Global

Details

  • Industry: Retail, Food, Drink & Consumer Goods
  • Type: Business and industry issue
  • Date: 6/20/2012

Go figure 

Go figure

You know more about your customers than ever before. But how much of your data is actually helping your bottom line?

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Two terms nicely sum up just how much data is sloshing around the world these days. The first is ‘zettabyte’. Some analysts think that’s the amount of information, in bytes, that is now on the internet. It’s a one followed by 21 zeroes. The second is ‘data puking’, a phrase that, while not pretty, aptly suggests that a lot of this information is undigested and unwelcome.


Consumer markets companies, and retailers in particular, will be only too aware of both phenomena. The development of ERP systems opened up the possibility of disseminating business information across stores and even continents. The advent of the internet led to an exponential increase in the amount of customer information and insight available. But social media may be the straw that broke the camel’s back.

Twitter’s global penetration among internet users is around the 10% mark, but already 177 million tweets are sent every day. “Whether you like it or not, thousands or even millions of people are talking about your brand or organization,” says KPMG’s Eddie Short, a Partner in the UK firm and former Group Head of Business Information at tobacco giant BAT.


“Facebook, Twitter and the like are creating enormous amounts of information – infinitely more market and brand research than you could ever possibly need.



"In-store marketing isn’t about the guy with a gut feeling. It’s becoming analytic"


“The problem with social media is that you can Google a point of view and prove almost anything. And it all originates from outside your organization. The right investment in governance controls, policy and procedure is of fundamental importance, so you can say: ‘This is the information we have bought or have from our own sources, and this is what we have from other sources. How confident are we of its veracity?’” With social media, a relatively small number of people account for a disproportionate amount of content, so it’s easy to overreact to bad mood music.


With new social media channels making the potential amount of brand-relevant information almost limitless, it is tempting to simply give up in the face of the flood and stick to age-old sales metrics and time-honored intuition. But just as Billy Beane’s mastery of baseball statistics took the Oakland Athletics to new heights in Moneyball, so certain companies are learning how to manipulate a new generation of data to their advantage.


For Short, the key is “using” rather than simply “collecting” information. At its most profound, customer insight can help shape product development, pricing and branding. But there’s a skill to it, he says: “It is important to take points of view and try and steer them, give some direction and engage with stakeholder communication, not just let them run riot.”


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The virtue of loyalty

Few companies navigate this path more proficiently than data consultancy Dunnhumby, which conceived and runs Tesco’s Clubcard loyalty program, arguably the world’s foremost retail data collection exercise. Half of all British households use a Clubcard, and Dunnhumby (now owned by the supermarket giant) processes six million transactions a day, building a comprehensive picture of Tesco’s customers, their preferences and their shopping habits.


Tesco shares this data with around 200 suppliers. And now it’s actively playing in the social media space, having bought BzzAgent, a “word-of-mouth marketing agency” that signs up “agents” to sample products and talk about them through social media channels. The ensuing conversations are gold dust for marketers. “Word of mouth is powerful online. Nobody will walk up to your trolley and say: ‘That’s not very good,’ but they will on the web,” says Mark Hinds, head of Dunnhumby’s Tesco business. “We are moving past loyalty to advocacy.” BzzAgent claims an average increase in sales of 6.3% for its partner brands.


But social media isn’t the only route for collecting, or using, data. And increasingly, the real insights are happening offline, in stores and malls, where metrics are foggier.


The big buzz in consumer markets circles is around “shopper marketing”, says retail consultant Gary Hawkins, who defines it as interpreting and interrupting (or positively influencing) the path to purchase in store. Even though shoppers are generally trying to avoid impulse purchases and manage budgets, snap decisions taken in the aisle are still huge drivers for high-margin items. “That has brought about a need for retailers and brand marketers to understand customer behavior in the store,” Hawkins says.


Analytics company RetailNext uses data taken from existing in-store security cameras to track customers. It can discover how they move around a store, how much time they spend in certain places (their ‘dwell’) and the rate of dwell-to-conversion. RetailNext customers include Barnes & Noble, American Apparel and luxury writing brand Montblanc, which says it saw 20% sales hikes after optimizing store layouts.


