Amin Lakhani says India’s marketers must outgrow their data FOMO

New Delhi: Imagine this: You’re a brand in India, trying to reach 100 million consumers scattered across metros, Tier 2 towns, and the vast vernacular hinterland. You know digital media is your playground, but there’s a catch. Consumers are no longer passive; they’re aware, wary, and increasingly protective of their personal information. 

Social media cookies are crumbling, privacy laws are tightening, and every misstep in handling data can cost not just money, but trust. Welcome to the new era of Indian marketing, where the secret weapon isn’t a flashy ad or a viral campaign. It's first-party data.

In a market that often celebrates growth at any cost, collecting data for data’s sake has become the marketing equivalent of FOMO: noisy, expensive, and strategically hollow. 

But used wisely, first-party data can be a lifeline, driving scale, efficiency, and resilience. It’s the difference between shouting in a crowded stadium and whispering the right message in the right ear.

Amin Lakhani, President of Client Solutions, frames the debate bluntly: “The shift to first-party data in the Indian marketing landscape is not an expensive trend, but a non-negotiable investment in future business resilience and compliance.” 

“The ‘expensive trend’ label only applies to those who collect data for collection’s sake—a form of marketing FOMO, rather than for strategic utility,” he told BestMediaInfo.com in an exclusive chat. 

At the heart of this argument is India’s evolving regulatory landscape. Lakhani explained, “First-party data is crucial because it acts as a compliance catalyst ahead of the Digital Personal Data Protection (DPDP) Act. Securing explicit consumer consent and building clean data pools are now risk-mitigation imperatives, not just media options.”

Low-ticket categories, high stakes

For high-volume, low-ticket sectors such as FMCG, telecom, and vernacular e-commerce, the challenge is immediate: the infrastructure cost of collecting and managing first-party data often outweighs the lifetime value (LTV) of a single consumer. 

Lakhani noted, “The critical short-term challenge is ensuring the infrastructure cost of collecting and managing first-party data is justified by the relatively low Lifetime Value (LTV) of an individual customer. This cost-to-value ratio is the core constraint driving our strategic choices. Over the long term (3+ years), this equation flips, as the amortised cost becomes negligible compared to the competitive moat and regulatory resilience gained.”

On measuring ROI, he emphasised that the business fit for first-party data is assessed based on Scale and Media Efficiency, not 1:1 personalisation ROI. 

“The primary ROI comes from using first-party data as a privacy-compliant seed audience to inform massive media buys. This ground truth allows brands to build superior lookalike models, enhance suppression lists (reducing ad wastage), and improve the CPA at scale for the next 100 million digital users,” he added. 

He further highlighted, “Given India’s mobile-first market, the most valuable identifier to own and clean is often the mobile number or email. Brands must prioritise this core ID collection for future identification and linking across platforms.”

Zooming in on the type of data to prioritise, he advised focusing on harvesting engagement data such as app activity and content consumption. He said this is a critical short-term tactic because it is cheaper to acquire and immediately invaluable for broad behavioural segmentation and optimising media buys. 

In the long term, he added, this behavioural data fuels their predictive AI models, which then drive superior retention and higher Customer Lifetime Value, even if the final purchase happens offline.

A pragmatic approach to MarTech

Lakhani outlined a staged “crawl, walk, run” approach:

• Crawl: Light/Modular. Focus on free or native cloud tools (like Google Analytics 4) and basic data connectors. Avoid dedicated, multi-crore CDP licenses. 

Outcome: Prove Value. Centralise the core customer ID (mobile/email) and accurately measure media efficiency against this clean data set.

• Walk: Moderate. Investment in a foundational CRM or ‘CDP Lite’ platform. Focus on integrating with local platforms (e.g., WhatsApp Business APIs, vernacular content systems). 

Outcome: Drive personalised customer experiences (CX) for high-value segments and increase customer lifetime value.

• Run: Heavy. Full-scale Enterprise CDP and Data Clean Room (DCR) investments. Requires dedicated Competitive Orchestration. Enable real-time, cross-channel ‘next-best-action’ marketing and maximise utility within ecosystem integration.

He emphasised the philosophy behind the stages, advising clients to adopt a ‘crawl, walk, run’ investment approach. In a cost-sensitive market like India, he said, the focus shouldn’t be on buying the most expensive CDP but on building a modular stack that delivers proven ROI first. The real investment, he added, is in hybrid talent who can integrate, localise and apply the data, not just the platform itself.

The federated frontier

Lakhani explained a shift away from raw data ownership to federated ecosystems: “Our focus is on 'Intelligence Beyond Identity.' We collaborate with data where it lives (federated learning) instead of demanding clients hand over raw data. This allows our AI models (WPP's Large Marketing Model) to train on behavioural data from 350+ partners without ever moving or copying the underlying PII.”

On turning compliance into an advantage, he said this approach converts regulatory compliance requirements, such as the DPDP Act in India, into a commercial edge. By offering a privacy-by-default marketing system, he added, brands can achieve the scale and precision they need while maintaining full data sovereignty.

He added, “The focus is on probabilistic modelling, using AI to predict behaviour and context rather than relying solely on deterministic identity matches. This means building systems that find the signal in the noise without compromising consumer trust.”

When accessing data beats owning it

Certain contexts make data access strategically superior, he noted.

“Retail Conversion Attribution: Accessing the RMN’s data via a clean room provides irrefutable, third-party verified evidence of ad-to-purchase conversion. While many brands have highly accurate owned D2C data, RMN access provides closed-loop certainty that is invaluable for its sheer scale, reflecting millions of third-party purchases, and its relevance in capturing immediate, verified purchase behaviour,” Lakhani stated. 

For pan-India campaigns, he said that if a brand needs to reach a million consumers in Tier 2/3 cities speaking Marathi or Tamil, they need access to audience data held by vernacular content publishers, local news platforms and regional apps. Trying to own this level of scaled regional behavioural data, he added, is impractical and far too slow.

Balancing intuition and data

Lakhani concluded with a human-centric reminder: “Marketers must never trade consumer intuition for dashboard dependency. Data should serve as a co-pilot, not the sole driver.” 

On AI, he said, “While AI (like Gemini) can generate thousands of banner variations in minutes (improving operational efficiency by automating the 'middle class' of ad work), the human role shifts from copywriter to prompt engineer and strategic interpreter. The machine is fast, but the human provides the singular, emotional insight.”

Finally, on trust, he said the biggest risk is the loss of consumer trust. He added that brands must be transparent about data collection and offer a clear, personalised value exchange, for example, faster service or better loyalty perks, in return for that data.