Boss-someone stole our customer data!!

Last week there was this interesting article in the Mint newspaper by Vandana Vasudevan about customer information being out in the open. You may be the customer of a bank or a telecom company or a retailer –somehow that information is out there with a variety of grey market database sellers! I wrote about the loss of privacy in a previous post here : Whose data is it anyway?

You can access the Mint articles here : Found in a lost database!

The catch about data security in today’s companies according to me is as follows:

1. Customer Centricity is itself not still a focus-given that markets are growing rapidly, Marketers are growing often by bringing in “new users” and so like a leaky bucket they are not obsessed with customer churn yet and that also makes them less customer focussed.
2. In a global survey of 1,375 subscribers conducted by Harvard Business Review Analytic Services in January 2010, 85% of respondents said that information is a key strategic asset, yet only 36% said their organizations are currently well positioned to use information to help grow their business.
3. One aspect that I wanted to point out was that the source of all of this is the Marketer's budget-if regulation comes down hard on the source brand it would drastically change the equation. Today we are chasing the telcos, telemarketing companies or the small grey market database companies-where is the focus on the brand owner whose message it is ! 
4. Customer data therefore is still not valued as much as it should be and though every one mouths platitudes about data security –the fact is that it is often compromised.
5. Not too many Marketing heads(CMO’s ) focus their efforts on extracting revenue yield from existing customers and that leaves relatively junior people driving this agenda. Analytics can help show the value of this data!
6. Ironically in many businesses where regulation drives a “Know your customer” regime like banks or Risk standards push the banks to do what is called a “customer point verification”-there is an army of cheap resources out there in the market confirming that you are who you claim to be….no one monitors this stream of potential data loss as carefully!
7. And finally, people do not pay attention at all to two other streams of data-Prospect data & Lapsed data. Especially customers who cease to be customers of a bank or Retailer, then end up as databases on the market further muddying a “grey market”

Our electronic footprints!

I wrote earlier about data privacy issues and how customers are willing sometimes to share data with marketers in return for specific benefits. What about data which gets picked up without you even knowing about it? Scary right!!

Nick Gonzalez has this interesting comment about this fascinating company:

Path Intelligence is a U.K. based company that monitors foot traffic in a rather ingenious way, through customers’ cell phones. Periodically our cell phones ping the nearby cell towers basically saying “Here I am”. Path Intelligence has built receivers that detect these signals and triangulate the owner’s location with accuracy of up to a meter.

Path Intelligence can then map these signals and track anonymous customers as they move around and answer questions about the store’s layout through online reports. Where are the bottle necks? Where do customer’s spend the most time. How many customers browse and go?

Here is my take:

1. This would be a fascinating way to analyse footfall within a store. It might lead to a better way of staffing different departments within a store. Or even locating another cashier till!
2. Imagine how this can be used effectively to understand which part of an exhibition or conference was visited more. Check this out: http://www.slideshare.net/brady/where-20-path-intelligence
3. Look at the rich analytics that you can do by marrying the footfall data with conversions within the store(cash memos per footfall)

Whose data is it anyway?

Big organizations have a lot of fear concerning peoples' privacy, but book publisher, event organizer and industry luminary Tim O'Reilly thinks it's time to throw our old models out of the window and re look at privacy afresh. "The old model of privacy isn't taking into account any of the trade offs, and clearly people are willing to make those trade offs," he says. "Google maps on your phone sends your location to someone else's server every time you look something up, for example." O'Reilly's position on privacy is a very important one, at this point  when the future of privacy is being debated.

O'Reilly says.

"Technology is taking us a direction where more and more is known about us. It’s hard to be completely anonymized. I think we need a complete fresh look at what trade offs we're making and why. A good example is health care privacy. It's true that there are some diseases that still have stigmas around them, but our need for privacy is mostly about adverse selection from insurance companies. The problem we need to solve is adverse selection due to pre-existing conditions, not to treat the info like it's toxic waste. If we look at the benefits of using the information - they are incredible.

