The great data disconnect in India’s fast-moving markets

New Delhi: In India’s fast-moving consumer markets, where a shampoo sachet costs less than a WhatsApp data pack, the industry’s obsession with first-party data is beginning to face an uncomfortable question: Is it even worth it for small-ticket, high-frequency categories? 

As brands rush to build their own data reservoirs, the economics of doing so for small-ticket items, such as FMCG goods, low-value apparel, and impulse buys, are increasingly under scrutiny. Industry experts point out that while first-party data is indeed the future, it may not be the most pragmatic investment for everyone.

The hype, the hope, and the hard reality

In the last few years, the marketing world has been collectively nudged toward building first-party data systems, spurred by the cookie demise, privacy laws, and the industry’s need to own audiences directly. 

But as the infrastructure gets expensive and ROI cycles stretch, small-ticket brands are finding themselves at a crossroads.

Putting things in perspective, Harsh Deep Chhabra, Global Media Lead at Godrej Consumer Products (GCPL) cautioned that the economics simply don’t add up for low-ticket categories. Instead, he sees it as a structural risk many brands are carrying today.

“We operate at MRPs of Rs 10, Rs 45, Rs 99. It’s not viable for us to build first-party data pools at a cost that makes sense. Unless your average order value is Rs 500-600, your CACs, cost of deployment, and logistics will never justify the game,” Chhabra told BestMediaInfo.com. 

He added that the entire data ecosystem is evolving in ways that could render current investments obsolete. “We believe the world will move from first-party and second-party data to every-party data. At that point, the amount of effort and money going into building these so-called exclusive first-party data pools may not hold up,” he said.

A top executive from one of the FMCG majors in the country, requesting anonymity, admitted that for categories of low-ticket, high-frequency products, the economics are tricky. 

“The volume of transactions doesn’t always translate to meaningful identifiers or actionable insight. Unless the data is being actively used to sharpen creative relevance, improve retention, or drive incremental sales, it risks becoming a vanity metric, a shiny dashboard that looks sophisticated but doesn’t move the needle,” the executive said. 

For the executive quoted above, first-party data is “a means, not an end.” It becomes a real growth driver only when it is tied to a clear business use case, whether that’s improving media efficiency, enabling precision remarketing, or deepening consumer engagement.

“Too often,” the executive added, “brands invest heavily in infrastructure and data lakes without defining the ‘so what’, leading to high costs and minimal commercial impact.”

The business fit problem

Vivek Das, Chief Digital Officer, Madison Media, believes the viability of first-party data depends entirely on the scale and nature of consumer interactions. 

For low-ticket, high-frequency categories, he said, the transaction volume itself offers an opportunity to collect consent-based data, but only when the cost of acquisition and operations doesn’t outweigh the incremental value.

At Madison, Das and his team typically advise clients to measure success through tangible ROI: repeat purchases, retargeting performance, or cross-sell potential.

He noted that even low-consideration brands have found success using simple consumer interaction tools like missed calls, QR codes, or WhatsApp surveys to build scalable first-party data sets. 

“These lightweight models have delivered higher engagement and improved sales via personalisation, without heavy upfront infrastructure,” he said.

Bhavesh Talreja, Founder and CEO, Globale Media, also sees the challenge differently. He argued that for such categories, ROI depends less on the size of the database and more on speed, context, and conversion cycles.

“The ROI is not in building large databases but in understanding micro-moments, for instance, how frequently a consumer engages and what triggers repeat behaviour,” he said. 

Aligned with Das, Talreja, for these brands, recommended lightweight CRM systems and consent-driven engagement through WhatsApp, loyalty programmes, or apps. “The focus should be on real-time responsiveness, not data volume,” he added.

Data ownership vs data access

A key shift underway across the industry is the move from “owning” data to “owning the insight.” 

Marketers are increasingly realising that maintaining petabytes of raw data doesn’t necessarily confer a competitive advantage. Instead, there’s growing reliance on smart partnerships, from data clean rooms to retail media ecosystems, that allow privacy-compliant access to high-quality consumer signals without the cost and liability of maintaining massive repositories.

Madison’s Das noted that Indian brands are increasingly adopting hybrid models. Larger, digitally mature players such as e-commerce or retail companies still focus on robust first-party data coupled with clean-room collaborations, while smaller brands prefer partnerships with platforms and publishers. 

“The trend is on the lines of hybridisation, where owning high-quality, consent-based data aids brand building, and collaborations catalyse reach efficiency,” he said.

Sini Magon, COO and Global Partner at Grapes Worldwide, described this shift as both “practical and necessary.” She explained that meaningful data isn’t always proprietary but rather contextual and collaborative. 

“Retail media networks, publisher partnerships, and clean-room models are allowing brands to access richer insights without shouldering full custodianship,” she said. This, Magon added, is driving a more flexible, partnership-led approach to data management, one that prioritises interoperability over isolation.

The economics of smart investment

The idea that every brand must invest heavily in martech and infrastructure is increasingly being questioned. Das pointed out that there is “no one-size-fits-all solution.” At Madison, his approach factors in client size, sales cycles, transaction volumes, and digital maturity. 

“For low-margin, high-volume categories, we recommend starting with lightweight, cost-effective solutions such as CPaaS or pixel-based analytics,” he said.

Magon agreed that sequencing matters more than spending. According to her, the process begins with clarity on what the data is meant to inform, optimise, or predict. 

Categories with long purchase cycles or higher consideration levels naturally need deeper attribution models, but in impulse-driven segments, heavy tech stacks often under-deliver.

Himanshu Gupta, Growth Director at Moloco India, reinforced this performance lens. He said the real challenge for high-frequency brands is that “heavy infrastructure alone doesn’t guarantee a positive ROI.” 

The real value, Gupta explained, lies in working with machine learning-powered channels that can act on real-time signals, both attributed and unattributed, to drive repeat purchases. “Storing data is just a cost; making it actionable is what delivers performance,” he added.

Gupta believes the evolution of programmatic and retail media could help small-ticket brands bridge the gap. 

“Modern programmatic and retail media allow brands to leverage rich, user-level data without having to own complex infrastructure,” he said, noting that advanced algorithms often outperform siloed owned data in such scenarios.

While many still see first-party data as the holy grail of marketing, experts caution that its pursuit must remain grounded in commercial reality.

Nisha Sampath, Managing Partner, Bright Angles Consulting, said the real strength of first-party data lies in how it deepens the brand-consumer relationship. “It’s not just about collecting emails or phone numbers; it’s about having a relationship with your customer and increasing goodwill, loyalty, and transaction values through the data you have,” she said.

She added that ethical, intelligent use is essential. “The best use is when all departments within your organisation understand your customer intimately through this data and use it to improve experiences, not just push out messages,” Sampath added. 

So, is first-party data worth it?

Perhaps the answer isn’t binary. For brands with high average order values or long purchase cycles, first-party data remains a long-term moat. 

But for those selling soaps, snacks, or sachets, the smarter move may be balancing ownership with access, letting technology do the heavy lifting while staying close to the consumer.

In the end, the question isn’t whether to own the data, but whether that ownership pays for itself.