The Future of Measurement: How to Uncover Cross-Channel Insights With Media Mix Analysis

As digital marketing increases in complexity, how to measure what works (and what doesn’t) evolves, too. From the shifting sands around third-party cookies to the rise of over-the-top (OTT) advertising, every corner of digital is continually impacted by technological advances, consumer behavior, and economic dynamics.

How then can businesses, with access to more data than ever before, know that they are identifying and interpreting the right information into actionable insights that can inform their marketing success at scale?

Cross-channel visibility doesn’t have to be out of reach. A complete picture of your digital marketing is possible for any business with strategic methods of analysis, access to the right insights, and some additional ingenuity. Within the changing measurement landscape, many marketers feel increased pressure to demonstrate the value of their marketing as brands seek to further quantify the results of their marketing efforts. If the challenge is how to allocate your marketing budget and conduct effective media mix planning within the unstable landscape of multi-touch attribution, the answer may still be simpler than you think.

Though brands are facing more challenges and marketers more pressure to measure their marketing efforts, there are still clear ways forward.

Optimize your media mix with audience insights

The optimal media mix varies from brand to brand, but analyzing and adjusting your media mix can help you ensure that you’re getting the most out of your ad spending—and your entire marketing strategy. Insights from your media mix shine a light on your best audiences. These deep learnings into your audiences’ behaviors not only hold power across widespread areas of your marketing plan but can also translate into real business results.

A holistic approach to media mix analysis and testing includes harnessing your first-party data in the upcoming absence of cookies and positioning your company to succeed. Through this and more, brands can improve their ability to identify and segment audiences—enabling themselves to thrive with next-gen measurement.

Plan your ad influence — precise touch, wide reach

A brand’s media mix is composed of the marketing channels to maximize reach, including social media, search, programmatic ads, digital streaming, video streaming, radio streaming, and much more. As marketers plan a brand’s media mix, the key questions they must answer are:

  • On which channels should I advertise?
  • How frequently?
  • When?

An effective media mix should be just that—a mix. Advertising with the right diverse range of channels expands your brand’s influence and allows you to harness the various strengths and weaknesses of each channel, from reach to creative impact.

There’s no need to ‘throw things at the wall and see what sticks.” The right data and insights illuminate the best media mix for your brand and business.

Media mix analysis and testing allow marketers to determine the optimal assortment of marketing touches across platforms.

Though brands may be tempted to funnel their entire ad influence into one or two popular channels, a varied media mix offers more powerful advantages. If you limit your media spending to just a single channel, you risk both overwhelming and potentially turning off its users (especially heavy users) while not reaching a significant group with buying potential—but who only use that channel minimally, if at all.

By incorporating the right channels into your media mix plan, brands can reach each channel’s heavy, medium, and light users—without bombarding one group with frequency and completely ignoring the others. The key is putting time into understanding and analyzing your media mix, and devising the most effective combination of channels to reach your target audience.

Media mix modeling

The best part about media mix analysis in the cookie-less world? Brands can still use this impactful strategy. In fact, companies have embraced the practice of planning and allocating media budgets across different channels throughout the modern history of media marketing.

Media mix analysis, a more general term, is often confused with another like-sounding term: media mix modeling. Media mix modeling (MMM) is a statistical technique that involves an in-depth analysis of how each of a brand’s marketing channels has impacted past results. Using sophisticated models, this method then predicts the future impact of media investments. Modeling requires huge volumes of past performance data, typically dating back two to three years, making it slower and less accessible for mid-market companies.

Though similar in name, media mix analysis is a broader term—part of a brand’s overall media planning strategy. This analysis could include media mix modeling, but it isn’t common. Because of the time and resources modeling requires, many businesses choose to analyze their media mix without this type of statistical modeling or masses of historical data—making the process simpler, faster, and more accessible.

While the eventual elimination of third-party cookies will make it more difficult to complete multi-touch attribution. This shift has already given rise to increased usage and more value from media mix analysis and media mix modeling. However, given the expense of generating algorithms and the painstaking time to capture and clean reams of data, media mix modeling is currently a method typically reserved for brands with the deepest pockets. Mid-market businesses find that other types of media mix analysis provide insights with a faster reaction time for them to compete on the public stage while honoring their budgets.

Making the most of your first-party data

As third-party data, via the use of cookies, becomes less attainable, brands still need a process for making decisions about how much money to put in each channel, improving cross-channel visibility. According to the CMO Survey’s report from February 2022, 74.8% of surveyed marketers expect their use of first-party data to increase over the next two years. Though third-party cookies will eventually be out of reach in 2024, some marketers will not abandon third-party data in the near future. Within the same survey, 30.5% expect their use of third-party data to increase over the same period.

