Lemnisk hosted a Customer Data Platform (CDP) In-Person Summit for the India region on June 15th, 2022 at Hotel Sofitel, Mumbai. The CDP Summit’s aim was to make enterprise marketers understand how they could create exceptional customer experiences using CDP-led hyper-personalization and increase their digital engagement and conversions. This article focuses on the fireside chat with Deepak Sharma, President & Chief Digital Officer, Kotak Mahindra Bank.
The key insights from the fireside chat are as follows:
Fireside Chat with Deepak Sharma
1. Why is the convergence of different functions in an organization important? From a leadership standpoint, what should be our big takeaways?
Organizations are realizing two things. One is a lot of initiatives or investments that organizations are making are failing to give a commensurate return. So that’s a question mark. When you keep investing across different aspects be it a martech stack or your data or CDP or real-time analytics, they are run by different functions of the organization. Each one has a vision of what they want to do but then it’s not adding up to the combined vision of the firm.
Second is the revenue or return that you expect from these investments. I think organizations have learned through some of these two questions what is the end outcome, why are we doing it, and why no one team or business can answer this question in isolation. I think that is forcing organizations to look at people, structure, and culture.
When you look outside, who are the incumbents that you are up against? In every industry or financial services today, you find a big tech or someone coming in and reimagining and creating a very different attacker model. The moment you look at that you realize it is something that you are doing is not right. I think apart from the internal ability there is also an outside view that is coming in now and I think both of these are driving the transition and the change within an organization.
2. As a leader, what guidance or advice would you give in terms of bringing different functions together in an organization and working them towards a common goal?
Start with outlining the key use cases and where you want to apply them such as reducing churn or increasing the product holding ratios, etc. There are key matrices and they are owned by different business owners or functional owners. The starting point is to understand from each area what are the key outcomes that they are trying to solve.
As we align the core business goals and the teams then we stitch it with the data fabric. Getting the data strategy in takes it to the next level. To see that you have got these two, what is the martech stack that you want to integrate? It should be open and not bind you with one particular provider. Because teams want freedom and don’t want to get locked in. And you also need to tell them that just because you’re working together doesn’t mean you don’t have the ability to experiment, think, and build stuff.
The data stack team knows what data they require and again brings the Context Relevance Real-Time (CRR). Hence, as long as these matrices are met, it comes back to the business teams to see how they use this using martech tools, the data that is available and convert it into business outcomes.
3. What do you expect from a martech partner? What helps you choose the right partner and do you have any guidance for it?
I don’t think there’s anything like a right or a wrong partner because we are all learning as we go along. But I think the challenge only is no one partner provides you with everything and I think that’s important and that’s why I said the stack needs to be modular. When we look at tools it needs to be easy to plug in and we should always have room to change, replace, and upgrade depending on how trends around us are changing.
Even within a CDP, there are multiple layers. We want a unified view of all our customer data. So, whether there are customers or non-customers, that itself probably is a core of some firms but not necessarily their ability to present the data in a format that you can consume. Or building the analytics engine on top of it or the reporting or activation part of it.
As long as we see that a fabric can be stitched together, I think that I would call it my number one priority because I internally keep telling that while a partner is good for today you don’t know how things will change. And I think our stack should not get locked in with a partner and I think we like to keep that flexibility and freedom with the organization to see how to maneuver over.
4. At the leadership level, there has to be a higher tolerance for failure and conversely there has to be an encouragement for risk-taking and experimentation. What are some inputs that you give to cut through this and develop that culture of experimentation which is crucial for success?
I think you’re right because when we do this before we perfect it, there will be mishaps that will happen on the way. Even in an organization, the practitioners understand better as to what they missed. A lot of times these things may even get unnoticed. Thus, not everything that you miss gets noticed.
