Planning for Privacy First: Implementing Incrementality

Firstly, we introduced the concept of privacy-first. Then we looked at the main scenarios for privacy-first marketing. In our last segment, we considered planning for privacy-first in the short and long term. In our latest blog, we’re going to look at how implementing incrementality can help businesses.

Defining Incrementality

Incrementality will become a core part of your service option in privacy-first marketing, so it is important to understand it thoroughly. So, put simply, incrementality is the degree to which a measurement method estimates the true causal effect of an isolated marketing activity.

Working out incrementality is simple. You can implement incrementality into your advertising tests. One group experiences a changeable variable – like an asset, copy or audience profile – whilst the other other group doesn’t. That means they become the control. After your campaign finishes, you can analyse your strategies which will allow you to see which was most cost-effective, had the best performance or achieved the fastest results.

Comparing these results to your control group’s performance and noting the difference will help you to calculate the impact of implementing incrementality into your marketing.

As a result, incrementality becomes a hugely valuable North Star for brands because it allows you to truly assess the impact of your marketing. It is a framework for understanding how the change in measurement affects your marketing and the further measures you can take to maximise or minimise this impact. Applying advertising processes based on incrementality is beneficial for the business too. It improves decision making and overall business resilience which is vital in the current economic climate.

Implementing incrementality can help your business grow.

The Limits of Implementing Incrementality

Although incrementality is very important, it does has some issues. Proxy metrics that work for one vertical don’t always extrapolate exactly to other situations. Furthermore, it’s important to ensure that you validate your proxy metrics thoroughly. Why? Well, validating these metrics can help your businesses to better understand your marketing outcomes and how your measuring processes can assist them. In contrast, implementing incrementality through invalidated proxy metrics may not help you at all!

It’s important to balance everything. Businesses that are trying to validate proxy metrics need to make sure they mix testing new ideas with established, well-practised marketing techniques in order to ensure they are not just totally wasting their time, effort and financial resources.

At the same time, implementing incrementality is absolutely essential for businesses that want to get the most out of their marketing metrics. It’s worth noting that different methods will inevitably have higher levels of incrementality depending on the metric you are measuring.

The Ideal Models for Implementing Incrementality

For non-incremental models, invalidated proxy metrics focus on attribution or counting. As already explained in this series, updates to device security have made these results less accurate. Validated proxies that use rule-based attribution, such as Facebook Pixel are more effective, however, they still aren’t the ideal outcome. The best model for these models is measuring in terms of business revenue, via total sales of a product or service.

For randomised tests, experiments such as Brand Lift are useful as validated proxies. However, on the other hand, you still want to try and increase results through sales experiments using calibrated incremental values. Calibrated and uncalibrated models both have the same incremental approach, which is using the marketing mix model effectively to assess the effectiveness, efficiency and return on business investment.

The Final Word: Incrementality

Evaluating the incrementality of your marketing methods alongside the incrementality of your statistical metrics is the perfect way for businesses to find the best metrics for ideal business outcomes.  Using a marketing mix model gives you a higher level of incrementality for assessing your choices, and a calibrated MMM comes even close to understanding the true impact of your advertising, which is critical in the privacy-first marketing environment.

In our final instalment, we’ll be assessing how implementing incrementality, and the short and long-term planning for privacy can be supported by choosing the right approach to marketing for your firm.