"One thing we can do is look at places where people have given up a fair amount of privacy and feel ok about it. The financial arena is one of those places - it's ok to do data mining for fraud prevention.

What do you think?

1. Should we as a society be sacrificing privacy for the sake of innovation and more relevant services?
2. What is the role of Marketers, especially in India, where data privacy regulations are nascent or not there at all?
3. Can  Analytics play a role in uncovering more insight in the data and making the marketing more relevant thereby crowding out the irrelevant messages ?
4. Should some industries lead the thinking on data privacy? After all Telecom services, Banks & Retail probably have the largest customer databases. Should Marketers in these businesses think ahead and establish “high ground” in how they treat their customer information?
5. What about data sharing across industry- Co branded credit cards have used data across Retail , airline and other sectors  to launch customized offerings? I Mint has done the same as a coalition loyalty program that has multiple participants-Banks , retailers, Airlines etc.
6. How should the CTO/CIO think about this? What kind of customer privacy safeguards can be built into the technology roadmap?

 

Wave & shop!!

I saw this interesting story about Citibank launching a pilot in Bangalore to test out what it claims to be the world's largest Near Field Communication (NFC) contactless payment pilot. Mobile Proximity or “contactless” Payments are made at the point-of-sale (POS) by physically touching or tapping the phone on a contactless reader device.

 NFC was one of Gartner's 8 Mobile Technologies to Watch in 2010. Mobile payments offer the possibility of entirely new ways of making payments and moving money to and from individuals, businesses, and other entities. Look at this interesting Coke vending machine-just wave your mobile and take your Coke!

I found this interesting because I have been observing customer payment behaviour change for over a decade now. Not very long ago, share of credit card spends in department stores was not more than 35 %(that is 35% of total store sales came from credit cards)! Today it is more like 50%!

I wonder how migration to newer payment technology will progress. This is why I found the Citi Tap and Pay pilot to be a very interesting experiment run with commitment & with strong investment. The pilot enabled Citibank MasterCard credit cardholders to use NFC phones to make payments at the point-of-sale and to receive promotional offers and discounts at a wide range of department stores, food courts, restaurants and fast food outlets, book stores and multiplexes.

The catch with contactless payment is that any device to be able to carry out such payments has to be embedded with near-field communications NFC chips; in most cases in India, for example with the Delhi Metro card, consumers are being issued separate cards. The problem with NFC deployments is that no handset manufacturer, except in Japan has taken on the additional cost and effort of embedding NFC chips in their phones.

To take part in the trial, Citi customers first needed to purchase a Nokia 6212 Classic phone, pre-loaded with the Citi Tap and Pay application and enabled with MasterCard's PayPass contactless payments technology. The Nokia phones were made available for sale from a number of Nokia stores in the city and, as an incentive, Citi offered cardholders a rebate if they purchased a phone and then used it to make purchases

Contactless payment allows issuers to compete with the cash payment market. Retailers realize benefits due to faster transaction times, increased revenue, improved operational efficiency, and lower operating costs. Consumers enjoy the convenience of hands-free payment, the ability to pay for multiple services using one device, and the security of not having to display a card for payment.

Contactless payment applications are particularly attractive to retail segments where speed and convenience of payment are essential (for example, quick service restaurants, gas stations, convenience stores, parking facilities, transit services, entertainment venues and unstaffed vending locations).

Here are some thoughts that came to my mind:

1. Convergence is about changing customer behavior-can be done through "trickle marketing" (one to one communication with relevance!)not "mass marketing"!Customers do not suddenly move towards Internet banking or Mobile banking or NFC (contactless payments) !
2. This change does not happen without a structured marketing effort to reduce consumer barriers. These barriers are at 3 levels: a)information barrier-I did not know you could do this? b) payoff barrier-What do i get if i change my behavior-and this need not be only price led & c) transactional barrier-how do i make this new behaviour a habit!
3. Making this kind of change requires marketers to think "one to one" and not "mass". It all starts with understanding & analyzing customer adoption. Analytics can uncover a lot of valuable information about customer paths as they adopt new payment methods.

