Customer Experience -the Amazon,Uber, Google way!

I have always believed that words like Customer centricity, Customer experience,Customer obsession etc are all fluff unless there are changes in the company’s operating model. Unless customers are given a place in the boardroom, it isn’t likely that we as consumers would sense a difference, despite all the analytics & technology at play. There is this anecdotal story about Jeff Bezos at Amazon leaving a seat vacant at every important meeting & telling everyone to treat that vacant seat as the customer in the meeting.

Now, companies have petabytes of data & a plethora of technology choices with which they can analyze this big data & get big insights. But the rubber meets the road, when the customer gets a better experience because the “customer data ” enables it!

Today I addressed a webinar at the Super CX week organized by Oracle.

Customer experience is changing as a concept & is creating large opportunities for companies who truly believe in bringing the customer up front & centre. Remember, it is easy to talk about Customer obsession rather than embrace it.

India now has close to 450 million Internet users. In fact, we now have over 440 million Millennials & over 390 million Gen Z consumers(born after year 2000). These consumers think very differently & have very different expectations from brands & companies.

And these youth have a social megaphone that allows to wrest the bargaining power towards them!

This leads to a whole new way of Marketing & these are the trends that I see:

  • Marketing will move towards relevancy
    • “Marketing that is done so well that it feels like a service”-To service is to Sell
  • “Marketing as a relationship”
    • Customers would only respond to “profitable conversations”
    • No one wants a relationship, unless it is relevant
  • Mass customization: segmentation to increase dramatically
    • From 3-5 segments that most businesses maintain to lights-out, automatic modelling that is driven by the data
    • Segment of 1

Delighting customers doesn’t build loyalty; reducing their effort—the work they must do to get their problem solved—does. How do companies embark on such a journey.

A few points to consider:

  1. Support an institutional memory of the customer-different silos or “lines of business” creating campaigns & running them independently means that you do not have a centralised contact history or “intelligence” about customer response
  2. Enable dialogues not just campaigns. If campaigns are seen as just “list pulls”, then anyone who knows basis SQL should be able to do the job. But the consumer is no longer ready to listen to “push marketing” & the creation of a “dialogue factory” is one essential element of a strong Customer strategy
  3. Establish a strong Customer management council: group of top leaders in the company who are able to mediate to solve the issues that arise out of taking customer centric action. This council becomes a strong enabler for Campaign management playing a differentiated role.
  4. Being loyal to customers & not the other way around (customers needing to be loyal to the company). This needs companies to have a longer term view of customer lifetime value & not a short term view of immediate profit. It needs an internal senior level stakeholder who champions the customer cause (CMO?)

Two years back Gartner predicted that by 2017 CMO’s will spend more on IT than CIO’s. Is this happening? So how big is the market for marketing software today? IDC has an answer to that question, $20.2 billion in 2014. IDC expects that the market will have a compound annual growth rate (CAGR) of 12.4% for the next five years, resulting in a $32.4 billion market by 2018.

I would urge CMO’s & CEO’s to first articulate & get board level agreement on a differentiated Customer Strategy. Make Marketing technology & team structure investments after that.

Here is a copy of my presentation at the Super CX week organized by Oracle today. Hope you will evangelize some of these concepts at your company.

Customer Experience Oracle

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.”

http://www.nytimes.com/interactive/2010/11/13/weekinreview/deficits-graphic.html

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 Amazon.com, 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 Amazon.com 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 programmableweb.com.

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
 succeeding.

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.

Customer journeys are not good enough, we need Customer context!

It’s a rainy day in Mumbai & my daughter is furiously multitasking to find fashionable rain coats. She is looking at customer reviews & social networking sites & is on Flipkart & Amazon too! All of them know she is from Mumbai, in some cases they have profile information from her registration data but none of them suggested she buy other stuff that she may need in the rains: Boots, umbrella!! Marketers need to understand the context in which consumers are & today there is enough data to give you insight on this. Retailers like Flipkart could have further used marketing campaigns across email, sms, in app, browser push to tell her more about expected weather in Mumbai over next 3 days & also providing her recommended brands to buy.

Consumers reach out to brands in many ways. India has 1.03 mobile connections & over 350 million internet users. Consumers connect with brands for a wide variety of reasons. Consumers want more information, improved service & better deals. And technology is making it easier for consumers to connect with brands. By 2020, the average person will have more conversations with bots than with their spouse, so says Gartner. They also say that “New audio-centric technologies, such as Apple’s AirPods, Google Home and Amazon’s Echo, are turning “voice first” interactions into ubiquitous experiences. By eliminating the need to use your hands and eyes for browsing, vocal interactions extend the web experience to multiple activities such as driving, cooking, waking, socializing, exercising, operating machinery.

context marketing

Today’s omnichannel customers will end up using the retailer’s touchpoints, in all permutations & combinations. Not only will they use smartphone apps to compare prices or download a coupon, but they will also be users of in-store digital tools such as an interactive catalog, a price-checker, or a tablet. Consumers will buy online and pick-up in store, or buy in the store and get their purchases shipped. Some research done by HBR has shown that customers who used 4+ channels spent 9% more in the store, on average, when compared to those who used just one channel.

