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Raising Media-Driven Revenue With Market Mix Modeling

Raising Media-Driven Revenue With Market Mix Modeling

AI AI, AI & Emerging Technology Consulting, Data maturity, Media, Media Analytics, Media Strategy & Planning, Performance Media 5 min read
Profile picture for user Michael Cross

Written by
Michael Cross
EVP, Measurement

Raising Media-Driven Revenue

In light of current economic conditions, which make it critical to do more with less budget, measurement of media effectiveness is becoming ever more important. In this context, incrementality—a term that has long been used in the world of consumer-packaged goods and promotions—is making its way onto the media scene, while innovations such as AI are used to accelerate the work.

The reason why we measure more and more is straightforward: so that we can forecast the performance of different strategic scenarios, and thereby help the brands we partner with optimize their media efforts. And just like any other discipline within advertising, the field of media continues to evolve, so let’s put a spotlight on what matters right now and will support your media measurement. 

Welcoming incrementality in the media world. 

First, let’s take a step back and look at what incrementality entails. Simply put, it refers to the lift in conversions or sales that can be attributed to a specific advertising campaign above those that would have occurred regardless—also known as the base. Incrementality has recently been adopted by us media folks, and the term has risen in importance because it’s a media measurement solution that isolates the incremental uplift. This matters because otherwise you can’t tell which media is driving growth and which is just harvesting conversions that you would have gotten anyway. As such, incrementality delivers a far more accurate view of how your media channels are driving conversions.

For example, traditional multi-touch attribution (MTA) often fails to separate the base from the uplift of the advertising campaign. This can lead to overstated results. Instead, in order to accurately measure incrementality, it's important to use MTA in conjunction with incremental techniques like market mix modeling (MMM). This way, you can better understand the true impact of advertising campaigns, move from ROAS to ROI, and as such have a more sensible conversation with your finance teams on the effectiveness of media.

How market mix modeling has got media measurement’s back. 

Market mix modeling—sometimes referred to as media mix modeling, but I prefer the former—is certainly not new to the scene, and this technique has been around in its commercial application to understand media uplifts for several decades now. However, the discipline has significantly improved, especially in the last few years.  

Contemporary MMM has come a long way. In the old days, annual updates would take months to bear results, while today you can get a pilot up and running within six weeks and use automation and machine learning to obtain monthly updates in just a matter of days. Besides, visualizations have also become much better, as today’s reporting dashboards offer analysts a plethora of ways to approach the data sets.

 

Monk Thoughts From the economy to seasonality, market mix modeling considers all drivers of sales, which makes the technique useful for CMOs as well as CFOs and a company’s board.
Portrait of Michael Cross

It's important to note that market mix models consider the whole market—including drivers like promotions to pricing, the recent pandemic, seasonality and more—and thus offer a holistic view. If you fail to take these other factors into account, you can’t get an accurate read on media and risk overstating its impact. As such, we’re seeing more and more brands partner with specialist MMM experts to help build the market mix models, or work with them to in-house this capability.

I have to point out that some players out there might say they execute “media mix modeling,” but are actually just building a simple regression with media variables or using multi-touch pathway techniques (which is not an incremental analysis). What’s so concerning about this is that they offer so-called MMM solutions at very cheap rates, which may sound appealing, but the damage of using these cannot be underestimated. Basing your decisions on a cheap but bad model could go wrong and cost you over 40% of your media-driven revenue—compared to an increase of roughly 30% if the technique is applied properly. You can make the call on what’s best for your brand.  

Leveraging AI to accelerate our analysis. 

Another very timely reason why I’m so excited about applying market mix modeling is the recent rise of artificial intelligence and the automation solutions that have stemmed from it—AI has been advancing fast in various areas, and it did not forget about MMM. 

At Media.Monks, we’re bullish about AI. That said, we also know that it’s important to be cautious and do our due diligence, especially as we see many AI providers claiming to build market mix models without having the right experience and tools to do so. When it comes to MMM, we believe that AI and automation solutions can be incredibly useful in speeding up the process, but of course there are also some instances that require manual labor. Let’s take a look.  

Raw data and processing. This can be automated using APIs or templates to stream data in, and then pre-ordained processes automate cleaning, saving lots of time. Beware of providers who take several months to initially onboard data pipes, as you really should be up and running in a matter of weeks.

Initial models. We use evolutionary algorithms to automate the initial model build, running thousands of models instantly in the cloud and scoring them, which enables us to arrive at a base model much faster and save weeks across MMM projects with multiple KPIs.

Final models. Note that this (still) requires manual intervention with a very experienced modeling team. We need to sense-check the models, triple-check the data, and use our extensive experience to spot any anomalies and alternative analysis to interrogate any controversial findings.

Sales effects and ROI calculations. These can be automated without the use of AI—this is just a process that can easily be repeated using code.

Automated reporting. Once all the numbers are calculated, it’s easy to automatically populate dashboards and media optimization tools. One thing that can’t be automated, however, is the answering of bespoke client questions around most effective second length, audience, and more. 

