Data driven Lingerie!

Data driven lingerie=Better products

In difficult times,
fashion is always outrageous.

—Elsa Schiaparelli

How can Lingerie & data have any correlation? I am sure you are asking that questions. But bear with me & don’t forget to watch the video that I have provided a link to.


But before that, allow me to digress a bit. Almost 78% of consumers think it is hard to trust companies when it comes to use of their personal data (Orange, The Future of Digital Trust, 2014). And yet Personal data has become a currency today. All of us are leaving our data behind in a digital exhaust that has begun to worry us as consumers.

And yet, the World Economic Forum is calling personal data a ‘new asset class’: “a valuable resource for the 21st century that will touch all aspects of society”. But companies will need to understand how they can gather customer information without compromising the customer’s trust!

A recent PEW report had this to say:

“While enthusiasts see great potential for using Big Data, privacy advocates are worried as more and more data is collected about people – both as they knowingly disclose things in such things as their postings through social media and as they unknowingly share digital details about themselves as they march through life. Not only do the advocates worry about profiling, they also worry that those who crunch Big Data with algorithms might draw the wrong conclusions about who someone is, how she might behave in the future, and how to apply the correlations that will emerge in the data analysis.”

True & co is this interesting company that combines data & design to create an opportunity for consumers to share data with the company thereby improving the appropriateness of the product to the customer. True & co claims to be the first company to fit women into their favourite bra with a fit quiz – no fitting rooms, no measuring tape, no photos – and to recognize that there’s so much more to fit than her band and cup size. The data they collect allows them to match the customer to over 6000 body types on their database.

Research suggests that women loathe the bra shopping experience and the massive $14B intimate apparel industry is dominated by one primarily brick-and-mortar player. So True & co uses big data to make shopping online for lingerie easier & better. They collect over Half a million data points from users to help customize the experience. Since the company launched in 2012, True & Co has collected some 7 million data points They used this data to launch products designed using this data. Body type, implicit explicit preferences etc all mashed together to create a personalized recommendation engine.

Do have a look at this video telling their story:

So consumers are happy to share personal information as long as they see a “value add” for themselves. And organizations with trust-based information sharing relationships with customers will have a significant competitive advantage over those with traditional data gathering relationships.


Sous Chef’s & data??

A Chef’s Data-Driven Empire

Geoff Tracy couldn’t clone himself. But as his restaurant empire grew he did the next-best thing, creating a complex, data-driven system to ensure that his employees always do everything—from plating a salad to setting the dishwasher temperature—the Chef Geoff’s way.

I have not heard of a restaurant that used data effectively to run its business & so Chef Geoff was a huge surprise. Isn’t it amazing how large companies often hesitate to use data effectively & end up setting up a central analytics function which needs to fight turf wars to even enable them to get their hands on data? While at the same time a restaurant like Chef Goeff’s could so effectively use the data to enable its business.

Finally, it boils down to belief, are you ready to make changes in Operations basis what your data tells you. And it is always a Catch 22, unless you make the changes that data is telling you to, you can never prove what is more effective.

I read this interesting statement from D J Patil from Linked In

Data Jujitsu: the art of using multiple data elements in clever ways to solve iterative problems that, when combined, solve a data problem that might otherwise be intractable. It’s related to Wikipedia’s definition of the ancient martial art of jujitsu: “the art or technique of manipulating the opponent’s force against himself rather than confronting it with one’s own force.”

I have seen that the strongest data-driven organizations all live by the motto “if you can’t measure it, you can’t fix it”. And in such companies, the “data or analytics people” are embedded in the operations! Analytics may not even be a separate function; rather it is the way business is done!

Read this interesting story about Geoff Tracy & how he is building his restaurant business on data steroids!! Also remember that now with Social data streaming in, the possibilities are endless. If Geoff Tracy was to claim his business on FourSquare he would also get access to a whole bunch of Analytics dashboards from Foursquare telling him about his daily check-ins.

Amazon & it’s bold experiments!

Jeff Bezos writes an annual letter to his shareholders which is an amazing lesson for any business. He always attaches a copy of his original 1997 letter to reiterate that even today it is Day 1 in his business. He believes that “A dreamy business offering has at least four characteristics. Customers love it, it can grow to very large size, it has strong returns on capital, and it’s durable in time – with the potential to endure for decades. When you find one of these, don’t just swipe right, get married”. Here is a link to one of his letters:

Anyone who thinks Amazon is just another online retailer isn’t paying attention. Amazon is constantly experimenting. You have to compare your business to Amazon & ask how many experiments did I run today & how many of those did I scale up?

In comparison, most legacy companies love structure & defined process. They test few things after a lot of shortlisting & then test them to scale up. They measure them vs financial returns metrics like IRR hurdle rates & only scale up those that pass financial metrics. I have nothing against this rigor. What I believe is that the metrics need to change. Companies must allow far more experiments to happen & measure the one’s which customers start to vote for & then change the system to understand how to scale them.

