Unleash Your Data Superpower with Google Cloud Cortex Framework

Picture the scene: It’s the late 1920s in the United States. People eat cereal. Only two brands really exist in the market: Post and Kellogg’s. Spoiler alert: You’d be forgiven for not knowing much about Post. C.W. Post was, in fact, a patient at the Kellogg brothers’ sanitarium who stole the recipe from Kellogg and set up on his own cereal business, creating a great rivalry between the two companies. But then it gets worse for business everywhere: The Great Depression hits.

As leaders of their companies, both men adopted very different approaches: Post did the prudent thing and significantly cut advertising costs. Kellogg doubled his ad budget, moved into radio, and pushed a new cereal (Rice Krispies with the famous “Snap, Crackle, and Pop” tagline — perfect for radio). Not a time to be bullish. Or was it? Turns out, cereal is a dish best served cold.

This famous story perfectly highlights the challenge in accurately reallocating advertising “cost” to “investment.” Something Kellogg did well to understand in those challenging Great Depression years.

Modern Advertising Needs

Fast forward today, and  while it’s commonly accepted that advertising is an investment and not an expense, it is still accounted for as an operating expense (rather than capital expense) and is often trimmed when times are tough. And 2024 has certainly proven to be a year of both geopolitical and economic turmoil. The pressure is mounting on marketers to prove the value of their advertising investments in the form of tangible business outcomes.

However, aside from direct response or lower-funnel advertising tactics with measurable, relatively immediate results, the broad bucket of advertising often leaves CFOs and other executives struggling with inconsistent delivery of ROI. Additionally, advertising ROI is often opaque since true multi-touch attribution is challenging.

In the same way as any investment, return is not guaranteed and often takes time. The immediacy of lower funnel media activations is compelling but is proven not to impact the long-term multiplier (LTM) that ensures brand sustainability over time. Rather, this is the role of brand advertising. With $1 trillion advertising spend estimated for 2024, and 69% of that invested in digital channels, the stakes have never been higher for driving as much efficiency and effectiveness from that investment to deliver real value to the business. 

Against this backdrop, brands are seeking to protect investments as studies show a negative impact on LTM when brand advertising is pulled. Nobody wants to run a real-time experiment to discover long-term impact, requiring huge investment and over-indexing to rebalance. So, it helps the situation to be able to better link the overall media investment to actual sales. 

Strategic Data Insights for Smarter Decisions

While traditional methods, including Marketing Mix Modeling (MMMs)  have their place, brands are increasingly realizing the benefits of conducting regular, data-driven testing on a large scale to effectively allocate resources that enhance both immediate and future sales. That is why three or more years of media and sales data is essential to calibrate a baseline upon which to monitor improvements via different channels.

But instead of just running historic analysis of the causal link between media investment and sales, wouldn’t it be more beneficial to build on that by experimenting different strategies and tactics to see how that impacts sales? To truly harness the power of these insights, the first step is accessing the data across different platforms. If we look at video investment as a segment of that, Meta, YouTube and TikTok’s share in 2023 was 30.1%, 8.3% and 6.5% respectively.3  A good place to start, right? As businesses explore diverse strategies to boost sales, the strategic focus shifts towards leveraging comprehensive data analysis and advanced technologies like artificial intelligence (AI) and machine learning (ML).

Overcoming ROI Challenges Strategically

Increasingly, businesses are seeking access to this data at macro levels – cross-brand, cross-category, cross-market – and micro levels – for in-flight campaign performance instead of just relying on a media agency to report back. Plus, they are seeking to find patterns and predict outcomes from analyses of substantial amounts of data and leveraging AI and ML to do so.  And while the post cookie ecosystem remains in flux, smart marketers are focusing more and more on how their own first-party data can support better media outcomes. Marketing leaders now understand that data can be their superpower to unlock better results. And they understand the value of influencing cross functionally to ensure data drives better decisions.

One compelling solution for these needs is Google Cloud Cortex Framework. Through the Cortex data foundation, brands or houses of brands, can access pre-built connectors, data models and analytics views to monitor and gain insights from multi-brand, multi-market investments with these platforms, all in a single, turn-key solution. As companies continue to expand their data requirements, time, effort and costs can rapidly increase, making crucial business insights an imperative.

With Google Cloud Cortex Framework, businesses can also measure audience performance and video engagement across different media platforms, as well as analyze key performance indicators (KPIs) over time. Additionally, organizations can measure costs against business outcomes to ensure the proper ROI for investments.

Additionally, there are a number of use-cases for businesses that extend across a variety of industries. For example, a retail and CPG company could use Google Cloud Cortex Framework to find out which audiences drive the highest sales impact and how their engagement differs across platforms. This information could then be used to strategically distribute budget and investments to drive the greatest return. Further insights could also be harnessed to develop creative solutions for driving sales and solving business challenges.

Real Insights from Real Data

In the evolving landscape of advertising, the challenge of proving ROI remains significant, urging businesses to adopt more data-driven strategies. The integration of AI and machine learning offers a powerful means to analyze complex datasets, providing predictive insights that guide strategic decisions. Leveraging first-party data has become crucial in enhancing media outcomes, especially as the digital ecosystem undergoes significant changes. By focusing on comprehensive data analysis, businesses can better align their investments with tangible results, ensuring long-term profitability and sustainability.

We all know advertising effectively drives ROI — make data your superpower to unlock critical insights on what “effective” means for your brand across channels, creative and media executions.