By R Chandra Mouli
“The world’s most valuable resource is no longer oil, but data,” The Economist declared in a 2017 report. Here’s how companies are leveraging data:
Imagine a Bank, Insurance Company, OTT channel or a telco with millions of customers, each with their own attributes, in terms of location, income, age and propensity to consume specific social media channels.
Now imagine talking to every customer personally with a customised message… If the personalisation is accurate, reach out is right and content credible, the upshot can be dawn of a modern-day mantra that epitomizes Marshall McLuhan’s “Medium is the Message.” If he was around 60 years later to rewrite his iconic book, the title may well be ‘Data is the New Oil.’ It is here we enter the crux of this narrative.
Managing Directors, Group Chairpersons, CMOs and CTOs reading this are likely to quip – hey, we figured out the relevance of data long ago, and will you please stop carrying coal to New Castle or lignite to Neyveli.
What if I concur and end the Column right here? Diverse verticals with data quantum that exceeds a quintillion could lose the opportunity to revisit their parsing strategy, and miss out on an all-new way to connect almost any data source to a consumer touch point.
For the benefit of veterans, millennials, GenX and Gen Alpha, and with the goal of integrating divergent data among a diversified segment of disparate customers, I shall sustain this evangelist tone, and enumerate what I have recently learned… about continuing the conversation with the end customer.
Business Intelligence has been around for over 25 years, only the labels have changed with the times, and today we rechristen the archetype or prior model as Data Analytics and Big Data (remember management grads poring over spreadsheets in the 90s or media planners analysing Audit Bureau of Circulation figures or National Readership Survey data?).
In the world of Web 3, enterprises with mega number of customers are hard-pressed to find new ways to interpret data and discern a behaviour pattern which in turn could lead to innovative ways of reaching out to the TG.
The newest is Sentiment Analysis – which relies on Social Listening, Social Monitoring and Customer Experience Analytics. An easy-to-understand example would be Hashtag Monitoring to assess negative expressions of a customer experience and the brand taking corrective action.
Conversely, a trending hashtag celebrating a CSR effort can be amplified as in the recent case of an industrialist gifting a home to “Idli Amma” in Tamilnadu, or using relevant hashtags and outstanding content to create visibility even among non-followers.
Another segment is analysis of First Party Data, ie. information that is residing with the client, such as a telecom subscriber base wherein details have been captured at the time of sign up, an edtech company which has obtained details of the trainee’s educational background and skillsets, or a bank with access to the retail customer’s age, income, monthly float, funds in deposits and lockers rented at the click of a mouse. Such data when uploaded and analysed on a martech cloud or marketing automation platform can assign more than 100 attributes (behaviour patterns), which means you can now customize your message without making personalisation appear obvious.
A legacy company with data collected over the years may seem most appropriate for this exercise. Right and wrong. The technology works for a crypto exchange at an early stage, or Non-Fungible Token marketplace launched three months ago. Such late entrants will do well by beginning data capture and continuing the conversation all through the customer lifecycle.
If the flow till now hints that Data Management is only for B2C, it is a fallacy that I have inadvertently created and shall make amends by revealing the value and utility for multiple models – B2B, B2B2B, and B2B2C (example a business targeting another business, or a portal like Amazon on which small businesses perch to target the end consumer).
At this point you may wonder how and where I get my insights. The answer is research, reading and interacting with new-age professionals. Another avenue is in-depth analysis of case studies to unearth emerging trends and simultaneously spot outdated technologies, the irksome use of which continues because a set of reluctant CTOs are resistant to change.
The ultimate trigger to delve deep into data analytics was a catch-up call I had with a highly successful lady entrepreneur who had worked with me as a trainee 30 years ago. Her journey is like a dream, or so it would seem, until you know how much harder she had to work to overcome challenges while launching a digital marketing start-up in Singapore 20 years ago, and how Herculean it was to take the decision to morph from a service enterprise into a tech platform, a calculated risk that has now positioned her company as a leader in data management techniques detailed above.
Impressed by her credentials and a use case where her company manages over 50 million customers of a private sector bank, her revelation that for almost 900 corporate customers they deliver 23 billion communications every week (not a typo), and that their tech platform powers an all-new consumer app launched in April by one of India’s biggest conglomerates, I asked her how much farther she can go, and she said simply: Infinity.
Currently, she has proposed a data management model to a business group, which if you name a domain is active in it – automobiles, aerospace, boat building, farm equipment, construction equipment, clean energy, IT, financial services, retail – and that’s just half the list.
The proposal suggests that customer data, residing in silos across Group companies, can be brought under a unified Audience Data Platform, which would enable personalised cross-selling rather than a mass reach out on the oft-overrated premise that all group customers are one big family.
True in a way, but the customer’s view can be what’s in it for me (example preferential allotment of shares to existing policy holders during a recent insurance company IPO). It is here analysis of attributes can make a significant difference (if you have a propensity to use Twitter more than say FB, that is tracked and recorded as an attribute and hence your touch point is likely to be a tweet, or if you order an onboard meal every time you fly that’s another trait noted and actioned – such as “6th Order is on us!”).
As my one-time trainee who now heads a company ranked for last 5 years in the Gartner Magic Quadrant wished me well at the end of the call and reiterated her mission to enhance customer engagement through AI-driven insights, I had a vision… of pioneers such as she heralding an omnichannel marketing revolution through deployment of smart digital and user-centred personalization.
Given their mastery of technology and inherent adherence to compliance, I expect the wave to be seamless – we won’t know who’s talking or stalking.
(The writer is a communications consultant, columnist, and former journalist. Views expressed are his own and not necessarily that of FinancialExpress.com)