In financial services, the risk is two-fold. You miss something and you correct it which does not cost a fortune to the firm. Keep doing it, keep experimenting. That’s absolutely fine. You’re not really setting your house on fire. The more we do the faster we do, the more mistakes we make, and the better it is for us. I would rather encourage mistakes in those areas because that’s a part of the learning process. I think where these experiments can be very expensive, especially where it’s about real money. So, I always keep reminding myself that we are a regulated entity with a high level of risk management function.
If you want to experiment, experiment small with a very small targeted piece where we can take that risk. Here again, there is no standard formula because each organization has a very different risk tolerance limit. I won’t even say how this should work because in the context of the organization one should be clear as to how much is the permissible risk that you can take while experimenting.
5. The “start small, go big” approach is easier said than done. You might not get the results you want or the results may not warrant a scale. However, if you scale, you might get different results. So, this interpretation of the outcome and this iteration, talk to us a little bit in terms of not giving up or when you should give up.
I think one of the risks we have in terms of experimentation is the risk of false positives. In some areas, false positives do not really hurt the reputation of the firm. It may still create customer dissonance. I’m not denying customer dissonance is a very important matrix but then it’s not leading to a financial or regulatory risk.
For example, we do certain personalization telling customers like you that this is the debit card that you need to upgrade to. If a wrong card is shown you will not like it, but that’s okay. But if we show you a limit on a credit card of say 2 lakhs while you know that you get a limit of 10 lakhs elsewhere is going to piss you off. Because you will say this organization doesn’t even understand what my net worth is and thereby they are giving me this link.
Therefore, while a debit card is okay to experiment but a credit limit on a credit card is not. Both are plastics but the underlying decision that we are taking based on which we run our campaign becomes extremely important for us. A lot of times we wonder why a certain campaign targeted at a good set of customers with propensity is failing to make the cut. Then you start realizing that it’s just not credit card, it can be on any product where you have a risk underwriting matrix.
Then you realize it’s not about our ability to mind that customer well but it’s our ability to use that credit risk model right? I think that at times when we run some of this, our underlying assumption decides whether we succeed or fail rather than how we stitch the rest of the stuff together.
6. Do you have any best practices that you want to share in terms of organization structure that you believe are more conducive to digital transformation?
I think the way we have been experimenting and seeing success is largely to orchestrate teams around platforms and what I call the platform operating model. A platform operating model typically brings in the business teams, tech teams, design folks, consumer insight practice, and data practice. Each team has value to add. In a typical organizational structure, the business team will expect something. Somebody will convert it into a business requirement, document it, and will look for a vendor, and get it developed.
By that time, the market would have moved and then the business team says oh no this is something I wanted three months back and now the market is somewhere else. By aligning these functions, we realize that they have a 360 view of the problem or opportunity that we are chasing.
Secondly, are you able to bring in all the relevant skill sets that are required for us to come together? Thirdly, they own the success or failure of that particular project so one cannot say I did my best but we failed it. Either we fail or we succeed together. I think as people get aligned to these outcomes, we are seeing increasingly most of our large initiatives run in a matrix structure. They are aligned to those teams and thereby we are able to cross-pollinate a lot of new ideas and experimentation and at the same time drive strategic ones.
7. What are some things that you believe are going to come to fruition in the future that you are personally excited about? What are others that you believe would sound more like a fad and may not take off?
I wish I knew really what will take off. I think we are seeing organizations morph more and more into consumer tech firms. I think where we miss the ball is the consumer. Because how well do we understand the consumer decides the success or failure of the organization? Consumer preferences or habits are changing so rapidly. Loyalty is out of the window. Customers need choice. They need to be spoiled.
The future of the firms who succeed irrespective of whatever business they are in is to bring in a very sharp consumer-led practice while everybody is scaling up the debt and data. If we are able to stitch that, we’ll be able to monetize a lot of tech and data investments and in the process, there will be few winners. But not everyone will swim and reach across the shore.
By Bijoy K.B | Senior Marketing Manager at Lemnisk