Beyond Clicks & Impressions: Mastering Personalization in the Attention Economy

Attention is now the most coveted commodity in the digital age. As digital spending skyrockets, consumers feel inundated by a relentless barrage of often irrelevant, intrusive content that two-thirds of shoppers dismiss as noise.

Traditional metrics like clicks and impressions are becoming less effective. As Forbes warned in “The Hidden Impact of the Attention Economy,” marketers must radically rethink their approach to consumer engagement. It's time for a fundamental shift: The era of hyper-personalization is upon us, demanding a deep understanding of consumer behavior and a relentless pursuit of deeper connections.

CPG brands, with their deep-rooted focus on targeting and performance optimization, are uniquely positioned to excel in this new landscape. Yet, the complexities of inflation and economic uncertainty have created a challenging environment, forcing marketers, agencies, and shopper marketing teams to reevaluate their strategies – delaying budget releases and shifting funds to please shareholders.

Embracing a value-driven, real-time approach
Consumers are impatient for change. They have said ‘enough’ to soaring prices, and even though economic indicators say their confidence remains strong, decisions about what and where to buy their groceries are shifting. Shoppers are adapting their habits, prioritizing value and seeking more meaningful brand interactions.

To thrive in this fluid, attention-driven economy, CPG brands must embrace a real-time mindset and leverage advanced technologies to unlock the full potential of their marketing investments. It’s critical to work with a partner who will use artificial intelligence and machine learning responsibly, allowing you to analyze millions of variables to predict shopping behavior for media efficiency.

Leaning into hyper-personalization
Many providers claim they have a clear picture of consumers and shoppers, but they're 20,000 feet away and painting with a fire hose. Imagine all of those wasted impressions.

Whether you’re an emerging or established brand, real-time personalization across channels – from e-commerce to social media to in-store -- has never been more intricate and complex. Hyper-personalization goes beyond demographics. Every message must be singularly relevant, whether it’s delivered on a webpage or mobile device, at the gas pump, or on one of the thousands of linear, cable and streaming channels. And it should be tailored to the current relationship shoppers have with your brand, whether they’re a likely trier, lapsed user, or loyalist with a tightened budget.

There are a number of hyper-personalized targeting solutions that will help you uncover buyer opportunities and maximize media performance. Catalina uses actual shopper behavior - measured by in-store purchases - that is analyzed by data scientists who combine critical thinking, creativity and domain expertise with AI and the most advanced machine learning and predictive modeling techniques:

UPC-level brand insights – Immediately see the addressable opportunity for your new product, brand, or category. Understand each consumer’s value, measured by how much they spend, what they buy in your portfolio, how often they purchase your products, and how much they buy. Catalina uses an ID Graph that weaves together 1:1 deterministic data and third-party data sets to gain insights into more than 400M shoppers. This includes purchase receipt and panel data, retailer visit behavior, demographics and media consumption patterns, as well as lifestyle and ingredient preferences.

POS transactional insights – Use real-time point-of-sale data from major grocery and drugstore chains to match UPC-level transactions at the household and consumer levels in a privacy compliant way. Catalina’s modeling keeps up with the rapid shifts in the market by finding a sample of historical purchase patterns and identifying the most important predictors of behavior. Data scientists then apply the model to current buyers who have not bought a brand to produce a score that represents the probability of trying a brand.

High-level performance insights – Benchmark your performance against your competitors, plus get back-end measurement data to understand your top KPIs, from building brand awareness to return-on-ad-spend (ROAS). Catalina uses a Real-Time ID Crosswalk that combines multiple ID sets and real-time transaction data to create sophisticated inflight optimization and content activation, from sequential marketing and suppression to hyper-personalization.

Applegate Naturals, for example, brought 20% new buyers to their category and brand using these techniques. They drove sales of their deli items during the important back-to-school season by increasing awareness to acquire new buyers, reengage lapsed buyers, and build loyalty with ongoing engagement.

They turned to Connected TV (CTV) to reach custom audiences -- matching household exposures and purchase behavior – with value-driven, personalized in-store incentives that delivered a ROAS of $2.22.

Thriving in the Attention Economy
By connecting the dots of fragmented shopper data through advanced targeting models, brands can thrive in the competitive landscape of the Attention Economy. Catalina’s team of data scientists have decades of experience using AI and machine learning to synthesize 3.5M+ variables that drive shopper loyalty and sales. It's no longer enough to simply capture a consumer’s attention; the key is to use hyper-personalization to convert that attention into lasting customer relationships that drive tangible business results.