1. Keep momentum with marketing mix modeling

A noteworthy solution to navigate the challenge of third-party cookie deprecation is marketing mix modeling (MMM), a technique well-regarded for discerning channel and sub-channel impacts on KPIs such as sales, leads, app downloads, and more, without reliance on third-party cookies. This is not a new concept; this approach to measurement has actually been around for decades. Marketing mix modeling is a tried-and-true method that is regaining popularity with the deprecation of cookies.

What sets MMM apart is its independence from third-party cookies, relying instead on aggregate-level data. This ensures a seamless flow in extracting valuable insights for strategic decision-making. These insights can be used to help businesses clarify a multitude of decisions including channel budget allocation, scenario planning, sales forecasting, and consideration of various market dynamics, both online and offline.

For example, a retail brand might use MMM to uncover an optimal budget size or to assess the immediate impact of media initiatives in promoting a new product launch. This empowers brands to pinpoint their prime media investment and blend, facilitating informed decisions in the dynamic landscape of marketing strategies.

2. Understand micro attribution analysis

If you’re seeking an even more detailed analysis at the campaign level or across devices, micro attribution analysis is the right technique for the job. This type of model is trained and tuned without cookies, using aggregated campaign-level metrics (ex: spend, activity by market) to enable a granular understanding of marketing effectiveness. Marketers can precisely estimate the impact of their activities at the campaign level and optimize budgets across devices, creatives, channels, sub-channels, and more on a weekly basis. This approach focuses on estimating how marketing activities influence conversions during a specific week. It only uses data relevant to recent marketing efforts driving the previous week's conversions and is a helpful tool to accurately capture any seasonal variations. This helps you understand what’s working now with more frequent model refreshes to best plan for the short term.

For retail clients, we can identify recent marketing, product, or tactic trends that may be spiking recent conversions. Capitalizing on those trends can dramatically increase marketing efficiency. Similarly, clients with seasonal businesses may generate marketing strategies based on what worked in the previous year. So, this type of measurement can enable smart decisions for how to ramp up or down spend to lift marketing performance when planning for those seasons.

3. Learn regression-based attribution analysis

In addition to marketing mix modeling and micro attribution, regression-based attribution (RBA) is another modeling approach to understand the impact of marketing. Like micro attribution in its modeling granularity, RBA offers another viable alternative. This methodology analyzes and quantifies the impact of various marketing touchpoints like website interactions or content engagement, accommodating for the complexities of the evolving tracking landscape. RBA differs from micro attribution due to the type of model used for measurement. You might choose RBA over micro attribution based on the size and scale of tactics or length of campaign tests that you want to estimate the contribution for.

As the era of third-party cookie reliance draws to a close, we continue to drive innovation through the development of new forms of measurement. Our commitment extends beyond adapting to change; it centers around driving business impact through actionable insights, supported by cutting-edge measurement techniques. Embrace the future of measurement with Merkle, where innovation meets customization to ensure your success in an evolving digital landscape.