And mostly Amazon experiments are about how to provide more value to its customers.  Everything in this list of customer-facing projects that set Amazon apart started with experimentation:

  • Amazon 1-Click,
  • Mechanical Turk,
  • Amazon Marketplace,
  • Customer Reviews,
  • Amazon Recommendations,
  • Amazon Wish List,
  • Amazon AutoRip,
  • Amazon Storyteller,
  • Amazon Studios,
  • the Kindle line of eBook readers,
  • Print on demand,
  • Amazon Cloud Drive, and
  • Kindle Direct Publishing.
  • And of course, AWS lives on innovations:

I would like to talk about two Amazon experiments:

  • Courage to change pricing:

At one of Amazon’s meetings, Jeff Bezos said that the company’s goal is to make Prime benefits so numerous and valuable that it’s irresponsible not to be a member. Wow, that’s almost a challenge to consumers to become more responsible!!

Amazon has been experimenting with physical retail stores since 2015. Though their efforts have mostly been experimental, there are lessons in it for Brick & mortar” retailers.

Customer loyalty is much more than a Loyalty program. Many Retailers launch loyalty programs but over time they are not able to clearly attribute the success of these programs. There are vague references to what percentage of sales is attributed to the Loyalty program but no clear mention of how much of that sale comes from repeat customers. The typical approach to customer loyalty shouldn’t end with the launch of a program, emphasizing discounts and offers. Rather it should signal the beginning of a strategic intent: the desire to building a relationship of value to the customer. Companies need to be loyal to customers & not the other way round.

Making significant operational changes is not easy.  Cashiers at Amazon’s physical bookstores now ask each customer the same question: Are you a Prime member? I know that we do get asked this question at many retailers we visit-Shoppers Stop Customer care associates ask if you are a member of the First Citizen program. But what is radically different is that the Prime customer actually gets far more value. That’s because Amazon recently implemented a new pricing structure at its bookstores that could signal a broader strategy for the company’s brick-and-mortar retail expansion.

At the Amazon bookstore in Seattle’s University Village, Prime members who pay $99 for an annual membership— or $ 10.99 per month— can purchase books and other items at the same price that they sell for on

However, if you’re not a Prime member, you pay the list price


  • Bringing in new data, reading your car license plates: Identifying cars would help it speed up pickup times at brick-and-mortar stores. Amazon knows that to truly win the retail wars, they have to attack the grocery segment & provide significant value for consumers. One of Amazon’s many ambitions for the next version of its grocery-delivery service, Fresh is to innovate like crazy. The company will set up a series of “convenience stores,” the Journal reports, where it will sell basic goods like milk, produce, and meat. For customers seeking a quicker checkout, Amazon will soon begin rolling out designated drive-in locations where online grocery orders will be brought to the car, the people said. The company is developing license-plate-reading technology to speed wait times.

    In India, the government is providing the digital data of registered vehicles to banks, insurance companies etc. as a paid service. Here’s the link to apply for the same:

    Can we pick up video feeds from Mall parking lots and automate the process of picking up the license plate dos from the video feeds & then hit the Vahan site & get the name of the owner & car make.

    Post that we keep deduping it with our client databases to get matches & then append the information.

    Amazon is teaching companies to experiment & learn how to build value.Hope legacy companies are listening!


Banks & Customer profitability!

It is interesting to see the Mobile phone services in India beginning their journey to increase profit per customer! During the last two years, profits and revenues of Indian telecom companies have suffered from a bruising price war that has cut call tariffs to less than one US cent a minute.

But looking at profits per customer does not come easily to most companies. Banks have done it well & so have some casino companies-Royal Bank of Canada & Harrah’s Casino come to mind here!

Also, the solution does not lie in “firing some of your customers”. Here is a lovely comment from the Vice Chairman, Royal Bank of Canada:

“There is no such thing as an unprofitable customer. If we can’t make money on the client, then it’s not the client’s fault – we have to change something in the way we operate. We can either charge the customer more because we have not got the price right or we need to take our costs down or we need to stop selling the product to them and find something more suitable to their need. We try to match up the package to the client so that they are only paying for what they need” Jim Rager, Vice Chairman, RBC Financial Group

I have seen a Bank in India, practice this strategy very effectively. I was the CMO of HDFC Bank & I saw how effectively customer profitability was baked into the bank strategy.Here are some observations:

  1. Start with a simple model of customer profitability or Customer value segmentation. Have different segments of customers; band them from least profitable to most profitable. Analytics can help here but try to keep measurement principles simple.
  2. Keep the measurement consistent –it need not be the most advanced analytic technique but important to hold it consistently over a 3 year period at least!
  3. Ensure you link management action to it. Look at why a customer is in the low profitability segment. If it is a bank, ask if the customer is doing too many cash transactions or has not been sold another product. This analysis can lead to clear management action.
  4. Review customer profitability metrics aggressively. Wouldn’t it be nice if you had a customer level P&L, too much to ask for?



Analytics & the art of the Puzzle!

The problem with analytics is that sometimes it becomes an ivory tower! But journalism is showing some wonderful examples of how analytics & visualization can connect economics & everyday life in interesting ways.

I continue to believe that this trend of “Information journalists” is what we must bring into the analytics practice in the corporate world. Make data interesting & actionable & you will see adoption go up like crazy!

Sometime back David Leonhardt, an economics writer for The New York Times, created an “interactive puzzle” that enabled readers to create a solution for reducing the federal deficit by $1.3 trillion (or thereabouts) in 2030. A variety of options involving either spending cuts or tax increases were offered, along with the size of the reduction associated with each option. Visitors to the puzzle simply selected various options until they achieved the targeted reduction.

