Adtech, or advertising technology, uses software and technology to automate, optimize, and measure the effectiveness of digital advertising campaigns. The adtech industry is constantly evolving, with new technologies and platforms always emerging. One of the key factors that set successful adtech companies apart is their ability to leverage a wide variety of partnerships. Adtech companies partner with publishers for ad placement on websites, mobile apps, CTV, DOOH, streaming audio, and with marketers and ad verification services for ad legitimacy. Third-party tracking companies for data analysis to optimize campaigns and improve ROI are also common. Working with so many partners in one ecosystem can lead to discrepancies in the data, as different partners may have different systems and processes for collecting, storing, and reporting data. These discrepancies can significantly impact tracking performance, revenue, and the time spent troubleshooting and monitoring these issues. For example, suppose ad impression data reported by a publisher does not match the data reported by a third-party tracking company. In that case, it can take time to determine which data is accurate. This can lead to lost revenue, as optimizing campaigns and deciding where to allocate ad spend becomes challenging.
Furthermore, these discrepancies can also create a lot of manual work for adtech companies, as they need to understand the cause of the discrepancy and troubleshoot it. This can involve logging into different systems, pulling data, and comparing it to identify the root cause of the problem. This can be time-consuming and tedious, leading to errors and inaccuracies if not done correctly. Additionally, the discrepancies in data can also lead to data privacy and security issues, which is a critical concern for companies in the adtech industry.
1. Implement Data Governance Policies: Establishing policies can help adtech companies ensure that data is collected, stored, and reported consistently and accurately. This can minimize the number of discrepancies and make it easier to troubleshoot when they do occur.
2. Use Automated Data Quality Tools: these tools help companies monitor data, identify discrepancies, and alert teams to potential issues. They also automate the process of cleaning and standardizing data, which can reduce the amount of manual work required to troubleshoot discrepancies.
3. Conduct Regular Data Audits: Regular data audits can help adtech companies identify and address discrepancies that may have gone unnoticed. This can be done through automated data quality tools or manual data reviews. The result can be a report highlighting any discrepancies and providing recommendations for addressing them.
4. Establish Communication Protocols: Having clear communication protocols in place can help adtech companies quickly resolve discrepancies and minimize the impact on their business. This includes setting up dedicated teams or individuals responsible for troubleshooting data issues and establishing clear lines of communication between teams and partners.
5. Invest in Data Management Platforms: Data management platforms can help adtech companies centralize and standardize data, making identifying and troubleshooting discrepancies easier. These platforms can also provide advanced analytics capabilities, which can help adtech companies understand the root cause of discrepancies and make data-driven decisions.
Reach out to Camelus today to see how we can help centralize your data and help manage discrepancies for your organization.
Comments