Even supermarkets, which are “pretty advanced” in customer insight, have something to gain from these metrics, says RetailNext Chief Marketing Officer Tim Callan. “Most of the information that they traditionally get is on sales. But what they have been missing is what happens in the lead-up to that. Let’s say you run a promotion and sales don’t go up. Did people come to the store and not buy, or not come to the store? Knowing that helps you work out the problem, and till data doesn’t give you that knowledge.”


At the cutting edge of in-store data, things are getting even more granular. Employees can be asked to wear tiny wi-fi boxes to track their movement and align it to customer patterns to create new shift rosters that ensure no area is ever under-staffed in a busy period. Weather sensors show the effect of heavy rain or baking sun on customer behavior, accessing their “thought process and emotional state,” says Callan. UK-based Path Intelligence picks up signals from customers’ mobile phones to track them as they move around shopping malls. This can help influence store proximity in particular.


As Hawkins says: “In-store marketing is moving towards becoming a science. We’re no longer talking about the guy who has been in the industry for years and has a gut feeling about what will increase sales. This is becoming very objective and analytic.”

Joined-up thinking

Manufacturers are getting in on the act, too. Unilever’s Chief Supply Chain Officer, Pier Luigi Sigismondi, says the company has introduced demand-sensing software to hone its inventory management systems as it moves to a demand-driven value chain.


But the hardest part of the data puzzle can be aligning what you learn from your customers with what you already know. Traditional ERP systems just aren’t designed to deal with the amount of data now being produced, or present it in ways that are readable and useful to either marketers or the finance department. Providers such as Oracle and SAP are coming up with big solutions for big data.


“You can get hold of information quickly – for example, at point of sale – and slice and dice it any way you want,” says SAP’s Adrian Simpson of the new generation of ERP. “You don’t just have to use it the way that it comes to you in an IT report. You can get inside the data so much more quickly.” CRM, EPOS, warehouse and supply chain data is coming together as the much-vaunted ERP ‘dashboard’, which can be revelatory when it comes to quickly making and implementing pricing decisions.


It sounds like a playground for savvy marketers. And in some ways it is. But the cloud on the horizon is the customers themselves.


They also have information, especially about price, and Short says he sees too many retailers and manufacturers drawn into a race to the bottom as they slash prices to react to the threat of real-time data. That gets even harder when retailers haven’t joined up pricing and stock availability across their own channels.


A consumer backlash against sharing data has yet to materialize on a significant scale. But Dunnhumby’s Hinds is mindful of the danger. “The key is that [sharing data] should add to the shopping experience. If you do it cleverly and it works, it’s good. If it’s done badly, it’s intrusive”. Or as Short puts it: “The important thing is to be trusted”. Even in a brave new world, some things remain the same.

Three businesses that learned to love the numbers

Groupe Casino Darden Restaurants Amazon
The French supermarket giant has developed an iPhone app which lets customers compile a shopping list before they visit the store, and pushes offers based on their preferences. Casino’s long-standing pricing technology gets rid of discrepancies between stores (or between shelf and till) in an instant, and allows the chain to react quickly, and roll out changes in an instant, when its rivals shift their price points. Tesco is following in its footsteps with an app that gives customers the fastest route around a chosen store based on their shopping list. An early adopter of technology – it first analyzed point-of-sale data in the 1970s – the company behind the Olive Garden and Red Lobster chains uses software to predict the number of guests in any of its 1,900 outlets at any time. The information helps organize staffing and ordering, as well as optimizing preparation time. Darden claims to have reduced overtime across its 180,000-strong workforce by 40%, and food waste by 10%. Customer comments are delivered electronically, and a Meal Pacing program helps deliver an order to table within a minute of being cooked. The online behemoth uses the language of social networking to recruit customers as its data miners. By making its recommendations process feel like a collaborative effort, rather than a hard sell (principally through its “Betterizer” tool), it gains cheap insight that is invaluable in marketing and predicting inventory levels. Amazon asks customers to rate old purchases, and allows them to disallow recommendations that don’t reflect their personal taste. With 100 million visits per month, Amazon is now believed to be expanding its online ad metrics.
 

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