AI and data: Transforming customer experience like never before

In today's competitive landscape, brands aim to maintain proximity to their customers in every possible manner. To achieve this, brands are increasingly using artificial intelligence (AI) and data analytics to enhance the customer experience.

By harnessing these technologies, brands can deliver personalised interactions that not only meet but also anticipate consumer needs, fostering loyalty and satisfaction.

Unlike traditional methods that rely on static data or broad demographic segments, AI adapts dynamically to individual users' behaviours and preferences. This allows businesses to create interactions that feel intuitive and relevant, significantly enhancing customer engagement.

To delve deeper into this, a panel discussion titled 'Leveraging AI and data to personalise customer experience' took place at the afaqs! Customer First Summit.

The panel featured Ashish Tiwari, chief marketing officer at Home Credit India; Deepak Oram, senior VP of growth marketing and martech at HDFC Bank; Dr. Davy Jindal, AVP of growth and strategy at CK Birla Healthcare; and Shashishekhar Mukherjee, head of digital marketing at Reckitt. The discussion was moderated by Namit Agrawal, marketing lead for Data, AI, and DX Cloud at Salesforce.

Mukherjee revealed that Reckitt employs AI to analyse intricate consumer behaviours. The brand, operating in the FMCG sector, gathers data from various sources including field forces, shopping panels, direct distributors, and D2C stores.

The brand enriches its data through martech platforms to effectively target consumers with greater discretionary income, he said.

“Take Dettol antiseptic liquid, for instance—a household staple with a role that evolves through life stages. From bringing a newborn home to a child’s first crawl, or even when a mischievous kid bruises a knee, each moment presents a unique opportunity. AI helps us identify these consumer touchpoints, tailor our propositions, and connect with consumers on platforms of their choice—making our brand a part of their everyday journey," Mukherjee said.

Dr. Jindal highlighted that AI is transforming the healthcare industry, extending its impact beyond clinical applications to enhance patient acquisition, engagement, and retention.

“At BM Birla Heart Foundation, our tele-ECG programme uses AI to monitor peripheral ECGs, flagging critical cases for doctors. AI bots now handle patient queries, reducing human intervention and empowering decision-making. By analysing discharge summaries, AI also identifies high-risk patients, enabling proactive, out-of-hospital care,” he said.

Oram from the banking industry emphasised that personalisation has shifted from being a luxury to becoming an essential expectation. Banks utilise data from card transactions, online browsing, and app interactions to gain insights into customer intentions.

He added that integrating financial data with digital behaviour enables banks to anticipate customer needs, provide tailored credit, loans, or investment solutions, and detect dissatisfaction through patterns in complaints. This approach boosts sales while improving customer service.

Tiwari of Home Credit India noted that while AI has recently gained popularity, the financial sector has been utilising it for many years. Risk modelling plays a crucial role in lending, with underwriting models utilising data and algorithms to streamline decision-making processes.

Data science is increasingly being utilised not only for decision-making but also for enhancing personalisation. Financial products lack differentiation, as money from an ATM or a bank loan feels identical. Therefore, personalisation is essential. Understanding consumer needs and risk profiles is essential for providing appropriate interest rates and customised communication.

Mukherjee highlighted that the approach for engaging consumers in real time involves the team making dynamic adjustments to pricing and promotional discounts during sales events.

“These are rule-based engines, whereas traditionally, people would download the data, analyse it, and adjust trade spending accordingly,” he added.

He said that AI enhances the outcome-based model by maximising input over a specified timeframe. Interacting with data allows for the optimisation of trade spending, ultimately driving maximum sales. The team can implement real-time upselling strategies to address a slight decrease in average order value (AOV) and achieve target goals.

Jindal pointed out a significant challenge in the healthcare sector: the extreme privacy of health data, which leads to individuals' reluctance to share their personal health information. The government imposes strict regulations on AI, requiring the anonymisation of personal data.

“The ethical challenge we will face is ensuring that patients have given explicit consent for their data to be used in AI models or for any future applications,” he said.

Listen to the full conversation here: 

We would like to thank our partners:

Digital Experience Partner:

Salesforce

Gen AI Partner:

Chat360

Co-Partner:

Zoho