The most important thing for a CMO to figure out is this, "If I have one dollar to spend on advertising, where should I spend it, and how much will I get in return?"

In this episode, we chat with Michael Kaminsky to learn different ways brands can measure the incremental impacts of marketing and how to choose the right measurement approach.

On October 25th, we're bringing together top minds in marketing and data for a global virtual event—SuperSummit.

Join us for discussions on the latest trends in marketing data, including Generative AI, Big Data, and Measurement & Privacy.

Sign up for free: https://supermetrics.com/supersummit

In this episode, we're joined by our original host, Anna Shutko. Anna is now an Analytics Consultant at Supermetrics. She's using her knowledge of marketing and data to help companies solve their analytics challenges.

Anna and Edward will discuss the importance of first-party data in marketing and why CMOs should invest in a marketing data warehouse.

On October 25th, we're bringing together top minds in marketing and data for a global virtual event—SuperSummit.

Join us for discussions on the latest trends in marketing data, including Generative AI, Big Data, and Measurement & Privacy.

Sign up for free: https://supermetrics.com/supersummit

Most marketing data problems are masquerading as data governance problems.

If you don’t know which campaigns are driving results, you should revisit your tagging setup. If you’re unsure who has access to what data, you need to improve your data-sharing process.

Without a good governance strategy, data becomes a liability rather than an asset.

In this episode, Evan Kaeding, Lead Solutions Engineer at Supermetrics, and Buki Froelke, Senior Product Manager at Google, will discuss how CMO can build a marketing data governance strategy and improve data quality.

As we transition to a privacy-first online environment, marketing leaders need to be ready to measure marketing differently.

MMM isn’t a new technology, but automation has made it a more efficient and accessible tool that can help businesses maximize their marketing ROI without relying on user-level data.

In this episode, we'll cover MMM works, the results it can drive, and the type of businesses it's suitable for.

In this episode, we’re joined by Bartosz Schneider, Lead Professional Services Consultant at Supermetrics, and we’re digging into a super important topic today, and that is the marketing analytics lifecycle and how to deploy successful analytics that drives value.

Most marketing data problems are masquerading as data governance problems.

If you don’t know which campaigns are driving results, you should revisit your tagging setup. If you’re unsure, who has access to what data, you need to improve your data-sharing process.

Without a good governance strategy, data becomes a liability rather than an asset.

In this episode, we discuss how you can build a marketing data governance strategy and improve trust in your data.

Can you trust your data?

If not, how can you justify your marketing strategy and budget allocation?

Our research shows that 51% of marketing leaders struggle with unreliable, siloed, and scattered data. At the same time, most marketing data problems can be traced back to a lack of marketing data governance.

But what is marketing data governance? We've narrowed it down to a framework of three pillars—data access, data quality, and data security.

There are two main reasons why you want to own your data. First, you can get rid of data silos and measure your marketing performance holistically.

Second, you don't need to rely on the data retention policies of Google, Facebook, or any other platforms. With full access to your historical data, you can pull the exact datasets you need to make better decisions about the future.

But how can you take control of your marketing data? Listen to this episode to find out.

You may have heard of the Toyota Way or Kaizen. It's a manufacturing approach that aims to maximize efficiency and reduce waste. Kaizen means 'continuous improvement' in Japanese.

So how can you apply Kaizen to marketing data management? We chat with Zeke Camusio, CEO of Data Speaks, to figure it out.

In this episode, we discuss two approaches to marketing data—centralized vs. decentralized.

With a centralized data access model, the data team can easily manage the data quality and ensure it complies with the internal data policies before distributing it to stakeholders like marketing.

On the other hand, a decentralized data model doesn't require data to be stored in a data warehouse or data lake. Rather, the data users can quickly get the raw data directly from different sources into their go-to reporting and analytics tools.

At Supermetrics, we're seeing many analytical-matured companies get the best of both worlds by combining both approaches.

Read more about centralized vs. decentralized data access models: https://supermetrics.com/blog/supermetrics-vs

Check out Supermetrics: https://supermetrics.com/start-trial