Dane Buchanan’s Post

Google has delayed cookie deprecation by another year 👀 While it does feel like we're chasing a mirage, future-proofing your measurement framework shouldn’t be sidelined. 🔍 𝐒𝐡𝐢𝐟𝐭 𝐘𝐨𝐮𝐫 𝐅𝐨𝐜𝐮𝐬: Move away from relying on attribution and embrace solutions like Marketing Mix Modeling (MMM) and Geo-Lift testing. Focusing on incrementality leads to better business outcomes from media. ⏰ 𝐔𝐬𝐞 𝐭𝐡𝐞 𝐓𝐢𝐦𝐞 𝐖𝐢𝐬𝐞𝐥𝐲: This extra year is a gift - use it to fine-tune and test your measurement framework. 🚫 𝐅𝐮𝐭𝐮𝐫𝐞-𝐏𝐫𝐨𝐨𝐟: 2024 won’t be the death of the cookie, but it should be the end of over-reliance on attribution. 📆 Don’t push improving your measurement framework to 2025! https://lnkd.in/eWQnnqkB https://lnkd.in/eSqQeBSY

Matillion is central to enabling our data strategy at M&C Saatchi Performance It was great to speak at their AI Spring Launch event, sharing our thoughts and experience. We’re super excited about the new AI features within the Matillion Data Productivity Cloud which will enable us to scale/ productionize some of our AI testing/ solutions. . . . And yes, making data analogies about the Moon is my Roman Empire 🤦♂️

Econometrics (MMM) is a hot topic in media measurement right now. With numerous blogs, articles, and podcasts, it can be hard to know which ones are worth spending time engaging with. Dr Grace Kite's Mobile Dev Memo Podcast on Econometric Measurement for Advertising is one I highly recommend: https://lnkd.in/e8UxbmGJ It’s 45 minutes well spent (and no, don’t 2x the speed). It will give you a great foundation on why MMM is important to you and your business. Some key highlights: 💭 Think differently - a Multi-Touch Attribution (MTA) shaped hole doesn’t mean you need to fill it with an MTA-shaped solution. 🔏 Privacy changes give us a chance to rethink our approach to media measurement. 💱 MTA did give us a precise answer, but we were potentially asking the wrong question. MMM gives us a slightly more holistic answer to the right question. 🤼 For digital marketers, adding MMM to their measurement stack is not just a technical change, it’s also a major cultural change – this takes time, so ensure you’re bringing everyone on the journey. 💎 Keep your MMM simple and explainable, complexity can be added as and when required. It’s not just about adapting to privacy changes, it’s about finding opportunities to focus on what’s genuinely better for marketers and, importantly, the entire business. Adding MMM to your measurement stack allows for a deeper dive into understanding of what drives sales and can act as the Rosetta stone for decoding the key drivers of your business.

Open-source Marketing Mix Modeling (MMM) received a new addition last week with Google’s release of Meridian. Meridian will replace Google's unofficial lightweight MMM solution in the coming months. - Google's Meridian: https://lnkd.in/esJS-yWx - Lightweight MMM: https://lnkd.in/erEhvQW5 Alongside Meridian, the other two major open-source MMM initiatives are: - Meta's Robyn: https://lnkd.in/e2ApWyVd - Uber's Orbit: https://lnkd.in/eRiEtgQ3 Open-source MMMs are making it easier for brands and agencies to dive into building their own MMMs. But keep in mind: ✋ MMM is a complex media measurement solution – just like owning a hammer and chisel doesn't make you a skilled carpenter, simply using these libraries doesn’t guarantee robust/ successful media measurement 🧠 I recommend initially working with an experienced consultancy or agency to implement your MMM projects. At MCSP, we offer this support for our clients. 🔥 Once your MMM framework has demonstrated its impact on media budgeting and optimization, you can then think about in-housing – but there is no rush if things are going well. Media measurement is evolving, and MMM will be a key player. However, if done badly, it can cause your key stakeholders to lose faith in the approach and potentially lead to poor media investment decisions. 🏇 Get started with MMM as soon as possible, but look for experience rather than quick fixes.

Econometrics and the C-suite is certainly worth a read. The opening by Les Binet should be enough to convince even the most ardent of MMM* skeptics of its value to their business. 🔃 The paper can be found here: https://lnkd.in/euqfabGT From the opening: “Marketing can have many different goals: to build awareness, to drive traffic, to recruit customers, to increase market share, and so on. But the ultimate goal, for commercial firms at least, is always the same: to generate incremental financial value.” Econometrics (aka Media Mix Modelling, Marketing Mix Modelling, MMM) is how you can prove the impact of your marketing efforts on your bottom line. While there's a perception that MMMs are slow and outdated, advancements in tech, AI, and open-source initiatives by Google & Meta have transformed them. MMMs can now be updated more rapidly and provide more detailed insights than ever before, a trend set to continue. However, the initial phase does demand significant effort - preparing accurate data, specifying models, and so on. They might not be the cheapest measurement solution, but then again, neither is investing your marketing budget behind the wrong channel or campaign and delivering zero incremental value. 🔖 With the anticipated end of cookies by Q3 2024, there's no time to waste: https://lnkd.in/eUqgv5t7 If you were to start now, you’d have enough time to prepare your data, set up your first Econometric model, and see its potential in shaping your media campaigns before the cookie crumbles. 👟 As an immediate step, I recommend contacting your media agency or MMM consultancy to get started. Jumping straight into an in-house solution is not ideal; it's better to think of that once your models are established and delivering value. *MMM = Media Mix Modelling = Marketing Mix Modelling = Econometrics. Let's not complicate an already complicated subject by debating the name.

Big thanks to Big Data LDN and Matillion for hosting us this week. It was awesome to talk about our journey with Matillion over the past year. Data is at the heart of everything we do at M&C Saatchi Performance. Matillion has helped us streamline our data processes, ensuring all our teams and clients have actionable data at their fingertips. While we might have been one of the few presentations not to mention AI, remember, a car without fuel won’t go very far; AI is no different.