End of the ‘spray and pray’ era: Why data-driven targeting is crucial

Brands can no longer afford to shoot in the dark. It’s time to ditch guesswork and go data-deep with targeted strategies.

author-image
Himani Agrawal
New Update
Him

Consumer attention is a commodity that brands are losing out on, fast. The digital landscape is saturated with content, and the old approach of ‘spray and pray’ marketing is not cutting it anymore. With reduced attention spans and the dismantling of the one-size-fits-all approach, brands have to look at data-driven targeting as a pillar in their strategy.

The need for precision targeting

While historically effective, mass-marketing ad strategies have shown diminishing returns in today’s digital economy. According to a Nielsen study, the effectiveness of traditional TV ads has declined by approximately 30% in the past decade, with users ignoring the ads or skipping them altogether.

Another 2024 study by the Institute of Data suggests that targeted ads result in a 5.3x increase in click-through rates (CTR) compared to non-targeted ads. 

Case in point, Procter & Gamble reduced its digital spending by $200 million in 2018, once they discovered that mass-targeted ads were ineffective, leading to wasted impressions rather than meaningful engagement or conversions. Instead, they pivoted their strategy to adopt precision-targeted campaigns, resulting in better ROI without increasing overall spend.

This clearly highlights the necessity for precise targeting, both in messaging and audience segmentation.

Precision targeting in influencer marketing

The aftereffects of misaligned messaging can be far-reaching, especially when it comes to influencer marketing, which has permeated all aspects of our decision-making and is therefore integral to the success of modern GTM strategies.

Unlike traditional digital ads, influencer marketing thrives on authenticity and audience alignment. However, when brands collaborate with influencers without data-backed insights, the results can be counterproductive. 

For instance, brand collaborations that do not align with an influencer’s target audience can often lead to low engagement and a reduction in brand loyalty. Basing decisions on AI-driven insights, sentiment analysis, and audience segmentation allows brands to identify the right influencers and ensure their marketing efforts drive real impact.

The transition to data-backed marketing, however, requires a fundamental shift in strategy. Traditional demographics alone are no longer sufficient; advanced segmentation now leverages markers like behavioural insights, psychographics, and real-time engagement data to refine audience targeting.

AI-driven analytics platforms enable brands to identify and engage with high-intent audiences, ensuring more precise messaging. 

For instance, brands using such AI-powered influencer marketing platforms like Hypothesis can analyse engagement patterns and audience demographics in real time to determine which content types and influencers would yield the best results. In fact, a report by McKinsey highlights that companies that adopt AI-driven personalisation can see up to a 30% increase in marketing efficiency.

Transcending vanity metrics

Additionally, performance metrics must go beyond reach and follower count. While vanity metrics such as these may provide surface-level insights, they don’t indicate true campaign success. For instance, a high follower count does not necessarily translate into conversions, brand trust, or even engagement for that matter.

Instead, modern marketing parameters such as engagement levels, conversion rates, retention metrics, and sentiment analysis now offer a clearer picture of campaign performance. In addition, influencer marketing solutions offer real-time performance tracking, eliminating the scope of error in post-campaign evaluations. 

Brands and marketers can now pivot strategies mid-campaign, optimise budget allocation, maximise impact, and craft data-driven narratives that drive authentic engagement and high-intent conversions, while AI does the redundant tasks.

Personalised interactions are the future

The marketing landscape is shifting towards precision, adaptability, and intelligence. Data-driven targeting can enhance marketing efficiency by improving personalisation, increasing engagement, and optimising resource allocation. This approach goes beyond commercial success, with targeted ads informing consumers’ buying choices. 

As per a recent study by McKinsey, 71% of consumers expect companies to deliver personalised interactions, while 76% get frustrated when that doesn’t happen. Brands that continue to rely on outdated mass-market strategies will struggle to stay relevant. By shifting from broad-stroke marketing to data-informed strategies, brands can ensure that every marketing dime is spent with purpose and impact.

The solution lies in integrating advanced analytics and real-time consumer behaviour as core pillars of brand strategy. The question is no longer whether data-driven targeting is necessary — it’s whether brands can afford to ignore it.


(Himani Agrawal is the Senior Vice President of Product & Analytics, Hypothesis at Only Much Louder Entertainment, where she uses data to drive content and marketing strategy.) 

digital marketers digital marketing
Advertisment