Nearly seven thousand Twitter users completed the puzzle, and Leonhardt has summarized the choices.

The starting point for their calculation is work done by Alan Auerbach and William Gale, two economists who are experts on the federal budget. Mr. Auerbach and Mr. Gale have written two recent papers that review what they call “the dismal prospects for the federal budget.”

Now imagine how interesting it could get if a company decided to use analytics in an interesting way to set up a Budget planning exercise within the company. And then leverage the techniques in user-friendly ways to get output that business users can play around with! It could be a powerful way to embed Analytics in the Business Planning cycle.

Again this needs Analytics to be embedded into the planning cycle of the company & only having an Analytics department is not sufficient.

The important point here is that it is the intersection of technology, creative & analytics that gets us to move ahead!


IBM, Adobe,Oracle…watch out!

IBM, Adobe & Oracle have all decided to focus on the CMO. Don’t get me wrong, I love these companies & I think they are doing a great job of reaching the CMO’s.

But the job of the CMO continues to get harder! And the number of options the CMO has to wade through just keeps getting larger. According to Scott Brinker: “From 2016 to 2017, the marketing automation category of the marketing technology landscape grew yet again, by 36%, from 156 vendors to 212. If you predicted it was going to consolidate in the past six years, sorry, you were wrong”

In the past there was a difference in the business models of software & service companies. One was low-margin analysts and the other was high-margin code. But that difference is now disappearing. SaaS has also entered the business lexicon. But it isn’t so simple for SaaS players also.

When it works, SaaS has delivered phenomenal results.Giants like Salesforce, Atlassian, ServiceNow, LinkedIn, Workday and Zendesk have displaced on-premise software solutions and have a combined market value of $94 billion

Not all situations are appropriate for SaaS products. In fact for marketing, maybe service providers are better suited to deploy the SaaS solutions for clients. They bring expertise & can help improve speed to market & also maximise utilisation of SaaS product features. JEGI has nicely coined this term SaaSfraS. In their words: “Client service teams expertly operates the software on behalf of customers to deliver the desired results. Call it “SaaS as a Service”. Or maybe “Software as a Service as a Freakin’ Awesome Service”– SassafraS”.

Meanwhile, service companies are selling more software. For example, Deloitte Digital packages its own predictive models under the brand name nACT. Global holding company Publicis Groupe acquired mobile ad solution RUN, part of performance-marketing platform Matomy. Meanwhile, rival WPP claims to have invested more than $1 billion in technology, much of it gathered under its ad tech umbrella Xaxis.

CMO’s need to navigate this landscape & think before they commit to either a startup or to IBM,Oracle or Adobe? And the IBM’s of the world have to think harder about how they sell, how they implement & how they can bring more innovation into their products?



A Billion people customer behaviour experiment!

India’s population & the mirage of the huge middle class has existed for many years. It is only now that a few trends are coming together to make some of those projections into a reality.

In November, when the government Demonetised the currency, it set in motion what can possibly be called ,the world’s largest experiment, a billion people were forced to change their payment behaviour overnight. Banks were centre stage during this & would today have access to all the individual customer data that showed change in behaviour.Maybe companies can become a full-time laboratory? What if you could analyze every customer transaction, capture insights from every interaction, and have that data available real time? Actually technology now exists to make this a possibility for at least those businesses which have direct customer information-Banks &Telcos amongst others.Google has just launched a new feature to Google Calendars called Goals. This allows you to direct Google Calendar to fill in unscheduled hours with time devoted to work toward more personal goals, such as exercise more, meet your mother or read more. Google bought Dan Ariely’s company to launch this feature. Now with millions of customers using Google Calendar, they will have actually have transactional information that predicts how people prioritise between the short & long term goals. What a massive behaviour experiment that will be! And new age companies like Google have assembled the technology & people to constantly analyse the data that is generated by users consuming their products. New age companies, such as, eBay, and Google, have been early leaders, testing factors that drive performance—from features on a Web page to the sequence of content displayed.

India’s urban population grew from 290 million, in the 2001 census, to an estimated 340 million in 2008 (this is 30% of India’s population) & according to Mc Kinsey estimates this could go up to as high as 590 million by 2030. It took 40 years for India’s urban population to rise by 230 million (between 1971 & 2008) & India will add the next 250 million in half that time.

Aadhar is probably the world’s largest database. But with this kind of demographics, companies operating in India will manage to create significantly sized customer databases. So data about the individual & how she responds to marketing triggers will now be available at large scale for marketers. As India becomes increasingly digital, customer data will emerge on:

  • How customer’s shop?
  • How they save?
  • How they react to cash & digital currencies?
  • How they transact?

About 40% of India’s population will be living in urban areas by 2025, and these city dwellers will account for more than 60% of consumption. Much of this growth will take place in small towns. BCG estimates that by 2025, wealthy urbanites will be responsible for one-third of total consumption. Again BCG estimates that nationwide, internet penetration rose from 8% in 2010 to almost 25% in 2016. It is likely to grow to 55% or more by 2025, when the number of users will likely reach 850 million. The composition of the user base is also changing. It is expected that expect that more than half of all new internet users will be in rural communities and that rural users will constitute about half of all Indian internet users in 2020.

