How do you measure and improve display ad attribution in the health care sector?

1 Attribution models

When assigning credit to your display ads, there are various models to consider depending on your goals and data availability. Last-click assigns 100% of the credit to the last ad clicked before conversion, but it ignores the impact of other ads. First-click gives 100% of the credit to the first ad clicked before converting, which is useful for measuring awareness and acquisition. A linear model assigns equal credit to all ads clicked before converting, while time-decay gives more credit to ads clicked closer to the conversion. Position-based gives more credit to the first and last ads clicked before converting, and less credit to those in between. Each model has its own advantages and disadvantages, so you should choose one that best fits your needs.

2 Data sources

In order to measure your display ad attribution, it is necessary to collect and analyze data from different sources, including ad platforms, analytics tools, and CRM systems. Ad platforms can provide metrics such as impressions, clicks, conversions, cost, and revenue, as well as attribution reports based on their own models and methods. Analytics tools can provide metrics such as sessions, users, bounce rate, time on site, and goals with attribution reports based on your own settings and rules. CRM systems can provide metrics such as leads, opportunities, deals, and revenue with attribution reports based on your own criteria and logic.

3 Data integration

To improve your display ad attribution, you need to integrate and align your data from different sources, so that you can have a comprehensive and consistent view of your customer journey and display ad performance. To do this, you should use consistent identifiers such as UTM parameters to tag your display ad URLs. You should also use common metrics like conversions to compare your display ad results across different platforms and tools. Additionally, you should use compatible models such as the same model or a similar model in all platforms, or a cross-platform attribution tool.

4 Data analysis

To improve your display ad attribution, you also need to analyze your data from different perspectives in order to gain insights and make data-driven decisions. Channel analysis can help you understand how your display ads contribute to your overall marketing mix and funnel, while campaign analysis can show how your display ads align with your marketing objectives and strategies. Ad analysis, on the other hand, can provide insight into how your display ads appeal to your target audience and influence their behavior. These analyses can then be used to allocate budget and resources, optimize campaign design and execution, and test and improve ad quality and relevance.

5 Data optimization

To maximize your display ad attribution, it is essential to optimize your data collection and reporting, so that you have data that reflects your business reality and needs. This can be done through conversion tracking, which allows you to define and track your display ad goals and success metrics. Additionally, cookie consent is necessary to comply with data privacy laws and regulations, such as GDPR or CCPA. Lastly, data quality tools should be used to monitor and improve the quality of your display ad data, such as detecting and correcting errors, inconsistencies, duplicates, or gaps. This will ensure that your display ad data is complete, accurate, valid, and timely.

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?