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.

 

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!!

How banks are missing the “millenials” mark?

“Banking is essential, banks are not,” Bill Gates, then CEO of Microsoft, famously said in 1994.Mobile phones, however, are essential. And many of us today are doing a majority of our banking transactions on the mobile.

Forrester had this interesting thought –“The moments that characterize the mobile mind shift are getting shorter. Simple triggers — messages, sounds, even tactile sensations — spur consumers to take action, both on devices and in the real world”. Forrester defines this quick-reaction subset of mobile moments as micro moments.

Millennials are digital natives — the first generation to have grown up with Internet-enabled devices and digital technologies — and they expect real time engagement with brands.

millenials 1

According to a study by Viacom Media, banking, as an industry, runs the highest risk for disruption. 53% of the Millennials they surveyed said they didn’t think their bank offered anything different than a competing bank. 71% said they would rather visit the dentist than hear what banks have to say. 73% would rather handle their financial services needs with Google, Amazon, Apple, PayPal or Square than from their own national bank.

India has a strikingly young population, especially compared to China. It has 440mn Millennials, larger than China (415mn).

So what must banks do to engage better with the Millennials :

  1. “To service is to sell” will be the new philosophy

Banks will leverage the rich customer data to “service first” , rather than sell. Sales will happen because banks anticipate service moments that lead to a sale. This will need appropriate technology investments for banks to sense “customer moments” in real time & respond to them. Millennials will demand that. Customer service may completely morph with Marketing into a Customer Experience function. More importantly banks will need to control their “push selling” paradigm. Regulators may help by mandating an end to “mis- selling” …but that may not happen anytime soon. More progressive banks will regulate themselves & move to this new philosophy! Banks have huge data that signifies a “service need moment”-eg providing an NOC to an auto loan customer without any follow up. Also picking up a credit card airline transaction & converting that to a bunch of “partner privileges & offers for that country”.

Again research shows that “marketers will build their own contextual marketing engines to connect with customers not through campaigns, but through ongoing interactions. To do so, they will have to combine systems of insight and systems of engagement”. So the mass & blast campaign management will change & instead much more relevant service based messaging will engage customers.

2. Become “Gurus”
Financial marketers have a clear opportunity to become financial gurus to Millennials. This generation is hungry for knowledge, is ready to learn digitally, and would prefer simple, easy to understand content to make better decisions about their lives. But this content has to be created to connect to Millennials.
Bank of America’s initiative “Better Money habits” launched in collaboration with the non-profit Khan Academy is one of the examples of interactive education resources targeted at the Millennials.      http://bit.ly/1xce4Uv

3.Think ‘Outside the Bank’

 Millennials are the experiential generation. They focus on today’s needs and take on debt for vacations or education. Research from Facebook IQ has shown that Millennials tend to show off not through the ownership of things but through experiences. How can financial marketers leverage this knowledge to bring an “experience edge” to their marketing. American Express provides its members with live streaming concerts on its unstaged website, and Chase treats some of its Sapphire cardholders with VIP access to music shows who can then share their experiences via social media.

http://bit.ly/1KPmY0N

None of this is new & brands should find more exciting partnerships – with writers, photographers, Theatre artists, social sector leaders, and other influencers. Research shows that “Such collaborations could result in storytelling initiatives with advice on different experiential topics in connection with financial matters behind them. Communications should be built not so much around a transaction, but rather all the exciting things you can do with it”.

4. Tear down the silos

Define, and start executing an overall payment strategy. Not only is responsibility for payments split between retail and business banking teams, but even credit cards and debit cards are often run by separate teams. Marketing tends to be a central team but may not have as much authority across silos to own a consistent communication paradigm.

5. Embed analytics into Mobile banking: 

Help customers see an accurate forecast for their spending. DBS digibank leads in the Indian market with its budgeting and spending tool. This allows customers to manually categorize transactions and autopopulate transactions like bill payments; they can also choose to receive email alerts when they hit 70% to 90% of their budget. DBS digibank also provides a basic saving tool to enable customers to assess their spending and save money. In terms of advice and planning, ICICI Bank offers customers a few useful tools, such as calculators for mortgage payments, investments, and pensions.

Mobile banking offers the opportunity to cross-sell to existing customers and to promote additional services. “Yet few banks use the context of a customer’s current product portfolio,recent life events, location,past behavior,and other factors to offer personalized marketing in their mobile apps”.