This also means that thanks to Digital, a lot of consumers will become addressable through their mobile phones. The more marketers spend money on digital, the more measurable it will become. In developed markets, this is leading companies to make large investments in data analytics

The rate of increase in the amount of data generated by today’s digital society is amazing. According to one estimate, by 2020 the global volume of digital data will increase more than 40-fold.Beyond its sheer volume, data is becoming a new type of raw material that’s on par with capital and labour.Massive Internet companies such as Google, Facebook and Twitter have shown the importance of collecting, aggregating, analysing and monetising personal data. These rapidly growing enterprises are built on the economics of personal data. I see many more companies beginning to take this very seriously in the years to come. Banking has understood this traditionally but I feel even the FMCG world will begin to grasp this in the years to come. Traditionally FMCG has been a data dark industry while service businesses like Banking, Retail, Travel etc have been customer data rich.

A lot of the growth in India would come with consumers moving up with affluence. And while consumers are becoming more affluent, companies now have the ability to reach & engage such customers through Mobile & other digital means.

Of the 650 million users expected to be using Internet in India by 2020, a whopping over 61 per cent will be accessing it in local language, forming majority of the online population, according to technology giant Google.

What kind of implications does this have for Marketers?

  1. FMCG brands should start to develop their own independent data to give them a picture of both consumer and shopper behaviour. Maybe the way to do it is through partnerships & creating coalition programs. Organized retail has low penetration in India. This impacts the largest “success criteria” for a coalition, the high frequency supermarket category. Consumers build points fastest with high frequency categories like supermarkets. But in India, organized Retail is less than 2-3 % of total retail spends. That makes it harder to effectively bring in a large number of smaller Retailers into a coalition program. Maybe the innovation required for India is that a consumer goods company leads such a Coalition & brings in its distribution muscle across small retail. Now that would be a game changer in India. Could such a venture be owned by a Unilever or an ITC? Or can the ultimate high frequency category, the newspaper pioneer this space in India. Imagine a Times of India led coalition!
  2. Loyalty: There are very large rural audiences in urban areas in India. This is due to the huge migration that is consistently occurring-moving people from rural to urban areas. I would look to experiment here. Build relevance amongst this segment with loyalty applications that are completely voice based. I would look at loyalty applications that allow this population to use voice based applications to share credits across: transportation, education, & money transfer!
  3. On boarding for new customers: Banks, Telecom companies & other service organizations will rapidly get new customers who are just not familiar with their services. There is likely to be a huge inflow of customers at the bottom of the pyramid who would with increased affluence be buying products & services for the first time. It would be critical to onboard such customers effectively. Also you would have a whole range of behaviours which would be getting triggered with the government’s move towards digitisation.  How do you get a customer to start using his debit card on POS without sufficient & relevant information?
  4. Growth of microsegments: need for analytics to study small consumer segments that may begin to display very different behaviour. As an example, youth in lower income household’s may take up Mobile banking in a much bigger way than what was traditionally thought-Marketers need to be watching this kind of behaviour change very carefully. Especially Banks, Telecom & retail companies have data at a customer transaction level which will help them watch this kind of behaviour change using advanced analytics.
  5. Impact on Retail: Many years ago during my Retail experience, I found that many stores were impacted by what we called the cluster effect-a store in Hyderabad got many shoppers from Vijaywada, a store in Pune got in customers from Solapur etc. And these customers came in for short visits to the city & ended up spending big time! So they were valuable high ticket customers! All this happens because these visitors had friends & family working in the bigger cities. It would be interesting to see Retailers develop focussed databases to identify such prospects in partnerships with Travel companies?
  6. Power of campaign management in local languages: Many brands will want to predict which language is their user or subscriber more comfortable in. Of the 650 million users expected to be using Internet in India by 2020, over 61 per cent will be accessing it in local language, forming majority of the online population, according to technology giant Google. So traditional campaigns in English would not be as relevant as content created in local languages. Google research shows that over 44% of local language internet users find it hard to comprehend product descriptions in English.
  7. Marketing technology can play a powerful role in all of this. Bring on a seasoned Technology guy into your marketing function to create a Martech vision.

Why Amazon may eat Future group, HDFC bank & other legacy businesses for lunch?

Is analytics yet another fad? Is there much more talk about it than real solid action. It does seem so when you look around you as a consumer. Marketers still don’t care, as much, about being relevant to you. You get that umpteenth credit card solicitation from the bank which has already sold you a card. And nothing about a physical retailer shopping experience makes it personal for you! And yet your online persona seems to be treated differently & when you go to Amazon & other sites you do get a feeling of getting offers being recommended for you. And as a consumer you flit between your online & offline avatars, this becomes more obvious. What have these “new age” companies done differently than has disrupted the legacy competitors?

One of the key strengths that new age companies bring is their “data literacy”. While legacy companies are still at some level paying lip service to the whole concept of data based marketing. So is Analytics just a fad & have we been oversold on it? Technology players have packaged analytics into each of their solutions at different levels of complexity. And they have created a lot of marketing noise around it. It almost seems like buying analytics software or some piece of digital platform will suddenly make the organisation an Analytics champion. Maybe the issue is much more fundamental.Organisations have to rethink how they leverage analytics & actually change their company structures, incentives & processes to create meaningful & large business impact. The volume of data available to companies continues to double every year & new streams of data from the Internet of things is adding to the party. Clearly most legacy companies still have a long way to go to truly extract value from analytics. Apart from a few digital natives such as Amazon, Facebook, Google, Netflix, and Uber most companies have struggled to realize anything more than average returns from their investments in big data, advanced analytics, and machine learning.

