the movie andbought the t-shirt. Embrace the Social Data At Amazon, for example, customers have neverRevolution - it will happen with you or it will been treated as demographic compilations, buthappen to you. as people who have made previous purchasing decisions, shared opinions, viewed particular items, established patterns of decision making, connected with friends either on Amazon or via third-party platforms, and a hundred other variables. Similarly, advertising on Google is not based on segmentation, but on the current search, and advertising on Facebook is based on your social graph. Highly specific segmentation has been surpassed by the ultimate marketing dream: one-to-one relationships on a vast
  5. 5. The Trading Intelligence Quarterly. Big eCommerce Data Rule #2: Become part of your customers’ cards face up. Lufthansa lets customers see how digital lives. many seats remain unsold on a particular flight, Actively help your customers to create a public a great example of socialising data. If you really persona. need to be on that crowded plane, you will pay the relatively high price and probably pay it sooner Customers have long defined themselves through rather than later. If you have greater flexibility, the products they purchase – the Canon (or you may be able to save money by waiting. Nikon) guy, the Prius driver. Maybe customers will not tattoo your logo on their biceps (or Rule #4 Don’t worry, be messy. somewhere else!) but if your company already is Let your customers provide the information they a part of your customer’s life, social data can help want, in the way that they want. you become an element of their self-expression. This is not about pushing product or tweeting So many companies force their corporate your latest marketing message. structure and database structure on customers who are trying to communicate with them by Nike+ does not sell shoes per se, but by allowing making them fill out forms, often resulting in customers to share and compare their running consumers turning away. Companies that insist regimes, it lets them build a public posting of their on forms for interaction don’t understand that prowess. Many check it every day, the average consumers are willing to share much more is three times a week. That is becoming a part of interesting and useful information. Instead, they your customers’ digital life. struggle to categorise themselves according to drop-down menus and feel both frustrated and Rule #3: Liberate your organisation’s data. annoyed. The company won’t sell that product Provide your customers with the information they and the consumer has a bad experience. For need to make decisions. example, if I want to buy anti-virus software for my company, I may be asked if I’m a small, Most companies jealously guard their internal medium or large business. My reaction is, “I don’t data, inadvertently creating a healthy market for know. I just want to buy virus protection.” industrial espionage. Open up your company to the world – it allows you to draw on the collective Instead, companies should take whatever they can wisdom of all the smart people who do not work get. Let consumers tell you whatever they want for you. Open source software grew rapidly and however they want to say it. Make it trivially precisely because it was not dependent on any easy for people to write comments. Then grab the one company’s brain trust. In addition, your data, surface it out and others will comment on customers will gain confidence in your offerings if it. Even if you don’t understand the data, maybe they can see through your workplace procedures, others will and explain it. Craigslist is a good your supply chain and your footprint in the example of this; when someone posts something community. other users will put it in the right group, or flag it as inappropriate. The old game was about exploiting information asymmetry, like the used car salesman who knows the car’s entire history while the customer is ignorant. The new game is played with all the
  6. 6. The Trading Intelligence Quarterly. Big eCommerce Data 28-29 Rule #5: Let employees be messy too. Rule #6: Focus on metrics that matter to your Empower your employees as innovators. customers, not your accountants. Centre the conversation around the things that Don’t stifle the freedom and creativity of your your customers care about. employees. Instead, empower them and give innovation the chance to bubble up. Several recent Most customers care more about receiving studies have shown that the most innovative their package on time than about your earnings companies use far more employee-generated ideas announcement. They care about speaking to than the average. Some companies allot a certain a live human being when they call customer amount of time for employees to explore relevant service. They care about being able to return ideas outside their usual responsibilities. Google’s goods or cancel a service without jumping Gmail, for example, was the result of this practice. through hoops. One of the benefits of social data is that it allows In the old game, savvy mail order retailers employees to test ideas cheaply and quickly. strove to minimize returns by making them Like a venture capital model, most of the small difficult. Zappos, a master of the new game, investments won’t pan out, but the occasional make returns trivially easy, which encourages eureka moments will pay for the rest. customers to make more purchases. Why not publish your call-centre wait times on the web Instead of trying to mine old data, let employees with a predictive model suggesting a better use social data to run well-constructed time to call? And when a customer calls, why experiments to answer relevant questions. not give them access to the recording of their Such questions can run the gamut of business conversation? Invite the world to see the amazing operations. Will customers like this new quality of your customer service, or, should you toothpaste package design? What are customers somehow fall short of perfection, improve on the who tried free samples saying to each other about interactions you are having. the new flavour? If one of two people who are both members of several circles on GooglePlus, how likely is one to respond to an advertisement for a product the other has already purchased?
