How data can improve customer experience

Data analytics has been changing the game for service providers when it comes to customer experience - technological disruptions are increasingly focusing on personalisation and optimising the user experience. Data mining and analysis have a vast potential in further fine-tuning processes and practices for better outcomes.

From targeted advertising to back-end solutions, data-driven AI/ML systems have been transforming the way the customer experience plays out. Companies are embracing the shift and implementing more data solutions to optimise their offerings. Efficiently collecting data through digital channels and making it actionable by presenting the insights so that they can be leveraged to drive business decisions is crucial at this juncture. It gives companies the ability to hone in on the right demographic to address, as well as better understand customer needs and deliver accordingly.

Customer experience

The customer journey begins when the first contact is established between the customer and the company. It is defined by multiple touchpoints along the way and in order to truly enhance the customer experience, these instances need to be optimised. The aim is to create ‘customer delight,’ which refers to surpassing customer expectations and leaving an overall positive impression. Transforming data into information and creating value for customers at every touchpoint can establish brand identity and loyalty, which is extremely important for any customer-facing company.

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With the right implementation, harnessing data to optimise customer experience holds transformative potential for companies. Data-driven customisation helps companies reach the target audience, and personalisation can boost customer satisfaction. In fact, McKinsey published data indicating that companies focusing on customer experience and digital transformation practices drive their customer satisfaction levels up by 30 per cent and boost revenues by up to 50 per cent.

Role of data analytics

Data analytics has revolutionised the way service models are developed and implemented to deliver a better customer experience. To capitalise on this emerging opportunity, it’s crucial for companies to understand their target audience and the pain points that need to be addressed in order to seamlessly integrate them into the service model. To this end, data mining and analytics can provide useful insights to better understand and therefore cater to the specific requirements. For instance, a data-led, AI/ML-based credit decisioning model can facilitate fast and unbiased loan approval, resulting in quick and efficient disbursements. This translates into customer delight in the form of a hassle-free business loan process and quick turnaround time that can help MSME customers tackle sudden expenses, as well as make the most of short-term opportunities.

Granular data also helps to understand the profile and repayment potential of a customer, therefore minimising the need to rely on traditional methods of assessing creditworthiness like credit score and history. This facilitates the underwriting process, helping to provide collateral- free loans to small businesses, even those that are new to credit.

Need for checks and balances

The tech transformation that has been unfolding across the country has been bringing a new crop of customers on board through digital channels. As the customer base expands, the need for checks and balances to ensure data security and privacy for them is growing as well. Data is increasingly being harnessed to improve the customer experience and has the potential to transform the face of digital service delivery going forward. However, there is a need for proper frameworks and compliance to ensure that sensitive data is not compromised in the process. The recent RBI digital lending guidelines are with the aim to protect the borrowers and are a step in the right direction for NBFCs and other lenders who are registered with the RBI and in compliance.

There is a need to follow best practices in order to maintain sanitation and privacy as more data get harnessed. Compliance is crucial to maintaining high standards of data privacy and security, as is staying on top of the changing tech requirements. A crystal clear data privacy policy to ensure transparency for customers is a necessary part of collecting and utilising data

(The author is the Founder and CEO, Kinara Capital)