But it is still early days. According to McKinsey, “About 90 percent of the digital data ever created in the world has been generated in just the past two years, only 1 percent of that data has been analyzed”.
I think where many companies go wrong is that they do not have a clearly articulated strategy around analytics. How much extra revenue can I generate if I had access to insights that Analytics can produce? What if Shoppers Stop said that we will target a Rs 1000 crore revenue by crafting an Analytics led strategy. How do we bake this in the company’s Annual operating plan along with the micro level changes required in company structure & business processes. How do we ensure that the business use cases associated with this are sufficiently detailed to ensure that we put together the data required to actually do the analytics. The next thing companies need to do honestly, is assess where we are on this journey. One of the most critical pieces in the journey is to embed analytics folk on the business side to become translators who help the traditional business manager understand what is being done with the analytics. This is a very significant step & companies need to invest fully in this to allow for such translation to happen on the ground.

What’s the difference? Is there a category of organization which is able to leverage “data” far more effectively? Who values Analytics more? Some industries seem to believe in the power of analytics & actually base decisions on this. A bank decides whether to give a loan or not basis an Application score card or a credit card company spots a fraudulent activity basis analytics & stops the card usage. A lot of other industries use Analytics for insight generation but are they as good as the Banking & Financial services industry (BFSI) in linking the analytics to action.

Clearly an important element that accounts for how data led the organisation can become, is the “Culture”. A way of working in the business where everybody assembles data to take key decisions. When Warby Parker selected its first office location outside New York, it considered a large set of variables — Gallup’s Well-being index, talent pool, cost of living, number and cost of flights to New York, etc. — and ranked and weighted them as part of the final decision. So what is critical is that, a data-driven organization will use the data as critical evidence to help inform and influence strategy.

Data led organisations also “test” a lot. They allow the data from the tests to do the talking & they make key decisions by testing. I think the “new age” companies who are born out of the internet revolution do this very well. Could the enterprise become a full-time laboratory? Digital native companies were built for data and analytics–based disruption from their inception.

While new age companies are structured to do this very well, there are a few traditional or legacy companies who have also created a differentiator using Testing methods. Nigel Morris, one of Capital One’s cofounders says that the company’s multifunctional teams of financial analysts, IT specialists, and marketers conduct more than 65,000 tests each year, experimenting with combinations of market segments and new products.

Google-executive-turned-Yahoo-CEO-thought-leader Marissa Mayer declares that “data is apolitical” and that her old company succeeds because it is so data-driven: “It all comes down to data. Run a 1% test [on 1% of the audience] and whichever design does best against the user-happiness metrics over a two-week period is the one we launch. We have a very academic environment where we’re looking at data all the time. We probably have somewhere between 50 and 100 experiments running on live traffic, everything from the default number of results to underlined links to how big an arrow should be. We’re trying all those different things.”

Here is an excerpt from Carl Anderson’s book:
“It was 1998, and Greg Linden, one of Amazon’s early engineers, had an idea. Why not create recommendations on checkout? Supermarkets put candy at the checkout aisle to stimulate impulse buys. That works. Why not peek into the cart and make personalized, relevant recommendations that the customer might appreciate? He hacked up a prototype, got it working, and showed it around. The rest of the story is best told in his own words:
While the reaction was positive, there was some concern. In particular, a marketing senior vice-president was dead set against it. His main objection was that it might distract people away from checking out — it is true that it is much easier and more common to see customers abandon their cart at the register in online retail — and he rallied others to his cause.
At this point, I was told I was forbidden to work on this any further. I was told Amazon was not ready to launch this feature. It should have stopped there.
Instead, I prepared the feature for an online test. I believed in shopping cart recommendations. I wanted to measure the sales impact.”
And what a success this experiment was! 35 percent of what consumers purchase on Amazon comes from product recommendations based on such algorithms. Amazon calls this the “item-to-item collaborative filtering” algorithm and it’s used this algorithm to heavily customize the browsing experience for returning customers.

I guess the “new age” companies are architected to capture data far better than the legacy companies. But a lot of it also comes from mindset. A lot of the new age companies do not hesitate to ask customers for their data, secure in their knowledge that they will provide value back to the customer in this barter. One simple example is Google’s Screenwise Trends panel, which gives a US$5 cash voucher to anyone willing to simply share their Internet browsing behaviour with Google and its partners, with a further US$5 gift every three months thereafter. Or take Raptr, an app that tracks users’ video gaming habits in exchange for regular rewards, such as in-game content or free games. Online fashion retailer Zafu allows customers to buy high end jeans by asking a series of simple questions about the customers’ body type, how well their other jeans fit, and their fashion preferences.The data collection and recommendation steps are not an add-on; they are Zafu’s entire business model

But these are just the starting point. Other businesses will start to develop more creative incentives, from loyalty points through to enhanced services, to encourage consumers to share their data. And the trick lies in making that data central to your business model!