 Meanwhile read about this interesting Citibank pilot here

http://www.edgardunn.com/uploads/100012_english/100366.pdf

 

 

 

 

Banking is going mobile!

There is this huge debate in India about who should own and drive the Mobile banking journey! Should it be the telecom operators or the banks! Recently, Duvvuri Subbarao, governor of the Reserve Bank of India (RBI), said at the Banking Technology Excellence Awards, “World over, there are two distinct models in mobile banking - the bank led model and the mobile operator led model. The Reserve Bank has a clear preference for the bank led model.”

 Indian mobile banking has two major segments: the urban segment and the rural segment. Celent, a consulting company, estimates that urban mobile banking subscribers will reach 65 million by 2012. The rural mobile segment represents a huge opportunity to bank the unbanked population, thereby adding a revenue stream. But I wonder how much are banks dipping into their vast treasure trove of transactional data to actually analyze the behavior changes that are driving adoption! Are consumers following a path through more advanced usage of ATM's and on to Internet banking and then they become Mobile banking users? Or are Mobile banking users distinct consumers with different needs?

 Whoever leads this journey, banks or telecom companies,the important thing is who is more likely to drive customer adoption and be more “customer centric” in their focus? Both industries, Telecom & Banking have a huge “new customer acquisition focus” and both have over the last 5 years been penetrating the market and bringing in a huge set of customers who are now beginning to expect far better customers service and more products configured to their needs.  In my view the critical area to think about is how are banks profiling and developing a better understanding of their customers who are “early adopters” of tech led services such as Net banking, Mobile banking, Direct pay etc.

Banks have so much information about what is leading to this kind of channel migration. How much of this information is being looked at analytically to deliver a better “one view” of this “new age” customer?

Who needs "New Customers"?

I worked in 2 organizations’, which had a “sense of urgency” about existing customers. I was the head of Marketing for Shoppers’ Stop and later for HDFC Bank.

 

The CEO himself led the “sense of urgency” in both companies! At Shoppers’ Stop we built a base of Loyalty program customers (over a million customers) contributing to over 60% of store revenue and at HDFC bank we reduced cost of acquisition by cross selling to existing customers using analytics.

 

But generally I do not see the same urgency across companies and industry and so I was quite amazed to see this bold statement from the Macy’s CMO Peter Sachse in his keynote speech at the Retail Innovation & Marketing Conference talking about a shift in company focus. For Macy’s, “What we don’t need to do is get new customers,” Sachse said. Instead, “we realized that all we need to do is take care of those who already love us.”

 

Here’s how it all started: Last year, Macy’s embarked on an intense research project to better understand their current customers. They conducted dozens of focus groups. Talked with nearly a thousand people walking out of their stores. Combed through all of their transactional data to find themes in buying patterns and shopping habits.

 

The company has set out on a goal to encourage each existing customers to visit the store one more time each year. “Half the battle is won if we can get them to walk into our store,” Sachse said. “And if we convert them during that visit, our comp store sales will explode.” To accomplish that goal, he said, “We had to get a lot closer to the customer,” which has led to the company’s new strategy of customer-centricity.

 

Here are some tips from Peter Sachse on how Macy’s is making decisions with the customer in mind:

 

• Make merchandising decisions with the customer in mind. Macy’s used to let buyers make merchandising decisions strictly with P&L statements. Today, the company layers customer insight over the sales metrics, which helps buyers make more holistic decisions over how pulling a product might impact customer behavior and overall sales. The product is no longer king anymore, said Sachse. Instead, the customer is queen. (Or king, of course.)

 

• Start all meetings by asking “what will our customer get out of this discussion?” At Macy’s, Sachse says, “If there’s no answer, the meeting is over.”

 

• Create a customer-champion team. Macy’s Chairman and CEO Terry Lundgren calls himself the chief customer officer. Who’s the customer champion in your company?

