Measuring whether and how brand marketing changes people’s brand perception often remains more art than science. Tools to track brand perception can easily cost millions across multiple markets but often come with serious challenges in data quality. One of the major areas of data frustration in brand tracking stems from inconsistent methodology and sample sourcing when complex setups are required. 

The problem: Why inconsistent sampling breaks tracking

Sample sub-contracting and method mixing make quality control close to impossible

Whenever tracking setups become complex - for example, because they require niche audiences, difficult nested quotas, access to small markets, high frequency or large volumes - there’s a high likelihood that a single sample provider or sampling methodology won’t be able to provide sufficient access to respondents.

As a result, sample vendors often subcontract work that they aren’t able to cover through their own reach, and their subcontractors might again subcontract part of the sampling work. In markets with limited online panel reach, alternative methods like CATI or face-to-face interviews might come into play, creating even more challenges for coherent data analysis. This can have a detrimental impact on data quality:

• Quality disparities: Different sample vendors often have different (or no) quality control processes, which can lead to sample duplications, surveys completed by bots and other quality issues.

• Methodology inconsistencies: Using different methodologies, for example, using online panels in India, but computer-aided phone interviews in Pakistan - can make data incomparable, as each methodology comes with different sampling biases.

• Complex investigations: Investigating suspicious data can become very difficult as it involves multiple parties and different technical setups.

For brands, these inconsistencies can lead to misread consumer sentiment, flawed marketing optimisations, and ultimately, millions wasted in ad spend.

The solution: Ad-based sampling

Ad-based sampling
Ad-based sampling uses the digital advertising ecosystem to display questions in the form of ads to people around the world. This has many advantages over classic panel-based sampling, but the most significant one is that the sampling frame extends to almost every person who has a smartphone. Since almost 70% of the world’s population - more than 6 billion people - currently own a smartphone and almost all of them use services and apps that are able to display advertisements, this means that ad-based sampling provides the largest possible sampling frame of any existing sampling methodology.

Another key advantage of ad-based sampling is that it works in almost every country and region across the globe in a methodologically consistent way, thus enabling cross-country comparisons without the need to correct for potential biases from different sampling approaches (e.g. if an online panel was used to collect data for India, but a face to face approach in Pakistan).

Why it works: End-to-end control + examples

Ad-based sampling provides full control over the entire data generation process, from the exposure of the survey to the respondents to the data analysis. This has some unique advantages for sampling consistency and quality:

• End-to-end visibility: The entire respondent journey is visible, from the type of app people use to their click behaviour and answer patterns. This ensures 100% traceability and transparency, and the ability to investigate any data movement or development.
  
  
• Scalable supply: Highly elastic access to supply with an overall sampling frame of over 3 billion people ensures that no project ever runs out of people to interview, and thus eliminates the need to subcontract work.
  
  
• Global reach: Access to almost every country, region and city across the globe through one channel ensures that there never has to be method switching, making the results comparable across every market.
  
  
• Diverse respondents: A highly diverse source of respondents from across thousands of apps and mobile websites ensures a representative coverage of the population without the need to sub-contract to adjust for bias.

The result: Higher data quality and easier scaling

Final thoughts

With less than 1% of a population typically registered in online panels, reliance on such methodologies inevitably leads to complex setups when brands want to expand their tracking capabilities to lots of markets, for lots of brands or to reach their more niche audiences. But it should not have to be so fragmented and so expensive to cover all of these measurement requirements.

Ad-based sampling can solve these methodology complexities with the vast and cost-effective reach it provides, enabling brands to:

Have better comparability across countries
For most of our clients, it’s not just important to have highly accurate trendlines, but also to be able to compare KPIs across countries in a consistent way. Removing the need for multiple subcontractors provides this comparability.

Ensure unified data quality control
Ad-based sampling eliminates a lot of typical data quality issues, such as fraud and incentive-driven acquiescence bias. Not only this, but bringing all of the sampling under one methodology eradicates the risk of quality control inconsistencies

Expand and scale trackers as needed
Tracking in more markets, adding brands to trackers, or narrowing in on niche audiences are all viable possibilities with ad-based sampling, without any disruption to existing data trends and without the addition of more work for brands.