  7. 7. Amazon’s mastery of dataAmazon’s unique approach to data New algorithmscan be most fully understood by Amazon has recognised that the traditional dogma of retail simply makes no sense in the online world,starting with a brief biography of and has developed new mathematical algorithms toJeff Bezos. interpret data.Bezos studied at Princeton University and graduated “Many of the important decisions we make atwith a degree in electrical engineering and computer can be made with data. There is ascience (having entered to study physics). Between right answer or a wrong answer, a better answer or1986 and 1994, Bezos worked in a number of a worse answer, and math tells us which is services businesses including Fitel, Bankers These are our favorite kinds of decisions.”Trust, and D. E. Shaw. In 1994, he founded 2005 “… most of our inventory purchase decisions canFurther, albeit subtle, clues on the inner workings be numerically modeled and analyzed. We wantof Amazon are found in Bezos’ annual letter to products in stock and immediately available toshareholders – there are 14 so far1. customers, and we want minimal total inventory in order to keep associated holding costs, andOur insights on Amazon’s approach to data thus prices, low. To achieve both, there is a rightencapsulate many of the themes of this edition: amount of inventory. We use historical purchase• A holistic view of profit data to forecast customer demand for a product• New algorithms and expected variability in that demand.• Input driven trading. We use data on the historical performance ofA holistic view of profit vendors to estimate replenishment times. WeBezos’s insight was that in a world of unlimited can determine where to stock the product withinshelf space, and stock decoupled from point of sale, our fulfillment network based on inbound andAmazon could rethink the economic model and re- outbound transportation costs, storage costs,engineer the retail cash cycle. and anticipated customer locations. With this approach, we keep over one million unique items“When forced to choose between optimizing under our own roof, immediately available for the appearance of our GAAP accounting and customers, while still turning inventory more maximizing the present value of future cash than fourteen times per year.” 2005 letter flows, we’ll take the cash flows.” 1997 letter “Our pricing strategy does not attempt to“Our ultimate financial measure, and the one we maximize margin percentages, but instead seeks most want to drive over the long-term, is free cash to drive maximum value for customers and flow per share.” 2004 letter thereby create a much larger bottom line – in the long term. For example, we’re targeting gross margins on our jewelry sales to be substantially lower than industry norms because we believe over time – customers figure these things out – this approach will produce more value for shareholders.” 2003 letter 1 All the Bezos letters can be found here:
  8. 8. The Trading Intelligence Quarterly. Big eCommerce Data 30-31Input driven trading A lesson for all online retailers hoping to emulateControl theory was developed in tandem with Amazon’s success – Amazon has put data at thethe industrial revolution. As inventions became heart of its business.more complex, the core idea of control theorywas to measure ‘inputs into’ and ‘outputs from’ a But data will only get you so far… the culture ofsystem and understand the relationship between continuous invention is consistent throughoutthem. Amazon seems to think of itself as a trading Amazon’s history. Bezos himself seems to bemachine with inputs and outputs, and input driven always learning, summed up in a delightfultrading is at the heart of Amazon’s approach. anecdote from his 2008 letter:“Senior leaders that are new to Amazon are often “At a fulfillment center recently, one of our surprised by how little time we spend discussing Kaizen experts asked me, ‘I’m in favor of actual financial results or debating projected a clean fulfillment center, but why are you financial outputs. To be clear, we take these cleaning? Why don’t you eliminate the source financial outputs seriously, but we believe that of dirt?’ I felt like the Karate Kid.” focusing our energy on the controllable inputs to our business is the most effective way to maximize financial outputs over time.” 2009 letter“For 2010, we have 452 detailed goals with owners, deliverables, and targeted completion dates. These are not the only goals our teams set for themselves, but they are the ones we feel are most important to monitor.” 2009 letter“Cycle time, the amount of time taken by our fulfillment centers to process an order, improved 17% compared with last year. And our most sensitive measure of customer satisfaction, contacts per order, saw a 13% improvement.” 2002 letter ***