Marketing Measurement 101: How to Plan, Design, and Execute a Successful Study

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As brands push to make more data-driven marketing decisions, data measurement tools have become increasingly accessible within major marketing platforms and via third-party partners. Despite what many marketers hope, there is no silver bullet solution to solve all marketing measurement challenges. Instead, a focus on measurement should be treated like a toolbox with specific uses and solutions to a variety of marketing questions.

Read on for guidance on how to navigate the complicated, multi-platform measurement landscape. We’ll explain how to determine if a study is necessary, how to select the right study to match your needs, and how to leverage data for maximum business impact.

Why Measurement Studies Are Needed

Marketers are constantly asked to show how their decisions deliver on the brand’s bottom line. Whether it’s showing strong ROI, growth in sales, or increased brand recognition, you need to evaluate performance results on a regular basis. But the results aren’t always black and white percentages, especially when it comes to branding initiatives and creative decisions.

In the past, advertisers relied on judgement and experience to build campaigns that appeared to perform well, but this decision making was hard to prove objectively. Advances in advertising technologies have enabled marketers to better define and track audiences, see how they interact with media, and judge how media performs. Yet we still need sound methods to make sense of all this data. Measurement studies give a results-oriented approach to data and can help you illustrate the impact of your work. As these tools continue to improve, measurement will be the foundation for clearer decision making in marketing.

Available Measurement Options

Just as there are myriad metrics available to measure performance, there are many study options marketers can use. It’s important to note that each choice serves a particular purpose in evaluating performance, and there is no one-size-fits-all study that can do everything.

Across the digital advertising landscape, both platforms (first-party) and measurement partners (third-party) provide study options that can measure activity across the marketing funnel. Choosing the right partner depends on what you’re looking to assess, the size of the media execution, and your available spend. First-party studies require less minimum spend and execution, have a quicker results turnaround, and offer more granular results. However, insights are only available for the chosen platform and study offerings vary by platform.

Third-party studies offer more study variety, including options that cross platforms and channels, and more objective analysis of results and insights. However, measurement partners require steeper spend and data minimums, are slower to turn around results, and are less transparent about methodology. The measurement partner landscape is also fractured with a variety of providers, ranging from major firms like Nielsen and Kantar to more niche consultancies. For the best possible results, marketers should make sure their measurement needs fit the scope of their measurement provider.

Across all platforms and measurement partners, there are a wide array of measurement study options to cover everything from awareness to conversion. Current options can be grouped into brand, conversion lift, penetration, econometric, and attribution studies. These studies look to address different areas of the funnel, as detailed below:

– Brand Study: Measures response to a brand after a campaign (e.g. brand recall)
– Conversion Lift Study: Measures the increase in conversions from running a campaign (e.g. sales lift)
– Penetration Study: Measures the reach of campaigns on target audiences (e.g. total audience ratings, digital ad ratings)
– Econometric Analysis: Measures different drivers of a business to quantify their impact, usually measured with ROI (e.g. marketing-mix modeling)
– Attribution Solutions: Measures the contribution of different media touchpoints toward conversion (e.g. multi-touch attribution)

It’s important that your choice of study aligns with campaign KPIs and strategic business questions to ensure you get the most out of your time and effort. Studies conducted without a plan for absorbing the data lead to poor insights and next steps. When you work with Adaptly on a measurement study, we’ll vet the partner options for you and help you set up, design, and execute a successful study.

When to Conduct a Study

There is no strict rule about the best time to conduct a measurement study. Studies should be tied into your brand’s decision-making process and run when their results will have the most impact. Different studies can help marketers improve campaigns in flight, gain better post-campaign analysis, or plan for future campaigns.

Brand, conversion lift, and penetration studies, for instance, are designed to be run over short periods. They can be deployed while a campaign is in process to make tactical adjustments as well as post-campaign analyses. Econometric analyses, on the other hand, require years worth of data to be effective, so these studies should only be run after minimum data requirements are met. Attribution solutions studies can be run more often, though it takes longer to develop measurement methodology in the case of multi-touch studies.

More important than when to conduct a study is understanding the measurement scope of each option and how that can be leveraged effectively to deliver on the desired results.

How to Design a Study

Studies should be designed to measure outcomes that align with business needs – the KPIs on which campaigns are planned. For example, if you’re looking to measure awareness, a brand study is the most appropriate option. Once you have aligned the study type with your KPIs, be sure to understand the methodology, data, and statistical requirements of each test. Methodologies can range from simple A/B testing to advanced machine learning methods.

Whatever the methodology is, there will be data requirements to get statistically significant results. Some are easier to track, like hitting minimum impression levels, while others might require testing to verify, such as sample size validity. To ensure a test’s integrity, verify that your sample data is relevant and large enough for the statistical method at hand. Hitting those requirements will help you achieve statistical significance and give you confidence in your study. You can work closely with a measurement partner to design the study and figure out what those levels are.

How to Interpret and Leverage Results

Results are delivered in the form of hard data – numbers and stats – so it’s important to know how to interpret it. A key step is to learn the statistics in your study. Whether your study looked at confidence levels, R-squared values, error terms, or another factor, understanding the type of measurement will help you see how your study performed so you can leverage results into actionable items.

When leveraging results, make sure your insights answer the key study questions posed before beginning the process. Too often, a study that’s well designed and well executed goes wrong at this final stage when interpretations stray from the scope of the study. When defined correctly, your study results can help you improve campaign results, media planning, creative impact, and many more aspects of your marketing operation. You conducted this study for a reason, and you must stick to this reasoning throughout to maximize its impact.