Also maybe, new age companies have younger employees who are not afraid to use data to change the mind of more senior folk. The shared economy of data lets owners capitalize on the First party data they are already collecting. First-party data can be gathered from a marketers’ site traffic, CRM database, or customer purchase history. With their Android and iOS mobile operating systems, respectively, Google and Apple know the location of every customer’s Wi-Fi-enabled phone — far more location data than any other company could access. The Silicon Valley giants aren’t allowing access to such data by outsiders as yet. The new age companies, from Uber to Facebook, hold growing stores of data about user behaviors, and that is a “customer data moat” that they are creating.

Data and analytics are in fact changing the basis of competition. Changes in the business environment affect all sorts of companies. India’s move to demonetise it’s currency was one such trigger. Paytm hit a record 5 million transactions a day starting 10th of November, 2016! In less than 24 hours, Paytm’s platform saw an overwhelming 435% increase in overall traffic — as millions of consumers across India moved to use their Paytm wallets to transact. Instamojo, the online payments service provider for SMEs, also saw a huge surge in merchant signups by 1,500 percent on its platform. And in most businesses now new age companies are fighting for market share with legacy companies. So your investment in analytics capability can pay rich dividends. Earlier Industry leaders invested mammoth amounts into factories and equipment, the new emerging companies invest heavily in digital platforms, data, and analytical talent. But in legacy companies, often Analytics is seen to be too theoretical. Not enough integration with systems has happened to push decisions to the point at which consumers interact with the business. This is far easier to do in new Online businesses which have built their systems around this capability. CIOs & technology teams in large existing legacy businesses are taking time to act on this. New age companies are doing it very well though. Recommender systems are very well integrated with the consumer buying process. As the new age companies compete more with legacy companies, the need to integrate analytics into the business fabric will become even more palpable. So a Meru cabs should be able to pivot & compete with an Ola by embedding some fundamental data & Digital thinking!

And yet,Gartner says that only 20% of enterprise will use more than 50% of the total data they collect to gain competitive advantage. So most companies are capturing only a fraction of the potential value from data and analytics. Companies are now looking at new sources of data that can bring enormous competitive advantage. In Vehicle insurance, where new companies have entered the marketplace with telematics data that provides insight into driving behaviors. Also in personal loans, a while new segment is created basis data trails that didn’t exist earlier. Similarly in Retail businesses, huge amount of Video data exists that can further bring insight that positively impact operations.
So unless companies learn to creatively marshal their data resources, they will leave a lot of opportunities on the table! This is what software architect Grady Booch had in mind when he uttered that famous phrase: “A fool with a tool is still a fool.”

In most legacy businesses, analytics as a function is often seen as a support function. The vision is limited to provide data based support to other business folk. This is a mistake as what is required is a complete disruption. Do you want your analytics team to participate in deeper strategic & longer term decisions in the company?Do Analytics folk with their deep specialist background have the skills to participate in such initiatives? Can they own a P&L & run the complete digital avatar of the legacy business.
So more debate is required before an organisation is able to clearly articulate its Analytics strategy. In fact the triumvirate of Analytics, Digital & Alternate channels go well together. Analytics can disrupt the business model & for companies who really want to compete in this data rich world, a clear articulation of Analytics strategy is very important. And then companies can debate about which analytics team structure is most appropriate. Should the team be centralised or decentralised. Or you could create an internal consulting organisation with resources embedded in user departments. Another way of thinking about this is to create a “hub & spoke” capability with a Centre of Excellence model underpinning it. But more fundamentally, how can a legacy company compete with new age companies & actually use analytics in a more holistic way.

My experience of working in the trenches has been that someone has to lift Analytics out of the mindset of a function & help seed it as a part of Business strategy itself. To do this, you have to articulate the Analytics strategy & expand on how it would impact the company Structure, Incentives, Channels& Processes. Companies need to realise that this needs a lot of involvement at the CXO level & just having an Analytics department would not enable that. An internal or external evangelist needs to push the envelope to create & sustain the strategy. New age companies do it more naturally, legacy companies need to make a solid effort!
Then again companies must realise that Analytics doesn’t need you to solve a technical problem but a “business & social” problem. And most Business analysts have not spent much time in business roles. They are super specialised number crunchers without a sufficient exposure to business reality. Even if the managers have some exposure to business through experience across a variety of analytics projects, is it enough? Analytics and data are transforming companies around the world. Yet one of the great difficulties with analytics is that it can be difficult to explain and understand; it is widely held that analytics specialists don’t communicate well with decision makers, and vice-versa. As a result, analytics adoption is still not easy within legacy companies. Analysts, at one end, are busy learning more specialised & deeply technical methods of analysing data & at the same time they are finding it difficult to get themselves “heard” within organisations. Influencing ultimate decision makers is similar to selling products or services to external customers. Analysts need to understand that when they present ideas to decision makers, it is their responsibility to sell — not the decision maker’s responsibility to buy. Does this bring the analytics career into some jeopardy? No but what it does is ask for the creation of an entirely new role often referred to as the Business Translators. Ideally for this you should take a few of your solid analysts with good communication skills & embed them in the business. Thereby asking them to play a translator role to embed analytics into the fabric of the company. Analysts need to “Story tell” to bring analytics into the fabric of the company. But analysts are too one-dimensional & not embracing the intersection of “technology, statistics & business”. So analysts struggle to tell stories. Often I see journalists do a far better job with infographics in media. But information journalists are not wanting a career in analytics & so there is a gap in “story telling”.

