Marketing Tactics: A Breakdown
Optimizing media can be tricky. You’re often stuck choosing between measuring at the channel level, which is too broad and coarse, or at the campaign level, which can be too granular with thousands of campaigns running at once.
This is where tactics – and specifically multi-tactic tests – come in and enable you to group campaigns in a way that’s just right for meaningful optimization.
A multi-tactic test is exactly what it sounds like: testing multiple campaign groups within a particular channel at the same time. It’s a middle ground that makes for effective measurement and optimization of an entire media portfolio.
Here’s how it works at Measured: Tactics are created by grouping campaigns based on two main attributes: First, The Platform – where the ads run, like YouTube or Facebook. Second, The Campaign’s Objective – what you want to achieve, such as prospecting or upper-funnel acquisition.
For example, “YouTube Prospecting” is a tactic. YouTube is the platform, and upper-funnel acquisition is the objective. Tactics like these provide a middle ground that makes it easier for you to optimize your entire media portfolio efficiently.
The structure of any tactic combines three basic parts:
- The ad platform housing the campaigns
- The campaign types (if applicable)
- The common strategy among those campaigns
A Smarter Way to Optimize
By grouping campaigns with similar objectives, you can optimize your media within different sections of your funnel seamlessly across different channels. Individually, the involved campaigns would provide too little data, but grouping similar ones together lets you determine how effective your efforts within the channel are for those specific purposes.
Imagine you’ve grouped all your Facebook Prospecting campaigns into one tactic and all your YouTube Prospecting campaigns into another. This lets you measure the performance of your upper funnel campaigns as a whole and move budgets between them without affecting your lower funnel campaigns.
Multi-Tactic Tests and Black-Box Campaigns
As we outlined in a post recently, marketing performance is currently more challenging to measure than ever before. When you run a test with Measured, our platform automatically splits out the results for each tactic, helping you measure interrelated incremental effects.
Adding to the challenge is the prominence of AI “black-box” campaign types in ad platforms (i.e., Google PMAX and Meta’s Advantage+). These campaigns make testing individual tactics less reliable due to overlapping audiences and inventory.
The need to measure the incrementality of each tactic, however, is more significant than ever. On the Measured platform, brands can run multi-tactic tests when they want to calibrate their Media Mix Modeling (MMM).
In our experience, brands often find that AI campaigns aren’t doing what they think they are, resulting in skewed insights.
Here’s how to measure black-box campaigns:
- Create measurement journeys starting with multi-tactic tests to establish a baseline.
- Set up tests carefully and closely monitor AI and standard campaign behavior during testing to ensure you're getting a clean signal.
- Measure AI campaign performance via testing with multiple tests over the course of the year and use observations to evolve and hone strategy and campaign settings.
- Expect that these AI campaigns are very likely not doing what you think they're doing.
Measured Learnings from Real Multi-Tactic Tests
We’ve gleaned some interesting insights from the multi-tactic tests that have run at Measured, particularly in terms of AI campaigns.
For example, with PMAX, we’ve found that iterative testing over multiple months is the optimal way to fine-tune its setup. PMAX buys media across multiple Google properties, which most brands are already buying individually.
By testing multiple Google tactics together with PMAX, we are able to understand the AI channel’s true, individual contribution to the business – and whether it was higher or lower than reported by the platform. We then make the appropriate modifications to PMAX’s settings, such as excluding brand keywords to make it more incremental.
Through this test-and-learn process, one luxury fashion brand was able to increase PMAX spend by 5X over two years while doubling their incremental ROAS.
When it comes to Meta’s Advantage+ Shopping Campaigns, it’s not unlikely for incrementality to be lower than expected following a test. Digging into this further, we’ve uncovered that certain settings such as non-exclusion of customers or site visitors – or lack of spending caps against them – could lead to contamination from other Meta tactics.
Similarly, we’ve found the same audiences being targeted in both ASC and non-ASC campaigns, leading to audience overlap. Without testing ASC alongside these other Meta campaigns in a multi-tactic test, we would not have been able to parse out the impact of Meta ASC alone.
In another example, one home goods retailer found they were experiencing this exact challenge with audience overlap. Testing just a month later after making the required settings changes revealed their incremental ROAS had increased by 3X.
The Measured Difference
In summary, not all tests are created equal and complex media budgets require sophisticated testing capabilities. With the rise of more nuanced campaign types like PMAX and ASC, multi-tactic tests are a proven way to understand their true business impact.
Measured has the industry's only incrementality attribution model that seamlessly integrates multi-tactic test results into your MMM. Our proprietary MMM helps marketers get maximum value from these tests by using the aggregate result to calibrate each individual tactic.
To learn how you can integrate multi-tactic test results in your MMM, set up a demo of the Measured platform today.