It’s Time for AdTech to Get Serious About Data Quality

Everyone in tech is talking about Big Data. Recent decades have seen an enormous shift from data scarcity to overabundance, in which data sets have become impossibly large for humans alone to make sense. We often said that data is the new oil – the most valuable commodity in the world. While that’s true, it fails to bring home an important point – many data sets are useless. Other data might be potentially useful but can’t do much in its raw form.

Weak data leads to bad decisions. If we draw upon the wrong data points for actions, the result will then lead to an inaccurate outcome. For the AdTech industry, operational priorities include using data for measuring performance and targeting. Programmatic data helps improve operational efficiency in ad bidding. Behavioral data helps determine which ads are most active at meeting KPIs. These data points allow providing consumer insights with a more in-depth overview of target audiences. Data can also help reduce fraudulent clicks. The list goes on.

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The challenges lie in identifying and curating the data and transforming it into actional insights. That’s why data quality should be part of every conversation about business performance and optimization. It starts with understanding the core dimensions used to determine data quality, consistency, and accuracy. Here are the main characteristics of data quality to consider:

  • Completeness – data sets should be monitored and managed to eliminate missing, invalid, or incomplete data.
  • Accuracy – data must be accurate enough for intended purposes and balanced with use, cost, effort, and timeliness.
  • Consistency – data should be compliant with requirements and consistent with other data sets over time; conflicting records are a sure sign of poor data management.
  • Relevance – data should be relevant to its intended purpose and undergo periodic review for quality assurance and feedback.
  • Timeliness – data must be current, preferably captured and analyzed in real-time to ensure insights are delivered while they’re still relevant.
  • Reliability – the data collection process must also be consistent across all collection points and systems over time.
  • Privacy – How was the data collected? Was the collection done following best practices? Are consumers aware of the usage, and did they give their consent?

Programmatic Advertising is one of the sectors that makes the most extensive use of data. The automated buying and selling of ads require massive amounts of data to determine which one to buy and how much to pay. If that data is of poor quality, publishers miss out on revenue, and advertisers fail to meet their KPIs.

The common problem with Programmatic Advertising is that it’s often a black box where trust and transparency issues get in the way of data-driven decision making. A lack of consistent metrics, widespread ad fraud, and visibility into third parties are just a few of the concerns plaguing the programmatic sector. For instance, to improve brand safety, it’s essential to have an established methodology for capturing data and ensuring its quality and accessibility. Programmatic Ad Buyers making data-driven decision-making must assess the information quality on the following criteria:

  • Marketers must now evaluate the quality of the data that is leveraged for decision making.
  • Data quality include numerous factors, including accuracy, completeness, reliability, timeliness, and consistency
  • Programmatic must ensure the ethical use of data and ensure consumer privacy is fully respected
  • Customer-centric organization understand what data is relevant for their users and how to best use the information best satisfy their needs

Programmatic Advertising efficiency depends on having easy access to integrated first-party data, leveraging second-party data for benchmarking and behavioral analytics, and finally verifying third-party data for authenticity and accuracy. While there are significant challenges, the industry continues to strive for greater transparency across the programmatic supply chain to build trust between consumers, advertisers, publishers, and ad tech vendors. Savvy marketers are demanding high-quality data to support the construct of compelling insights and the creation of more personal relationships that further empower the business.

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