Maturity of customer data: Aditya Birla Sun Life Insurance
Rajiv Malhan is Head of Strategic Projects and Business Transformation at Aditya Birla Sun Life Insurance. He tells Qorus and Wavestone how they utilize data in order to enhance their customer experience.
Rajiv Malhan is Head of Strategic Projects and Business Transformation at Aditya Birla Sun Life Insurance. He tells Qorus and Wavestone how they utilize data in order to enhance their customer experience.
In your opinion, how does use of data and the personalization of offers and paths respond to development or loyalty issues for organizations? What transformation does this evolution pre suppose?
The personalization area is becoming more and more interesting as customer is spoilt by the choices and options available. Mindshare of customer is getting narrower and organizations need to ensure their brand recall value be maximum.
Focus on marketing and product only cannot fulfill this aspiration, organisations need to treat and serve the customer as an individual. There is a term called n=1, means every customer has individual identity to be taken care and served on, hyper personalization and hyper customization for that “n” customer is what will keep customer stick and stay loyal to the brand.
Organizations need to work on customization and personalization using accurate data sets procured from the footprints of the customer (with due approvals on data privacy and customer consents). Need to create specific products & services for customers while understanding their needs and offer solutions proactively and accurately.
Simplified customer journeys within eco-system of customer will also play critical roles in creating loyal customers.
What types of data are your personalization use cases based on? How do you enrich them?
In BFSI sector (Banking, Financial Services, and Insurance sector), customer has a deeply engaged and extended journey. Due to various proactive and other engagements, good amount of data is generated across customer life cycle. Apart, social media can also provide relevant customer information (with due approvals on data privacy and customer consents).
There can be use cases to reach out to customer at different milestones of their life and be available to serve. For example, different milestones for a bank can be - a student opens a bank account – started getting salary credits – nominated spouse for some product – transactions related to kids – transactions related to hospitalization and so on. Same ways a life insurance or health insurance organization can also predict the need to increase protection levels..
Once need is established, machine learning algos can guide how to engage with customer with what particular nudge. Basis relationship quotient of customer with organization, further customer journeys can be crafted to enhance customer experience.
Which data use cases you particularly feel can be game changer for BFSI sector ? On which customer/employee situation ? What are the expected/measured ROI elements?
Data sets provide customers’ personas, their beliefs, values, expenditure behavior, patterns on responses to different situation and so on. If organisations are able to listen to customers well, provide proactive solutions, simplify customer journeys, engage with in their eco-system as per their demand and provide vow customer experience, then customers will surely evaluate all these factors before switching to other option.
I am personally looking forward to technologies like Speech to text analytics, Messaging services to replace mobile apps, Facial scan analytics, Voice analytics, Propensity modelling and Customer 360 degree tools like Relationship Quotient. Technology is making large computation possible so AI-ML algos will provide sharper insights to customer behavior enabling organisations to serve customers proactively resulting more loyal and sticky customers.
ROI will obviously be higher retention, higher collection and engaged customers who can also influence others to pick up the brand.
What are the main obstacles and/or key success factors you are facing in their development and/or deployment?
Data cleanliness and the accuracy are critical for creating workable data sets. Getting correct data is a challenge, and whether these analytical tools can help providing right set of predictions is another.
Models can provide only those outputs to which they are trained to, apart from data scientists organisations have to create pool of those business guys who can articulate the clear outcome. Expectation from data scientists is to create magic and give solutions to meet organizational goals. Fair expectation, but to train models and tweak outcomes, there has to be a team who can help training those datasets in the required fashion. The person who is helping these data scientists should be someone who has worked with the customer-facing teams.
More generally, what is your view of maturity of BFSI sector in India with regard to the personalization of paths and offers?
Fintechs/Insuretech are working on amazing use cases in India. Availability of internet in tier 3 and t 4 cities have helped larger set of consumers to transact digitally. But with every use case new opportunities are also cropping up to work on. Govt of India is also focusing on digitizing services, very detailed work is done/wip in this area. Digitising of public records and availability to right set of organization will help digitizing more and more transactions with more and more accurate data getting generated.
Good days ahead in terms of digital products and services with hyper personalized touch.
Is there anything else you would like to highlight?
BFSI sector also needs to groom talent who can understand customer behavior and their changing preferences. Customers are exposed to so many choices with many promises, making it confusing and non-directional. Making a right choice is becoming difficult and many times it ends up in either non value added or an expensive option. Data and technology shd also help customer pick up the right fit with right budget.
Again reiterating on the point of customer journeys. Due to availability of digital options its very much possible to provide simplified customer journey with in the eco system of customer as and when asked for. Executives involved or with experience of managing customers should also be involved in creation of journeys because they are the people who will execute those plans along with frontline.
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