Law 25: How To Adapt Your Data Marketing Strategies

Digital Marketing / August 17, 2023

How does Law 25 affect your marketing.

To put it simply, Law 25 presents us with two significant challenges: a decrease in the quantity of data collected and a decline in its accuracy. These challenges will inevitably affect the analyses and the efficacy of marketing campaigns.

Although these new challenges can seem like a serious drawback for digital targeting and retargeting practices, there are various solutions that will enable us to move towards a future where respect for consumers’ personal data is prioritized. Many of these solutions are also being considered in anticipation of the disappearance of third-party cookies, offering companies an opportunity to prepare accordingly.

What Should You do Now.

01. Utilize 1st Party Cookies

First-party cookies are created and controlled by the website or domain the user is actively visiting. You can leverage 1st party cookies to monitor how users interact with your website, track page views, click events, conversion actions, and other engagement metrics. This allows you to gather valuable insights about user preferences and optimize their experience without relying on 3rd party cookies to display ads or personalized content.

But don’t forget – you need to have a robust cookie consent management solution in place. This involves displaying a cookie consent banner or pop-up to visitors, informing them about the types of cookies used on your website and obtaining their consent for their use. 

02. Implement User Authentication and Account Tracking

Encourage users to create accounts or log in to your website. By implementing user authentication systems, you can associate user activity with specific accounts. This enables you to track user behavior across sessions, personalize experiences, and measure engagement without relying on 3rd party cookies.

03. Utilize Alternative Tracking Methods

Explore alternative tracking methods such as server-side tracking or utilizing other non-cookie identifiers like local storage, device IDs, or Universal ID (like Google Privacy sandbox with Topics API). These methods can help you gather data about user behavior without relying heavily on 3rd party cookies. However, you need to ensure that you comply with privacy regulations and respect user preferences when implementing such solutions.

04. Explore a secured environment with Data clean rooms

Beyond the “walled gardens” such as Google, some companies are working to build omnichannel data clean rooms. 

 The goal of a data clean room is to create a privacy-preserving space where customer data can be joined and utilized in a collaborative manner. No PII data is stored and only aggregated data is shared back to the business (data matching). In order to leverage large, aggregated datasets of consumer behavior to provide insight into critical factors like performance, demographics, campaigns, etc. 

Of course, those technologies can’t exist without human intervention to Set-up, share insights, aggregate data sets, and analyze results to enhance collaboration and goals. (we can certainly help with that!).

05. Enable probabilistic data in GA4

A good way to deal with the shortage of data in Google Analytics 4 (GA4) is by using the “behavior modelling” feature. This tool uses advanced computer methods to guess and imitate how users behave, which can help fill in missing data. But then again, it’s important to note that Google only uses data from people who agree to share it – usually those who are more involved with the brand.

06. Utilize Media Mix Modelling

With Law 25, there are several breaks in direct measurement between a campaign and a conversion, making analysis incomplete. One solution is to turn to: media mix modelling (MMM). 

Media mix modelling (MMM) is awesome because it allows us to measure the impact of marketing and advertising campaigns to determine how various channels contribute to the objectives. Media mix modelling brings all the data together for thorough analyses and even allows you to predict future performance which is crucial to develop successful marketing strategies. It’s important to note though that these models need lots of data (a good budget and at least two years’ worth) to work well.

At Bloom, we are obsessed with performance and data – which is why we created our very own media mix modelling tool: Polaris. It leverages econometrics to reconcile platform reporting and Google Analytics results. Polaris effectively helps our teams craft more efficient and data-driven media plans.

Curious about how to effectively address this new challenge for your marketing strategies? Feel free to reach out to us! Our team of experts is eager to assist you in reaching your business goals.