 

 

Why “Less is More” in Retail?

Retailers find they sell a lot more of nearly everything by reducing the number of brands on offer, but figuring out what should stay and what should go is not easy. In economics they call it the "paradox of choice," the idea that a shopper, when faced with multiple options tends to focus too much on which item to choose, and is therefore less satisfied with the item she finally picks.

Reducing the number of products can help companies increase sales by as much as 40% while cutting costs by between 10 and 35%, according to a 2007 study by consultant Bain & Co.

Here is an extract from an interesting article in The Globe & Mail:

Several months ago Wal-Mart Canada Corp. decided to overhaul one of the staples of its grocery business – the peanut butter aisle. It dropped two of its five lines of peanut butter to free up scarce shelf space for cinnamon spreads. But the decision didn’t cost the retailer a single jar in sales. With fewer selections to browse, customers wound up purchasing more than before.“Folks can get overwhelmed with too much variety,” said Duncan Mac Naughton, chief merchandising officer at Wal-Mart in Mississauga. “With too many choices, they actually don’t buy.”

In a reversal, retailers are now reducing the amount of choice on their shelves. After years of tempting customers with ever expanding arrays of brands, hues, sizes and flavours, they’re racing to simplify their offerings. The recession has encouraged them to focus on top sellers and private labels while throwing marginal products overboard.

But look at the India situation:

Here are some facts from a recent article by  Meenakshi Radhakrishnan-Swami

FMCG companies in India have had a fairly smooth run until now - given that the average kirana is 150-200 sq ft and has space for less than 1,000 SKUs, they didn't need to create endless product variations and extensions of the same brands.

Compare this with Barry Schwartz's list in his 2004 bestseller The Paradox of Choice: Why Less is More, based on a visit to his local supermarket in the US:  285 types of cookies (21 options in chocolate chip alone), 95 different snacks, 360 shampoo types, 40 options for toothpaste, 275 varieties of breakfast cereal, 175 types of teabags.

Schwartz's supermarket was a "not particularly large store", but Indian consumer goods companies would struggle (and fail) to stock even that level of products (and remember, this book is three years old): Cadbury India has over 100 SKUs in two categories, Procter & Gamble sells over 320 SKUs across five categories, while Hindustan Lever has more than 700 SKUs in over 20 categories.

If hypermarket visitors are not to be confronted by acres of empty shelves, then, consumer goods companies will have to expand their portfolios substantially. "

Here is my view:

1.   I wonder if Retailers would like to explore using their Loyalty data to understand purchase behaviour at an SKU level. Companies like Big Bazaar & Spencers would have humongous amount of data which can be used effectively.  Analytics on this data would throw up actionable insights.
2. Also I am sure that a Retailer could partner very effectively with a credit card company to further overlay information on his loyalty card behaviour and analyse his assortment better. Partnered analytics is still a new concept in India and I wonder how it could explode action-ability.

 

Analytics is sexy ..what about making it work!!

Making Analytics sexy doesn’t make it easier to implement! And this is where the challenge lies in Analytics. Striking headlines make for easy copy but don’t do wonders for executing analytic intent within a corporation.

Unfortunately executing analytics is hard work and demands the coming together of business skills, advanced statistical knowledge and technology capabilities. For years there have been sexy headlines about a retailer who found that diapers and beer are purchased together by men on Fridays. Recently one can see this story about Why Visa Predicts Your Divorce?

Unfortunately the challenges faced at the implementation level are really about making your way through issues about  company's structure, process, incentives & the really big one about “silo mentality”.

Making a great Analytics scorecard is possibly only about 35-40% of what is required –much more needs to be done in terms of change management and all the nitty gritty of wading through the implementation. The greatest analytics would not solve the problem of the sales channel continuing to sell a higher margin product! Even if analytics predicts that the next product more likely to be purchased is a different one-the sales channel would continue to sell the higher margin product. In such situation what is needed is the ability to be able to articulate the business case for analytics which involves having a voice in the decision making process of the corporation. Often Analytics teams may be structured as independent support functions and then they would not have the authority to seek such changes.

