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While many companies aim to be data-driven, they struggle with the challenges of data management, building robust data strategies, and implementing AI to create differentiation in the market. Companies with effective data strategies can make better decisions, overcome data management challenges, operate efficiently, and innovate seamlessly. Couchbase and Amazon Web Services, in association with YourStory Media, held a round-table discussion to explore ‘Future-proofing the Data Strategy’. 

The panellists included Ranjitha R, Director – Engineering, Myntra; Madhusudhanan S, Group CTO & Head of Partnerships, Dvara Holdings; Akhil Sharma, Director – Product Management, Razorpay; Sundeep Kumar, Head of Engineering & Data, VerSe Innovation; Paulami Das, Director of Data Science & Engineering, PayU; Varun Khurana, Director of Engineering, Gameskraft; Saurabh Odhyan, CTO – Consumers, FreshToHome; Manish Pal, VP-Engineering, Smartcoin; Surendranath C, Senior Director Of Engineering, Gupshup; and Minakshi Khuntia, Director – Product, Freshworks; Krishna Thirtha, Regional Business Head, Couchbase; Santosh Hegde, Senior Director Engineering, Couchbase.

The challenges of data management

The round table began by looking at the challenges and solutions in data management, engineering, and analytics. Pannellists emphasised the importance of real-time data, data protection, and the challenges of data compliance.

Surendranath C, of Gupshup, shared that the company’s view of data was twofold. Firstly, Gupshup examined data from a privacy perspective, stating “we worry much more about protecting data than leveraging it. So we have different kinds of solutions for our customers, including encryption strategies, protecting data in motion, and data at rest”. The second part of Gupshup’s data strategy is leveraging data authorised for use by the customer, analysing it, extracting valuable insights, and taking action.

Varun Khurana, of Gameskraft, shared that data compliances make data accuracy a big priority for the company. He highlighted the importance of having a Single Source of Truth for data, which has helped Gameskraft aggregate all systems.

Ranjtha R, of Myntra, spoke about Myntra sellers, vendors, and customers expecting quick updates and reports. Processing and providing accurate analytics meant that the company had to learn how to move fast to create democratised data platforms on par with data governance and compliances.

Manish Pal, of Smartcoin, shared that the biggest obstacle the company faced was providing real-time underwriting with the customer data they had. The second challenge was creating an efficient data access strategy, to understand the kind of access that needed to be given to different stakeholders. 

Data as an asset

Paulami Das, of PayU, shared that the company views data as “less of an asset and more of a product”. One of the first strategies that PayU leveraged was creating a Single Source of Truth for their data. From this SSoT, engineers and data scientists could identify use cases and then offer data as a product that could solve a particular issue.

Saurabh Odhyan, of A FreshToHome, shared his experience of leveraging data to organise the massive seafood industry in India. Sourcing fish from 500 harbours across India was a massive challenge, which the company solved with data. “The seafood industry in India is a $50 billion industry. We would not have been able to solve multiple problems without understanding the value of data. We learned how to optimise sourcing, minimise wastage, and ensure that we are able to deliver fish caught at the Gujarat coast to a city like Delhi in 24 hours. We needed extremely accurate demand direction, and we were able to get it with data,” he shared. 

The importance of A/B testing 

GenZ is setting trends in many fields today. Intelligent, connected, and up to date, it is known as a mobile-first generation and significantly influences consumer preferences. Businesses are now paying greater attention to GenZ mobile usage patterns and their preferences before designing apps. In this regard, panellists spoke about the influence of GenZ and the importance of A/B testing data to help them create an immersive customer experience. 

Sundeep Kumar, of VerSe Innovation, spoke about how the company uses A/B experiments when it comes to any kind of initiative, such as new models, product features, or a product launch.

Ranjitha R, of Myntra, stressed the importance of A/B testing in ecommerce. She wades through a massive amount of data to understand the trends (both macro and micro) in fashion. She recommends A/B testing to roll out website features to appeal to GenZ. “How do I create a cluster of people catering to certain attributes of affluence, age, or geography, and then see it really works? A/B testing becomes really important to how I obtain data and then categorise it,” she shared. 

Customer data verification in lending

The world is rapidly digitalising, and lending isn’t far behind. While digital lending brings speed and convenience to customers, it also comes with risk – particularly identity fraud. Identity verification is crucial for lenders, but it can sometimes be difficult given the increasing incidents of fraud. 

Fintech Panellists from PayU, CoinDCX, Smartcoin, and Credit Saison shared their experiences on handling fraud and implementing checks in the customer KYC process, customer consent in the underwriting process, and access to data from credit bureaus.

Madhusudhanan S, of Dvara Holdings, spoke about the challenges of accessing customer data in rural regions. “We go by assessment-based loans. There is no digitisation, so you have to depend on the field staff visiting and trying to assess family members. In these cases, how many family members are present? What are their occupations? It’s extremely difficult to verify. Everything depends on what the customer writes. This is the reality of loans under Rs 3 lakh,” he said. 

The panellists agreed that verifying customer data requires alternate sources. Poulomi Das, of PayU, pointed out, “There is a lot of pressure to get alternate data. The industry will not survive without it. So it’s a very delicate balance between how invasive you want to be, how deep you want to go into a customer’s data, versus what the government will allow you.”

The final point discussed was around data sharing. Panellists discussed various initiatives to create a common data-sharing framework, including the RBI Unified Lending Interface (ULI) platform, which facilitates the seamless flow of a customer’s financial and non-financial data from various data source providers to lenders. They also cited examples, such as RBI initiatives to share land records, private players who offer satellite-based data to agri lenders, and data clean rooms for secure data sharing.

At the end of the discussion, Couchbase shared how the distributed NoSQL multi modal database is designed for adaptive applications, combining the flexibility of a document-oriented data with an integrated cache (memory first architecture). This brings in unmatched versatility, performance, scalability, availability and financial value into the application landscape.