Widely used by major brands and companies to monitor key metrics, understand behaviours, and measure performance, tracking studies are critical for helping inform business decisions. They provide valuable insights into how your brand is perceived, how your campaigns are performing, and how customer preferences are evolving.
But are you getting the full picture of your audience? Traditional trackers often only focus on a limited set of metrics, leaving gaps in understanding consumer motivations and emerging trends. To truly unlock the potential of your tracking data, it's essential to leverage connected data from multiple sources. This approach enables a more holistic view of your audience, providing richer context and more actionable insights to guide strategic decision-making.
To help you make the most of your tracking studies, we’ve put together some guidance on how you can leverage connected data solutions to capture a 360 view of your audience.
The Limitations of Traditional Tracking Studies
You may be capturing a wealth of data from your tracking study, but there could still be critical gaps:
- Limited Behavioural insights: Traditional tracking studies capture stated preferences over time, but these don’t always align with actual behaviour.
- Data Silos: Tracking study data often exists in isolation, missing critical context from other business or market sources.
- Lack of Agility: Traditional trackers can fall into a “set it and forget it” mindset because making changes is complex and time-consuming. As a result, they may struggle to adapt to shifting business priorities or rapidly evolving market conditions.
Balancing Survey Efficiency with Data Completeness
One of the ongoing challenges in tracking studies is finding the balance between collecting valuable data and maintaining respondent engagement. Brands often strive to reduce the length of surveys to avoid survey fatigue, but at the same time, they need enough data to draw meaningful conclusions. This creates a tension between wanting to ask fewer questions and still capturing the depth of information required.
As we streamline survey content, there’s an increasing need to fill in the gaps in respondent data—whether it's incomplete demographic information or lack of certain behavioural insights. To improve analysis and ensure accuracy, it’s crucial to find effective methods for supplementing missing data. This helps create a more complete picture, allowing for better decision-making without overburdening respondents.
The Power of Data
In today’s data-driven world, having access to the right information is essential for brands and companies striving to make informed decisions. From behavioural data that reveals how consumers interact with products to social data that captures sentiment and engagement, each data type plays a vital role. Below are some examples of different data types and how they can help you build a more comprehensive profile of an audience:
- Demographic and geographic data: Adds context by revealing who your customers are and where they are located. Examples of demographic data include age, gender, income level, occupation, household makeup, and more. Analysing demographic and geographic data can aid with targeted campaign or audience segmentation, resulting in more effective marketing.
- Behavioural data: Tracks interactions with products, services, or platforms to identify trends and preferences. Examples of behavioural data include product views, browsing history, website click-through rates, app usage and advertising exposures. This data helps brands understand which features or content are most engaging, allowing them to optimise user experiences, personalise offerings, and improve conversion rates.
- Transactional data: Provides insights into purchase history, spending habits, and customer loyalty. Examples of transactional data includes order volume, payment methods, frequency of transactions, etc. This data can help brands identify trends and optimise pricing strategies.
- Social data: Powers digital behavioural insights sourced from social media signals including category and brand engagement, influencer and content engagement, media channel usage, and derived interests, all based on how people engage in their social networks via follows, mentions, shares, hashtags, likes, etc. By analysing social behavioural data, brands can paint a broader profile picture of their exact audiences to drive media and messaging planning and digital media activation and targeting.
- Pre-defined segment data: Drives deeper audience insight into consumer lifecycles from pre-defined audience lifestyle groups and clusters. Pre-defined segments categorise individuals with similar demographics, lifestyles, and behaviours into summary groups, offering names and descriptions that reflect the typical characteristics of households within each segment. Examples of pre-defined lifestyle segments could include descriptive group names like “solo retirees” or “families on a budget”.
- Syndicated data: This type of data is collected, owned, and sold by third-party research companies and sold to multiple parties. It offers businesses insights into market trends and industry dynamics, without having to conduct their own research. For example, Kantar offers syndicated data access through a variety of on-going studies like MONITOR, BrandZ, ComTech and more.
What is Connect Data?
Connected data refers to the practice of linking various data sets to create a more comprehensive and integrated view of a target audience. The Profiles team at Kantar has a practice focused specifically on solutions linking their panellists to other first, second, and third-party data sets.
What does this mean in practice? When connected data is integrated into your tracking studies, it transforms the way you understand your customers. Rather than being limited by a survey instrument, you can enrich respondent profiles with deeper layers of insight—such as online and offline behaviours, media consumption, purchase activity, preferences, and more.
This integrated view allows marketers to develop strategies that resonate with audiences on a deeper level, leading to stronger engagement and more meaningful connections. You can also uncover opportunities for activation, personalisation, and campaign optimisation.
Now that you understand what connected data is, let’s look at an example of how a major player in the pharmaceutical space leveraged connected data in a brand health tracking study:
A Case Study
The challenge: A leading pharmaceutical and consumer healthcare company wanted to validate the effectiveness of its targeted digital advertising. Specifically, the team set out to answer three key questions: Is there a clear connection between digital media exposure and brand awareness? Does awareness clearly translate into product purchases? And ultimately, can they prove that targeted digital ad campaigns are driving real purchase behaviour?
The approach:To connect the dots between digital media exposure, brand awareness, and purchase behaviour, the Profiles Team at Kantar used enhanced sample solutions. This allowed for a seamless integration of survey responses with the company’s own ad exposure and purchase data. To begin, Kantar pre-matched its panellists to the company’s data collaboration platform, linking individuals to digital ad exposure and product purchase data. Panellists were then surveyed on key brand health tracking metrics, including aided and unaided awareness across 7 categories and 5 recent product launches. The resulting data set (connecting brand perceptions, ad exposure, and purchase behaviour) was delivered back to the company for in-depth analysis, providing a more complete view of marketing effectiveness.
The impact: By connecting the company’s ad exposure and purchase data with tracking insights, the analysis confirmed a strong relationship between digital media and both brand awareness and product purchase. For example, all brands with connected, ad-exposed audiences saw a measurable increase in brand awareness. Among ad-exposed individuals, brand awareness lift ranged from +17% to 32% across all brands. Amongst ad-exposed individuals who also purchased the company’s product, brand awareness lift averaged +50% across all brands.
This connected data approach validated the company’s hypothesis: targeted digital media not only boosts brand awareness but also drives actual purchase behaviour. The findings now inform decisions around more than $50M in digital media investment, particularly as they optimise future campaigns and prepare for upcoming project launches.
Conclusion
Traditional tracking studies, although powerful tools in the business world, can be limited in their ability to provide a full view of an audience. By integrating connected data—such as first-party customer data, third-party sources, and behavioural analytics—organizations can unlock deeper, more actionable insights.
Interested in learning more?
Fill out the form below to download our full guide, Custom Tracking for Business Growth that dives into the essentials of effective tracking and how it can transform your brand strategy. Or, contact Kantar today to explore how you can leverage connected data to unlock deeper value from your data.
