Responsible data-driven storytelling in Indian advertising, Marketing & Advertising News, ET BrandEquity

Responsible data-driven storytelling in Indian advertising, Marketing & Advertising News, ET BrandEquity


<p>Representative image (iStock)</p>
Representative image (iStock)

By C. Deep Prakash

In the evolving Indian digital advertising landscape, hyper-personalisation has become a powerful tool for connecting brands with consumers on a highly individual level. Personalisation through AI allows companies to offer tailored product recommendations, offers, and narratives, making intangible services such as healthcare or financial products more relatable.

However, the power of personalisation comes with significant ethical responsibilities. Seventy-two percent of Indian consumers are concerned about online privacy (KPMG, 2023), and 63 percent want greater transparency regarding how brands use their data (FICCI, 2023). Thus, responsible data- driven storytelling is essential to maintaining consumer trust.

Storytelling as a tool for engagement and sensemaking

Storytelling has always played a central role in advertising, serving as a way for brands to give meaning to their products and services. Today, big data analytics can process consumer behaviour data to craft stories that resonate on an individual level.

This dynamic interaction between consumers and brands enhances the adoption of smart services, as customers better understand the value offered. However, storytelling must remain transparent and informative rather than manipulative.

Ethical concerns of hyper-personalisation

Hyper-personalisation presents serious ethical challenges. AI-powered advertising uses behavioural data and psychological insights to deliver highly targeted messages, which can exploit consumer vulnerabilities. A notable example is Target’s predictive analytics system , which identified pregnant customers, leading to a teenager’s pregnancy being revealed through targeted mailings.

Moreover, the rise of genomarketing, where brands use DNA data to personalise products, has amplified privacy concerns. Consumers are often unaware of how their genetic data is being used, raising the issue of informed consent. Breidbach and Maglio (2020) identified 13 ethical challenges in such practices, including coercion, data awareness, and proxy discrimination. Without robust regulatory frameworks, hyper-personalisation risks eroding consumer trust.

Algorithmic bias and the risk of discrimination

Another key issue is algorithmic bias in AI-driven advertising. Algorithms are trained on historical data, which often reflect societal biases. In India, where divisions based on caste, religion, and gender are deeply ingrained, the potential for biased algorithms to perpetuate inequalities is a significant concern. AI-powered personalisation can inadvertently exclude certain groups from job or housing ads, reinforcing societal disparities.

Brands must ensure their data sets are diverse and representative and regularly audit their algorithms to minimise bias. Failure to address these biases not only presents ethical concerns but can also undermine the effectiveness of personalised campaigns by alienating key customer segments.

Reducing risk and building trust through storytelling

Given the intangible nature of many services, consumers often seek the experiences of others to reduce uncertainty. Storytelling can help potential customers understand a service’s value. For example, financial services companies can highlight customer success stories to demonstrate the value of their products, helping to reduce perceived risks and foster trust. However, transparency is crucial.

Consumers must know how their data is being used to shape these stories. Without transparency, data-driven storytelling can become another form of manipulation, exploiting emotions rather than fostering informed decision-making.

Addressing the dark side of data-driven marketing

The undesirable side effects of data-driven marketing, referred to as emergent properties in systems thinking, can be unexpected and counterintuitive. Hyper-personalised marketing can lead to adverse outcomes such as privacy violations, financial penalties, and customer discrimination. De Cremer et al. (2017) categorise these risks into four types:

1. Knowledge-based behaviour, such as privacy issues.
2. Transaction-based behaviour, like confusing customers with complex offers.
3. Relationship-based behaviour, including customer favouritism and creating switching barriers.
4. Integrity challenges, such as manipulative practices that exploit trust.

To mitigate these risks, brands must prioritise ethical guidelines, transparency, and self-regulation.

Balancing innovation with responsibility

Brands must strike the right balance between innovation and consumer protection. Transparency, consent, and data agency should form the foundation of any personalisation strategy. Consumers should have control over how their data is collected, used, and shared, with easy-to-use tools that allow them to manage their personalisation settings.

Brands should also develop self-regulatory frameworks to address ethical challenges in AI-driven advertising. This includes designing algorithms to minimise bias, creating complaint mechanisms, and auditing AI systems for ethical compliance. By doing so, companies can build consumer trust and ensure that hyper-personalisation benefits both the brand and the consumer.

A call for responsible hyper-personalisation

Hyper-personalisation raises pressing ethical questions about privacy, autonomy, and fairness. To protect consumers, brands must adopt a responsible approach to data-driven storytelling—one that prioritises transparency, accountability, and the ethical use of AI. This responsibility goes beyond compliance with existing regulations; it requires companies to reimagine their role as guardians of consumer trust in the digital ecosystem.

Furthermore, the use of emerging technologies, such as genomarketing, will continue to test the limits of consumer tolerance for data collection. As the boundaries of personalisation extend deeper into aspects like genetic makeup, the ethical stakes become even higher. The question is no longer just about what data is collected but how it is used and whether it leads to a truly beneficial experience for the consumer or crosses the line into manipulation.

A consumer-first approach is the need of the hour. Hyper-personalisation should not be about pushing the boundaries of data exploitation but enhancing the consumer experience while respecting their rights and dignity. Brands that ignore these ethical concerns may win short-term gains but risk long-term reputational damage, eroding the trust that personalisation seeks to build. Consumers today are becoming increasingly aware of the trade-offs they make with their data, and they will favour brands that align with their values of fairness and respect.

The future of advertising in India lies in finding a balance between the promises of hyper- personalisation and the protection of individual privacy. Brands that are proactive in developing self-regulatory frameworks and engage in open dialogues about data usage will build stronger customer relationships and contribute to a more ethical digital economy. The path forward is not just about being innovative—it’s about being responsible in shaping a future where consumer autonomy and trust are at the forefront of every advertising strategy.

(The author is an assistant professor, information management and analytics, at SPJIMR. Views expressed are personal.)

  • Published On Dec 3, 2024 at 08:50 AM IST

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