Blog/Research

Let’s face it – most traditional tracking products aren’t built for how agencies or brands actually work today. 

Many trackers simply can’t keep up with the pace of campaigns or media grids. They’re too slow, inflexible, and operationally intensive to meet the needs of modern insight teams. Worse, they usually come with rigid questionnaires and multiple manual steps, from data cleaning to reporting, which slows things down. The result is that insight teams end up spending excessive time and budget, only to get data that arrives too late and isn’t easily reused or integrated elsewhere.

What’s needed is a new approach – a modern data stack for brand tracking – that lets insight teams track at the speed of their most demanding media programs. In this article, we’ll break down the most common pain points with traditional brand tracking, and show how modern, AI-enabled research platforms solve each one.

Step 1: Move from slow to high-frequency tracking

Pain point – sluggish, infrequent dips: Traditional brand trackers operate on slow cadences – often monthly or quarterly – which means you’re always looking in the rear-view mirror. Infrequent tracking not only delays insights, but also makes it hard to tie brand metrics to recent campaigns or events – by the time you get the results, the moment has passed.

A modern data stack flips this by enabling high-frequency, near real-time tracking. The best platforms automate the laggiest parts of research (fieldwork, data quality) to allow dips to be drawn on a weekly or even daily basis, across several markets. This means you can keep a continuous pulse on brand health, consumer sentiment, and reputation – detecting changes as they happen and reacting in time. Whether you’re tracking the impact of a new ad campaign or monitoring public opinion during a crisis, this always-on approach ensures you’re never caught off guard.

Case study: Mediahub UK partnered with Focaldata to replace slow, manual brand tracking with automated, weekly insights across 20+ markets – saving analyst time and powering faster, data-led campaign decisions.

Step 2: Replace one-size-fits-all with custom tracking

Pain point – Rigid and generic trackers: Traditional brand tracking programmes are often one-size-fits-all, with rigid structures that are hard to adapt. Many rely on standardised questionnaires focusing on generic metrics, which may not fully align with your specific client’s KPIs. Once a tracker is in place, it’s difficult to change course. Adding a new question or tweaking the survey to reflect emerging market conditions is a challenge. 

We need trackers built around clients, rather than the other way around. The best trackers are tailored to each client’s objective and reporting cadence, rather than off-the-shelf. By doing this, you get more actionable insights (no wasted questions), and your client or end user has research at their fingertips that is speaking directly to their goals (keeping your budgets secure!).

Step 3: Automate data quality control

Pain point – Laborious data quality checks and nasty surprises: Anyone who’s run traditional surveys knows the pain of data quality and quality control. After fieldwork, teams often spend days manually sifting through responses to remove speeds, straight-liners and low-quality data. Trad panel providers often only apply basic checks, leaving a lot of dirty data for your team to sift through. All this manual QC’ing drains researchers’ time and productivity, and puts delivery timelines at risk. 

The solution? Automating data quality control. 

The best platforms have a quality engine trained on millions of data points to detect low-quality respondents in real time. At Focaldata, every response is scored and filtered automatically – with an average of 35% of respondents removed on quality grounds (well above the ~10% industry average). The result? Researchers can focus on generating insights, not cleaning data.

Step 4: Streamline delivery with minimal team overhead 

Pain point – Resource-intensive process: Traditional brand tracking isn’t just slow – it’s heavy on operational overhead. Running a tracker often involves coordinating multiple suppliers and steps (panel providers, translators, scripters, analysts) and plenty of project management. For agencies trying to do more with lean teams, the conventional approach just doesn’t scale.

The modern tracking stack dramatically reduces the operational overhead of brand tracking. Your data partner manages the entire process for you – from sourcing respondents and programming the survey, to translations for each market, fieldwork monitoring, and data processing. Modern platforms automate what can be automated (sampling, quota management, quality checks) and researchers handle the rest with expert efficiency.

The result? Running a large-scale tracker becomes practically “zero-touch” for your insights team. You get speed and scale without the usual headaches – no more chasing suppliers or juggling data files. The data is delivered seamlessly, so your team can focus on what they do best: research design and insight storytelling.

Step 5: Turn your data into a long-term asset 

Pain point – Data siloes and wasted insights: Traditional brand tracking projects often operate in isolation. After each wave, you might get a static report or a slide deck, and then the data is filed away. There’s rarely an accessible central repository for all that survey data, making it hard to compare results over time or repurpose past data for new questions. Vast amounts of valuable data end up siloed or forgotten once the project ends, meaning agencies miss out on cumulative learning.

Focaldata’s solution: Built-in data infrastructure and integration

A core tenet of the modern data stack is that your data is centralised, accessible, and ready to analyse. Modern data providers deliver exactly that for survey research. 

Every survey run on our platform is securely stored in your company’s private dashboard – effectively creating a living data library of all your brand tracking (and other survey) data in one place. Instead of data disappearing into PDFs, it’s all there for your team to search, query, and analyse whenever needed. In essence, your data partner provides the “data lake” for survey research so you don’t have to build it from scratch. 

But we don’t force you into a standalone portal if you already have analytics tools; we can integrate directly into your existing data stack. If you have your own pipelines and data storage, we’ll output the data exactly how you need and set up integrations to stream it automatically into your pipeline, allowing brand tracking data to seamlessly merge with other data streams in your organisation.

The payoff is huge: your team can leverage all past and present data to generate deeper insights and strategic foresight, rather than treating each tracker wave as a standalone effort. By integrating brand tracking into the modern data stack, modern brand tracking helps agencies turn raw data into an ongoing strategic asset.

The age of slow, inflexible brand trackers is ending

Forward-thinking agencies are embracing a modern data stack for brand tracking – one that delivers data at high frequency, adapts to each client’s needs, automates away grunt work, and integrates seamlessly with the rest of their data universe.

But it’s not just about tracking brand metrics faster; it’s about giving your team more time to focus on generating insight, not managing operations – while building a cumulative data asset that becomes more valuable with every wave.

In short, a modern approach to brand tracking makes your agency more agile, more consultative, and more indispensable to your clients.

Keen to see what that looks like in action? Get in touch.

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