Published: 2/06/2025
Sandy Streim
Senior Business Development Director, Dynata
Audience targeting has become the cornerstone of effective marketing campaigns across digital and connected platforms, plus linear TV and DOOH. To accomplish this, marketers have long relied on behavioral data to identify and engage audiences. However, there is another oft overlooked data option for targeting—attitudinal data.
Understanding Attitudinal Data vs. Behavioral Data
Behavioral data reflects the “what.” It tracks what people do online: pages, clicks, and carts. It’s useful for identifying patterns and trends but often lacks explicit context or motivation. Given the industry is awash in behavioral data, this targeting assumes past actions predict future behavior, which isn’t accurate (and maybe stunningly out of date). This is also a blunt instrument when applied, where nearly everyone has access to the same data (eg, is there an endemic site in any segment that restricts access to their pool of site visitors?)
In addition, the opportunity to tie back to and optimize against media investment or changes in key performance indicators over time is limited and quickly depletes the pool of targets.
Attitudinal data reveals the “why” behind their actions. It uncovers people’s values, preferences, and emotions through surveys, social sentiment analysis, and other means. This data is not about what someone has done but about what drives their decisions—providing insights into their mindset, interests, and future intentions. At its core, these are unique to the brand or agency, especially when derived from custom segmentation surveys or brand lift measurement. By integrating this “personal” data into audience targeting strategies, marketers can unlock unparalleled opportunities for precision, relevance, and brand loyalty.
How to Create Attitudinal Data
- Custom Research: Use direct feedback from consumers to understand their preferences, motivations, interests, cares, and pain points.
- Ad Campaign/Brand Lift Measurement studies: These studies determine how effectively an advertising campaign moves the needle on a brand’s funnel and perception metrics, homing in on one or several variables from which to model attitudinal audiences allows for more efficient targeting, quick and pointed optimization options, and refilling of the data pool.
- Client Segmentation Frameworks: Move beyond demos and single variables to create custom groupings or description of any audience by any variables, intent, or beliefs specific to a brand. The brand’s custom segments describe their ideal customer(s) based on a combination of proprietary research, consulting work, historical data, and so on. Bridging the gap between those inexact segments into usable, rigid data elements or ID pools for use in programmatic tools is a unique challenge.
- Creative testing: Evaluate creative assets against specific audiences to develop ads that resonate for specific segments
The Advantages of Attitudinal Data
- Enhanced Personalization
Behavioral data enables surface-level targeting—recommendations based on prior actions. Attitudinal data dives deeper, allowing brands to match messaging that resonate with a person’s stated intent, values, and interests. - Forward-Looking and Proactive marketing
Unlike behavioral data, which is inherently retrospective, attitudinal data captures current and embedded opinions and intentions. This predictive power helps brands anticipate consumer needs before they manifest as actions, making marketing efforts proactive rather than reactive. - Better Customer Segmentation
Behavioral data often lumps consumers into broad categories based on similar actions. Attitudinal data enables more nuanced targeting. For example, two consumers may buy the same product, but one may have valued quality while the other prioritizes affordability. Understanding these distinctions allows for more targeted and meaningful communication. Also, determining which consumers care “more” or even at all about a subject can be teased out before the media runs or in the intra-campaign optimization cycle.
For example, a consumer motivated by their pet’s health in buying its food would be found by asking about that preference rather than either using pet site traffic or drilling down to a much smaller pool of non-scalable visits to a relevant “health” page on a pet site. - Improved Campaign Effectiveness
When targeting and messaging align with attitudes, campaigns achieve better targeted results at specific funnel stages and perceptions that matter (or combinations of those) and expectedly increase engagement and conversion rates. By leveraging attitudinal data, marketers can move beyond one-size-fits-all strategies to create campaigns that truly speak to their audience.
As campaigns march on, one can develop new, intra-campaign messaging and strategies for modified or even new customer segments and attitudes. - Stronger Brand Loyalty
Attitudinal data helps brands connect on an emotional level. When consumers feel understood and valued, they’re more likely to develop long-term loyalty. This connection goes beyond transactions, fostering a deeper relationship between the brand and its audience.
Attitudinal Data Complements Behavioral Data
While attitudinal data has significant advantages, it’s mainly a complement not replacement for behavioral data. Combining both datasets provides not only a palette of targeting options, but also a more robust view of the consumer. Together, they enable truly holistic targeting strategies. Further complementing these options, additional benefits arise as these strategies intertwine:
- Refill the targeting pool—broadening the audience to those outside of typical first-party (net new) and third-party site visits
- Move beyond perceived barriers to audience engagement
- Suppress or anti-target audiences that will waste media spend
- Extend segmentation work to uncover new audiences that don’t/can’t show up with behavioral dragnets
- Fine-tune precision targeting as broad (awareness KPI) or as narrow (mid/lower funnel KPIs) as needed
The Future of Audience Targeting
With the increased prevalence of privacy concerns and regulations, attitudinal data offers privacy-compliant and cookie-free person-level targeting without invasive tracking. By focusing on what consumers specifically share about themselves and motivations, brands can better find their audiences while delivering highly relevant messages.
While behavioral data provides valuable clues about what your audience is doing, attitudinal data delivers the context needed to understand why. By using both types of targeting, marketers are empowered to go beyond ubiquitous targeting, creating campaigns that inspire action, forge lasting connections, and rebuild target segments and data pools. Audience targeting isn’t just about observing behavior, it’s about understanding and finding the right people.