Measurement-Minded Media Planning

Please be sure to read about Meta’s approach to measurement and the available tools in other blog posts of this series:
Get a Better Understanding of Digital Marketing with Meta's Measurement Solutions

Best Practices for Running a Conversion Lift Study

For organizations that put resources behind advertising, it’s important to understand the impact of their digital marketing efforts. However, many advertisers often overlook measurement planning, treating it as an afterthought in their media planning processes. This oversight can lead to various issues, including last-minute test setups, technical errors, tests not fit for what should be evaluated and difficulties in interpreting results.

We know that organizations that invest in measurement strategies and tools to understand what advertising tactics and channels are the most impactful are also better able to drive performance. In fact, according to Bain and Company, global businesses and organizations that regularly run experiments to test their advertising see increases in return on investment of up to 20%.

So how do organizations running digital advertising take advantage of this? They start their measurement planning at the same time as their media planning. This is because media and measurement are interlinked and rely on each other to drive successful campaigns. Below are some considerations to keep in mind as you kick off your media and measurement planning.

1. Clearly define campaign objectives and set a quantified target.
Before considering measurement, ensure that media campaigns each have a clearly defined objective and, where possible, a quantified realistic target. For example, you may have a campaign where the campaign objective is to drive 5,000 new registrations for a public service or increase the number of citizens reached by 5%.

2. Develop a learning question.
All tests and experiments should be rooted in a learning question linked to your campaign objective. What do you want to learn? And what will you do after the learning is realized? For example, you may want to test if automatic placements outperforms a businesses-as-usual (BAU) approach of manually choosing your own placements to get registrations for services - so your learning question might be ‘Will automatic placements outperform a BAU approach of manually choosing my own placements to drive registrations?’

3. Pick the right measurement tools.
Select the right Meta measurement tool to address your learning question. For example, for your automatic placements vs. business-as-usual manual placement test you might want to use A/B testing. Learn more about Meta’s measurement solutions and how they can be used to get results to inform your marketing decisions.

4. Link measurement tests to campaigns.
For your test, ensure you follow both media and measurement best practices. For example, continuing with automatic vs. manual placements, you may want to consider following our Performance 5 best practices - such as results validation and Conversion Lift best practices - such as having sufficient budget and data to get out the learning phase.

5. Use one test variable.
One of the core best practices for successful measurement results is ensuring all the variables are the same except for the variable you are interested in learning about. For example, if you are testing different creative approaches (image versus text based creative), ensure everything across the test cells are the same except the creative.

You may also want to take a long-term view and develop learning questions that look to define the various measurement questions you have. Then, systematically and regularly address them. Measurement via testing and learning should be a regular occurrence within your organization, driving continuous action and improvement. This is especially important as the advertising landscape shifts and you leverage new measurement tools to meet the needs of your organization.