Key requirements to make Analytics work in my view are as follows:

1. Allow analytics to be both centralized & de centralized-it should not be seen as a function but rather as a necessary process to achieve more profitable results. Some companies who have “got it” tend to have had a visionary leader at the CEO level who drove this vision through-Gary Loveman at Harrah’s Casino is an example.

2. For the Analytics process to mature in any company –leadership must build a “evidence seeking” culture towards decision making. Like the old saying-“In God we trust , all else must bring me data”

Meanwhile the sexy headlines are fun to read, so enjoy!! http://www.thedailybeast.com/blogs-and-stories/2010-04-06/how-mastercard-predicts-divorce/full/

How to make information affect behaviour?

I read an interesting article on how data which is coverted into information affects behaviour. Most often, all data analyzed and presented as information to users or even to customers may not necessarily have the desired impact to affect behaviour.

Here are some interesting perspectives and points that we need to think to help present data in a manner that can seriously help people change behaviour: 

1. Intuit/Mint are great examples of customers having their financial data(online) of where they spend their monies and how they invest & save. By uploading this data, do people change their behaviour to either spend less or save more? - Mint definitely believes so. According to Mint, they started as analysis tool but slowly progressed into providing insights to customers on their current behaviour and promoting actions that affect behaviour!
   
2. The question really is if data can help change behaviour, how do we present this data so that it really has a telling impact on the customers/users who are using it?
   

       The idea data according to this article that can help this is:

      a. Passive data ( The user has nothing to do with this data)

      b. Non-invasive

      c. Real-time

      d. Focussed ( Like a dashboard with key metrics)

      e. Linked in real-time to the desired effect

      f. Simple to gain insight and understand

      g.Linked to private and personal benefits ( Weight loss/gain)

      h. Linked to public benefits ( Reduces carbon footprint)

      i  Quirky positive feedback

      j. Non-threatening negative feedback

      k. Socially connected to take advantage of human nature

This led me to think how we present various data to our stakeholders across businesses and user departments today. We still have a long way to go especially given the fact that discovery of insights after mining the data, needs to be presented well for it to change behaviour across an organization. Also, if we want customers to either buy from us more or recommend alternative products or services, it needs to be done a lot more intuitively by presenting the facts & insights well to get them to consider our recommendation.   

 

The Data tsunami!!

Wal-Mart, a retail giant, handles more than 1m customer transactions every hour, feeding databases estimated at more than 2.5 petabytes-the equivalent of 167 times the books in America's Library of Congress.

Only 5% of the information that is created is "structured", meaning it comes in a standard format of words or numbers that can be read by computers. The rest are things like photos and phone calls which are less easily retrievable and usable. But this is changing as content on the web is increasingly "tagged", and facial-recognition and voice-recognition software can identify people and words in digital files.

Seth Godin put it simply in a recent post: Too much data leads to not enough belief.

Luckily in emerging markets the challenges are somewhat different:

1. Yes data is growing rapidly. But a lot of businesses have not focussed on how they can convert data into information and then into knowledge.
2. Huge opportunity exists to just create a simple "customer one view" and collate information at a customer level. A retailer could look at how an individual customer is shopping, what SKU's does she buy and when does she shop. And then put it together with payment data -did she pay by debit /credit card or by cash.
3. Retailers can then look at how simple data analysis can help build business. Some years ago as a Retailer, I had the opportunity of executing simple campaign experiments on loyalty program data. We sent a simple letter, from the store manager, to customers who had not shopped with the store for more than 6 months and who lived within a 5 km radius of the store. The campaign did wonders and got back many customers to stores across India. As a marketer you can start small and then improve business impact by using more analytics!

Here is an interesting article on how data volumes are ramping up for businesses worldwide
http://www.economist.com/specialreports/displayStory.cfm?story_id=15557443