And finally, the Average age in the “new age” companies is far lower. Younger people are adopting analytics far faster. They are getting exposed to it in their education & they are consuming it through their “digital avatars”. They see this often as a “no brainer”. Older executives are harder to convert to this line of thinking.

Unless legacy companies completely relook at how they see analytics, they may lose to New age companies!
So will Amazon eat the legacy businesses for lunch? Time will tell but clearly the legacy companies need to take notice of how data is now a core product & leveraging it can hugely boost company performance. In general, markets now value companies more than the sum of their tangible assets. And so intangible customer data & how it is used by companies will be the key differentiator in the days to come.


Test or get Fired! Harrah’s casino’s amazing philosophy

Analytics needs a evangelist! Without such a person, you just don’t get the impact that Analytics actually is capable of providing! Mostly this evangelist needs to be right at the top, the CEO! I have worked with a range of industries & everywhere the degree of impact shoots up once you have a CXO who is evangelising this change.

Of course, some CMOs have led their organizations into embracing the practice, including John Costello, former exec VP-CMO of Home Depot; John Elkins, head of global brand and marketing at Visa International; and Cathy Lyons, CMO-exec VP at Hewlett-Packard.

One organization which has become a huge case study in the application of a “fact” based approach to business is Harrah’s Entertainment! Recently though it had a messy bankruptcy of its casino operating unit and reportedly faced fines of up to $20 million over money laundering allegations. The most valuable of the assets being fought over by creditors is the data collected over the last 17 years through the company’s Total Rewards loyalty program.

Back in 1998, as Harrah’s was about to embark on a wave of expansion, their CEO Philip Satre asked Gary Loveman to take a break from Harvard to become chief operating officer of Harrah’s Entertainment. The important thing was the he was not brought in as a CMO but as the COO-he had the line authority to make changes that would impact the business!!

“In terms of income, it was actually a pay cut,” Loveman says, since he had to forego the consulting that supplemented his income as a professor.

He went on to develop the gaming industry’s most successful loyalty and analytics program—Total Rewards—which boasts more than 40 million members.

In an interesting article, Karl Taro Greenfeld says this about Gary Loveman, who has since then also become the CEO: the chief executive officer of Harrah’s Entertainment Inc., the largest gaming corporation in the world, sees his customers as a set of probabilities wrapped in human flesh.

Since taking over as CEO in 2003, Loveman, 50, has relied on the numbers to build Harrah’s from a regional operator of 15 casinos to one with 39 in the U.S. and 13 more overseas.

His first big move as COO was to start a loyalty program called Total Rewards, which became such a success — growing to over 40 million members by 2010, the largest database of probabilities in the industry — that by the time Satre stepped down in 2003, Loveman had become the logical choice to succeed him.

Loveman earned a Ph.D. in economics at MIT and went on to become CEO, president, and chairman of Caesars Entertainment, owner of Harrah’s casinos and other resorts worldwide.

Loveman says there are three ways to get fired from the hotel and casino company: theft, sexual harassment, and running an experiment without a control group.

But this seems like common sense, run experiments , see what works & scale up! And yet very few companies do it.

Dan Ariely, a behavioral economics professor at Duke University and the author of Predictably Irrational, outlined some of the resistance to experimentation that he’s come up against.

“I’ve often tried to help companies do experiments, and usually I fail spectacularly,” Ariely writes. For a company struggling with getting a good bonus system in place, he suggested experiments or even just a survey. Management, he says, “didn’t want to add to the trouble by messing with people’s bonuses merely for the sake of learning. But the employees are already unhappy, I thought, and the experiments would have provided evidence for how to make them less so in the years to come.”

But Gary Loveman managed to stay incredibly committed to Testing. These tests run from the use of coupons to offers of free meals or hotel stays, all designed to get customers to spend more money during their playtime.

This is what he said when asked about the Testing culture: “We need to overcome hunch and intuition with empirical evidence. . . . We can start with a hunch or strong belief, but we act on it through experiment. We want evidence. We’ve gone from the introduction of experimentation as a technique to a culture of experimentation as a business discipline. We hire people predisposed to do this by temperament and by background. Organizationally, we’re committed—and I’m committed—to making sure we have the discipline to have the decisions we make informed by this evidence”.

So what is the future for analytics in Gambling? Over time with data being leveraged by everyone, it was only natural for analytics to also start helping the players. Big data services quickly appeared that were designed to empower gamblers, giving them more information and helping them strategize more effectively. One such site that made full use of big data is SharkScope, which collects data from millions of online poker games every day. Players can track all their statistics on the site as a way to improve and increase their chances of winning.

And lastly we must also ask ourselves, is this kind of Analytics good for society! It’s estimated that 3 to 5 percent of people who gamble develop an addiction to the activity, which can lead to an array of problems for gamblers, their families, and society at large. Keeping gamblers coming back may hurt them & cause a lot of turmoil in many lives! Does analytics not have a social responsibility!

Your Bank can be Amazon & Google!

Roughly one in three banking and insurance customers globally would consider switching their accounts to Google, Amazon, or Facebook ,if the tech giants offered financial services, according to a new survey.

