What emerging trends are changing display ad analytics?

2 Real-time bidding

Real-time bidding (RTB) is a process that enables advertisers to bid on display ad inventory in real time, based on various criteria, such as audience, context, or performance. RTB allows you to access a wider range of inventory, reduce costs, and target your ads more precisely. However, RTB also poses some challenges for display ad analytics, such as data quality, privacy, and fraud. You need to use reliable and transparent tools and platforms to monitor and measure your RTB campaigns and ensure they meet your goals and standards.

3 Artificial intelligence

Artificial intelligence (AI) is a technology that uses machine learning, natural language processing, computer vision, and other techniques to perform tasks that normally require human intelligence. AI can help you improve your display ad analytics in several ways, such as predicting customer behavior and preferences based on historical and contextual data, generating and testing creative and personalized ad content and formats, optimizing ad placement, frequency, and timing based on real-time feedback, and analyzing large and complex data sets to provide actionable insights and recommendations.

4 Video and interactive ads

Video and interactive ads are becoming more popular and effective as display ad formats, especially on mobile and social media platforms. These ads can capture attention, elicit emotions, and encourage interaction, leading to higher engagement and conversion rates. To measure their performance and impact, however, you need to go beyond traditional display ad analytics such as impressions, clicks, and CTR. Instead, more advanced metrics should be used such as viewability (the percentage of time and space an ad is visible on the screen), completion rate (the percentage of users who watch a video ad until the end), interaction rate (the percentage of users who interact with an interactive ad), and brand lift (the increase in brand awareness, recall, or preference as a result of an ad exposure).

5 Privacy and consent

Privacy and consent are becoming increasingly important and complex issues for display ad analytics, as consumers become more informed and concerned about their data. Regulations like the GDPR and CCPA impose strict rules and penalties on data collection and processing, while browser and platform changes limit the availability and accuracy of data. To stay compliant, you need to adjust your display ad analytics to these changes while still delivering relevant and effective ads. Some strategies you can use include leveraging first-party data, contextual data, anonymized or aggregated data, as well as consent management platforms. These tools can help you collect, store, and manage user consent for data collection and processing.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?