Always connected customers can’t be pigeonholed into linear journeys. These consumers automatically turn to their phones in search of information, whether they’re at the gym, commuting to work, or shopping for groceries. Google refers to these spontaneous instances of discovery as micro-moments.

But even while consumers are finding increasing number of ways of reaching brands, companies struggle to provide them a seamless experience as they use these myriad channels.

This is further complicated by the emergence of communication channels that rely on proprietary standards — like Apple’s iAd, Android’s open architecture, and Facebook’s platform.

Each channel tends to be used by it’s distinct customer segments-like customers in the older demographics who are using i pads or multi device using millennials & so messages need to be customised to appropriate customer journeys.

Banking customers often struggle to engage seamlessly with banks. Citibank saw that an important concern of customers was to stop any charges on their card after it was lost or stolen, the company introduced Citi Quick Lock that allows users to quickly lock their card from a mobile app while they look for it.

None of this can happen unless companies start to change structure & processes keeping the customer at the heart of the thinking.Overseeing all of a firm’s interactions with customers is someone in the role of chief experience officer, a relatively new position in the C-suite. Chief digital officers are also starting to have this top-level responsibility. Marketers need a structure within their teams that brings the customer journey up front & centre & connects it with context!

As all of your products and services generate more and more data, the resulting context gives you the opportunity to disrupt your competitors. Also today consumers are allowing marketers to know their location. Since 2014, the number of Internet searches using a “find the nearest” term has doubled. Customers are also beginning to see the value of revealing their location in physical environments. The number of connected devices is growing by 15% to 20% per annum and will reach approximately 30 billion in 2020.Many devices, such as mobile phones, cars, and wearables, constantly monitor their user’s location, so the volume of inbound, spatially related data has never been greater. So the ability to further drive relevance by using location context is becoming real! Marketer’s need to be conscious to not overdo this & risk looking “creepy” to consumers!

McCormick developed FlavorPrint, an algorithm representing the company’s flavors as a vector of 50 data points. FlavorPrint helps consumers decode the flavors they already love, and invites them to discover, share and bring new flavors into their homes. FlavorPrint site has a simple promise: Tell it what you like, what ingredients you have, and what cooking equipment you have, and it recommends recipes. Those recommendations become finely tuned to your context as you continue to interact with the site. McCormick’s now partners with retailers and food suppliers, as well as social media networks and third-party services like Foodily, to create more relevant customer experiences.

Over the next few years or so, we’re likely to see a radical integration of the consumer experience across physical and virtual environments. Mckinsey research says that by 2016, the web will influence more than half of all retail transactions, representing a potential sales opportunity of almost $2 trillion. All this will drive marketers towards using “consumer context” in all of their marketing engagements. Many industries have a large opportunity in looking to align their Marketing with the context in which consumers discover, buy & experience their products & services.

Forrester calls this Context based marketing:

“For all the activity you try to catalyze through campaigns, individuals more commonly interact with your brand outside of those campaigns. They may learn about your product or service prior to purchase. Then they’ll use your product, connect with others, and even organize activities around it. They spread word of mouth, positive or negative — and that, whether you
like or not, is your actual brand image.The context of all those interactions determines whether they will engage and, more importantly, transact with your brand again. Marketing’s job now is to identify and use context to create a repeatable cycle of interactions, drive deeper engagement, and learn more about the customer in the process. The more marketers can internalize and act upon what they learn, the easier it is to make future interactions that much more engaging”.

Many businesses will create data led marketing advantage as they build competency in storing , interpreting & taking action on these vast terabytes of context data. Contextual marketing will yield a new form of “owned data” that is generated from the interaction cycle. Smartphone owners pick up or glance at their mobile phones 150 to 200 times each day, spending on average over two hours a day accessing apps and websites. This leaves a huge data trail behind as well.To get the full customer portrait rather than just a series of snapshots, companies need a central data mart that combines all the contacts a customer has with a brand: basic consumer data plus information about transactions, browsing history, and customer-service interactions.

But to do this CMO’s will have to take charge & demand a level of technology hitherto not seen in the Marketing department.And yes, 2017 is the year when Gartner predicted that CMO’s will spend more on IT , than CIO’s!!

Airbnb & the art of analytics storytelling!