Google , Amazon & Facebook have been setting standards for degree of personalisation & powerful customer experience.

Newspapers are getting disrupted by online resources. These same web destinations are becoming less relevant as people simply lift and filter the information they want using RSS feeds. The music CD is being unbundled as customers buy individual tracks online Power has shifted to customers: it’s no longer about the products that marketers want to sell but about the content components that users want to consume & mash up together.

The new battlefield lies in the control of the user interface and the customer intelligence system that supports it. Companies that build highly equipped Customer intelligence units will win in the coming days.

The internet is disrupting retail & I am sure Retail banking is also waiting to be disrupted. According to Capgemini’s 2014 World Retail Banking Report (WRBR), less than 40% of customers globally reported positive customer experiences with their financial institution. But banks still push products on their own terms. Take a term deposit for 3 or 6 months? Well, why can’t I have it due on April 28th, which happens to be my birthday?

Google has launched its own mortgage calculator, and imagine what an Amazon Bank could look like, but who are the startups disrupting banking today? Mostly these are the Fintech companies! New age companies are very good at embedding design & personalisation into the fabric of their business.

The other thing, which the new-age companies do very well, is the notion of ‘profitable data sharing’. They do not hesitate to share data across partners to ensure their customers get a kickass solution. They share data through APIs. There are over 14,441 APIs offered by firms today, according to

Amit the Co-Founder & Chief Curator of Let’s Talk Payments had this interesting statement:  “As FinTech startups continue to disrupt traditional financial services, banks are also waking up to the fact that offering an open API—where developers can latch on and create very specific customized app solutions—is the way to engage and retain their customers in the future”.

Adaptive Path, a design and user experience consultancy has been acquired by Capitol One. And just before that Daniel Makoski, founder of Google’s modular Project Ara phone project joined Capital One.

In the new digital world, banking & creativity may not be oxymorons!

New banks in India have a unique opportunity to embed “digital” in the fabric of how they do business. But banks are complex with structures that don’t allow for speed. In many cases, eBusiness teams own the mobile banking strategy, but few eBusiness teams have an exclusive mandate over their firm’s mobile banking initiatives. This division of responsibility creates silos and adds significant complexity to the coordination and optimization of Digital efforts.

What does design have to do with finance, money and banking?

Brands that use design very effectively are far easier to spot nowadays because we interact so much with fast growing digital businesses, Ola, Amazon etc. Consumers, especially Millennials, are learning to expect more from the companies they choose to do business with. And they are not limiting their benchmarks within one industry-I want my Netbanking to be as easy as the Uber interface!

‘Project Pokhran’, as Paytm calls its payments bank project is due for launch the summer of 2017 & they may begin to look at banking very differently.

New banks in India ,IDFC & Bandhan, better be listening.

A few years ago Adaptive Path, a design and user experience consultancy was acquired by Capitol One. And just before that Daniel Makoski, founder of Google’s modular Project Ara phone project joined Capital One.

Then Capital one acquired Money management App, Level Money. The app is focused on the Millenials & helps users set savings goals & offers suggestions for what they can do with their extra cash.

Capital One recently launched what is called as Capital one Labs. This is what they call the “rogue innovation arm” of the bank. Lab members have opened a series of “Capital One 360 Cafes”, a hybrid of a coffee shop & a bank branch. Here employees interview café customers to get real time feedback on new prototypes.

In the new digital world, banking & creativity may not be oxymorons!

Some time back I came across this Job requiremnet at Capital one:

Design Strategist

As a strategic thinker with a focus on innovation for our banking business, you will have the opportunity to define, design, and develop new products and services that defy industry expectations and meet real human needs.

At Capital One, we’re building a leading information-based technology company. Still founder-­led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are

New banks in India have a unique opportunity to embed “digital” in the fabric of how they do business. Maybe some of them will come up with teams that include a “Design strategist”.

But banks are complex with structures that don’t allow for speed. In many cases, eBusiness teams own the mobile banking strategy, but few eBusiness teams have an exclusive mandate over their firm’s mobile banking initiatives. This division of responsibility creates silos and adds significant complexity to the coordination and optimization of Digital efforts.

And yet, the user experience is the key for more consumers to adopt the bank’s digital channels.

As the infrastructure of digital technology — the chips, network connections, computing — becomes ever cheaper, they’re becoming commodities, and the value of tech products is shifting to the design and the user experience. But the real value starts to flow when companies orchestrate the User experience with Personalisation.

Personalization, it seems, is really about gathering exactly the data that’s needed in order to perform a particular task. Think about how Amazon asks users whether purchases were for themselves or as gifts, or how streaming services like Netflix and Pandora ask users to rate content. But personalization is a complex process involving multiple components:

Some areas to ponder about:

  • What do you think about the internet & mobile disrupting banks? Which areas can the banks defend and which are vulnerable to disruption?
  • What do banks need to do to modernise their architectures to compete against the new wave of startups? Will they offer API’s to other brands?
  • What is the new age Customer intelligence unit that can be the nerve centre for competing in this landscape? How do they capture unique customer data & create a competitive differentiator by mapping the Customer DNA ?
  • How will banks completely transform their digital experience? Or would the new Fintech innovators show the banks the way?

It would be interesting to see how the new Indian banks & the existing players shape up to this new reality.