Without cookies, businesses can use Universal IDs to connect various third-party data services. These cookie stand-ins patch together online activity by monitoring the websites where customers submit their email addresses. However, brands will still find it more challenging to act on this information and integrate third-party data with their first-party data.

Due to this, marketers are rushing to collect as much first-party data as they can, supporting forecasts of significant increases in the next few years. This is data the company itself collects—for example when a customer enters their personal information to make an online purchase on the company website.

Brands are already sitting on a rich source of first-party data through their websites and sales transactions. With this wealth of customer information, media mix analysis becomes an actionable strategy for creating a cross-channel advertising plan.

Marketers can generate informed inferences about their audience and measure ad success using their own first-party data and testing to optimize their media mix.

However, a problem for many businesses is that what they possess in enthusiasm is often not matched in experience. Unlocking the full power of a brand’s proprietary data is an expertise. For example, first-party insights can be enriched by appending data such as age, household income, and address to customer profiles, thereby painting a more robust picture of audiences. How do businesses access this information and receive the necessary insights? By partnering with agencies that offer these advanced services.

For example, at Amsive Digital, we can gather and append data faster, at a lower cost, and more securely than is possible for a mid-market business’s internal departments. Our extensive experience handling first-party data and our cadre of in-house PhD data scientists and statisticians means we can seamlessly contextualize this information and implement whatever new tools arise. Internally, we have accumulated large volumes of data from highly-vetted vendors, and protect client privacy by appending first-party data ourselves instead of sending it out. When dealing with personally identifiable information or data subject to rigorous HIPAA or financial regulations, we are equipped with robust security protocols to keep this information secure. Internal teams at small to mid-market businesses don’t have the access and ability needed for this intricate process.

Expand your ad experimentation and testing strategies

Within the changing measurement landscape, many marketers are feeling increased pressure to demonstrate the value of their marketing as brands seek to further quantify the results of their marketing efforts.

In the face of these challenges, media mix analysis helps marketers measure ad success, model audiences, and develop long-term marketing strategies.

Testing and experimentation are vital to developing the optimal media mix—helping brands adapt to a cookie-free world and remain agile as new marketing channels become popular. With millions of variables to test, brands testing their media mix must think strategically about what to test for and the metrics most relevant to their business. In a world without cookies, marketers can experiment with different channels, analyze the media mix holistically, and fine tune ad presence methodically.

In just one example, tools like MRI-Simmons, whose roots go back decades, can support brands in developing their testing strategies and are resurfacing in value. In addition to its extensive library of product usage, demographic, and psychographic data, MRI-Simmons’ cross-media information identifies the percentage of time a brand’s audience spends on the various media channels. With these insights, marketers can determine an initial allocation across different platforms and then test to see what happens when increases or decreases are applied to a particular channel. Based on the results, your media mix plan can be strategically calibrated and optimized. This is just one tool that can be harnessed to optimize your media mix.
Testing gives marketers the data to demonstrate marketing effectiveness. One of the most insightful metrics is incrementality, the number of customers who come to a brand that wouldn’t have otherwise.

Recent and upcoming changes in measurement don’t mean businesses are left to wonder—and wander the media landscape. Strategic media mix analysis, with the right inputs to establish the right outputs, enables marketers to provide evidence of conversions and justify media spending.

Insights and support within the shifting measurement landscape

Media mix analysis is a powerful technique that can illuminate audience segments and ad effectiveness. But for many businesses, performing this analysis in-house team isn’t realistic.

In times of disruption, brands need flexibility and a breadth of resources to efficiently allocate ads across channels and make the most of their media budgets. With the right tools and access to comprehensive expertise, brands can succeed at every phase in the media allocation process—from gathering first-party data to testing media mix scenarios. As we work towards a cookie-free world, media mix insights help brands make strategic decisions and optimize key aspects of their overall marketing strategy. We partner with legacy and rising national brands to identify incremental audience gains, eliminate waste in media planning, and ensure full-funnel media efforts contribute toward clear business goals.

The shifting media mix landscape doesn’t have to mean less impact for your brand. This is the second in a series of five articles diving deep into measurement today—unpacking what works and what’s next. So, stay tuned!

Until then, discover more about The Future of Measurement: What’s After Third-Party Cookies?

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