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 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 them “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. Rudyard Kipling once wrote that if History was taught in the form of stories, it would never be forgotten.” In her persuasion & power of story video, Stanford University Professor of Marketing Jennifer L. Aaker explains that stories are meaningful when they are memorable, impactful and personal. Have a look at this wonderful story told by Jennifer.
http://bit.ly/1iqcvin

Stories are the best way to influence! But we don’t see them being used so often. Analytics doesn’t need you to solve only a technical problem but a “social” one. Analytics is sexy but for it to make an impact, it needs to be embedded into the fabric of the company. This calls for analysts to become more social & in fact better presenters & story tellers.

They need to learn to demystify analytics & link it to practical ways for the business to make money! And analysts need to learn to link their work to “the last mile”. Analytics should not be expected to deliver a “Aha moment”, instead it should be a “factory approach to improved decisions”. So analytics is not just a planning tool as much as it is an Execution tool to improve the customer experience & business impact. Start with a decision in mind & work backwards, not with the data in mind & working forward. And today with reams of external data available to most marketers, analytics can even mash up different kinds of data & improve the Customer experience.

Compare the analytics industry with the world of journalism. One of the most deadline filled industries in the world is getting it right with what it calls precision journalism! Despite crazy deadlines, I am amazed at the powerful stories journalists write using data. I wish the analytics industry was half way as good!!The corporate world needs to learn from this & use data to tell stories better! Journalists are coping with the rising information flood by borrowing data visualization techniques from computer scientists, researchers and artists. Some newsrooms are already beginning to retool their staffs and systems to prepare for a future in which data becomes a medium.

Analysts are often tempted to communicate how they did the analysis: “First we removed the outliers from the data, then we did a logarithmic transformation; that created high autocorrelation, so we created a one-year lag variable”—& the typical business user is already yawning! The audiences for analytical results don’t really care what process you followed; they only care about results and implications

Here is an example of a master storyteller. Many people employ static charts, but visual analytics are increasingly becoming dynamic and interactive. Hans Rosling, a Swedish professor, popularized this approach with his frequently viewed TED Talk that used visual analytics to show the changing population health relationships between developed and developing nations over time. Rosling has created a website called Gapminder (www.gapminder.org) that displays many of these types of interactive visual analytics

In early 2010, The New York Times was given access to Netflix’s normally private records of what areas rent which movies the most often. While Netflix declined to disclose raw numbers, The Times created an engaging interactive database that let users browse the top 100-ranked rentals in 12 US metro areas, broken down to the postal code level. A colour-graded “heatmap” overlaid on each community enabled users to quickly scan and see where a particular title was most popular.

See more at: http://nyti.ms/1iCAQnp

Brent Dykes has this wonderful take in a Forbes article & I quote:

“It’s important to understand how these different elements combine and work together in data storytelling. When narrative is coupled with data, it helps to explain to your audience what’s happening in the data and why a particular insight is important. Ample context and commentary is often needed to fully appreciate an insight. When visuals are applied to data, they can enlighten the audience to insights that they wouldn’t see without charts or graphs. Many interesting patterns and outliers in the data would remain hidden in the rows and columns of data tables without the help of data visualizations.

data analytics

storytelling with data

Finally, when narrative and visuals are merged together, they can engage or even entertain an audience. It’s no surprise we collectively spend billions of dollars each year at the movies to immerse ourselves in different lives, worlds, and adventures. When you combine the right visuals and narrative with the right data, you have a data story that can influence and drive change”.

change management

Creating organisation changes through storytelling

Also today Marketers have access to a lot of external data. How they mash this up creatively with their own data & produce features that are of value to consumers is going to become very important in the days to come.

Here is an example:

How Airbnb can add more value to its consumers?

Airbnb is making travel easier for its consumers & today they have access to a lot of data that can make the consumer’s buying process easier!There is a lot of data available about city neighbourhoods.I thought of this particular example because of  Ben Wellington’s article in The New Yorker. He used data points from New York City noise complaints not only to map out which neighbourhoods were noisiest, but why they were noisy.

Noise data

New York data

From the screenshot above, you can see that you’ll definitely want to steer clear of two neighbourhood near the Bronx if you hate the sound of ice cream trucks.
How can this help a Marketer?: Imagine if this led Airbnb to import this data & use it to help you in selecting a place to stay. I am fresh from staying in Singapore in an Airbnb apartment which was in a noisy neighbourhood. If this can be created into an index which pops up as I view an Airbnb apartment, it adds another data based layer to my decision of which apartment to choose. You can enhance this with other data like Crime in the neighbourhood etc & suddenly data is actually adding much more value to the AirBnB platform.
So if data based storytelling can be linked to “How customers buy” , that can hugely enhance a customer’s experience & value. Think about how you can do this in your business & use storytelling to impact key decisions in your company & also your customer experience.