Engagement. Reporting ROIs and optimizations is one thing, but gaining an understanding of and trust in the models is another. Therefore, in the early stages of MMM engagements, it's imperative to have people who can explain the models and results to the wider team—not just marketing, but also finance, sales, the board, to name a few. My advice would be to circle back to this in later stages, once people understand and trust the model, and then you can move to more automated reports.

In short, automation can replace a lot of the heavy lifting of data and results processing and visualization, while AI can be used in the initial modeling stage. But what can’t be replaced is the sense-checking, interpretation, and experience of a good modeler to ensure the results are robust, realistic, understood and therefore usable.

Decreasing time, while increasing results. 

In the context of economically uncertain times, a time-saving—and thus cost-saving—solution like market mix modeling, especially when it’s powered by AI and automation, comes in very handy. Based on these models, media measurement typically enables brands to forecast different sales scenarios. In turn, having a robust forecast of performance is critical in justifying different strategic scenarios to the board, owners and investors of a company.

Incrementality is critical in the quest for accurate ROI, and MMM is a main way to get there. Though this technique has been around for decades, its pace of change and adoption rate is accelerating, which I’m sure will be further driven forward by AI. That said, in order for you to reap the many rewards of this tried and tested technique, it’s critical to work with a media partner who includes the whole mix of sales drivers and can take your models from sheer numbers to clear business actions.

 

Through market mix modeling, we help brands measure media effectiveness to forecast the performance of different strategies and optimize their media efforts. media strategy market research campaign performance campaign optimization data and analytics customer data Media AI & Emerging Technology Consulting Media Strategy & Planning Media Analytics Performance Media Data maturity AI

4 Focus Group Alternatives for More Varied Consumer Research

4 Focus Group Alternatives for More Varied Consumer Research

5 min read
Profile picture for user mediamonks

Written by
Monks

4 Focus Group Alternatives for More Varied Consumer Research

Focus groups may be one of the most well-known consumer research methods there is, but they’re not always the most effective in reaching your goals. Camera setups and a sterilized, corporate environment could make the experience feel very artificial for consumers, amounting to less than stellar (or super accurate) results. While focus groups have their opportunity to shine, some situations call for other options.

No matter which method you prefer in gathering user research, having multiple options is best: some methods are best for qualitative research while others are best for quantitative. Ideally, your research approach should include a method for both. “Research just for the sake of it isn’t good for the project,” says Fernanda Gonzalez, a Sr. UX Designer at MediaMonks who has done research on behalf of travel brands including Aeroméxico. “Use two methods that fit directly with your objective.” This allows for both broad, statistically valid insights as well as the deeper understanding required in maintaining a focus on the user experience.

Where Focus Groups Can Fall Short

Focus groups certainly have their uses: they’re versatile enough to use at different stages of the discovery or design process, and can aid in testing which creative approach resonates best with a handful of users. But their biggest limitation is that they often feel artificial. “The process is so well-known to consumers, and the setup can often alienate the subjects from those doing the research,” says Gonzalez—not something you want when seeking open, honest responses from your audience.

Monk Thoughts The more hygienic and clean the environment gets, the further you are from the consumer experience.

For UX Researcher Olivia Cabello, who has provided consumer insights to brands like ServiceNow, the potential for groupthink can also limit the value of insights derived from focus groups. “The loudest person in the group tends to influence others’ opinions,” she says. “In the past, I’ve prompted individuals to privately give written responses before the group discussion. When checking them afterward, you can see how their opinions changed throughout the conversation.” Therefore, this method can result in biased responses or ones less specific than anticipated.

Giving Research a Human Touch

“The more hygienic and clean the environment gets, the further you are from the consumer experience,” says Daniel Goodwin, a Digital Strategist at MediaMonks in Hilversum who has worked with brands like Heineken and McLaren. Highlighting this need, brands must introduce empathy through alternative approaches that bridge the gap between business and customer perspective. Each of the methodologies outlined below place their focus on validating the user experience on an individual level.

Monk Thoughts It’s important to say ‘I am here to listen to you, to understand your challenges.’

In this respect, Gonzalez stressed the importance of treating users as active participants rather than study subjects. “It’s a mistake to act as if we’re equally impacted by how a platform or service will affect us,” she says. “It’s more important to say ‘I am here to listen to you, to try to understand your challenges and to help build something useful.’ This frames them as part of the solution, not just someone being helped.’” Because consumer research relies on trust for open, honest responses, it’s important to treat subjects with sensitivity and care—a goal which leads to the more human approach we strive to take in research.

1. Good Things Come in Threes

Gonzalez’s favorite alternative to focus groups is the three-person method: simply gather three people of a similar demographic or persona, then interview them about their experience. While the loudest voice in a focus group often dominates others, these smaller groups comprising similar or like-minded subjects is more akin to a group of friends chatting about their experiences. The approach establishes a more collaborative and casual environment that makes it easy for subjects to share their perspective, making it ideal for validating creative concepts.

“When you have a group of people complementing one another in terms of persona or segment, you avoid the issue of a leader emerging, like in focus groups,” says Gonzalez. “Instead, group members build off one another’s ideas, which also makes it useful for gauging brand perception.” Gonzalez recommends working with two groups, resulting in insights from six similar subjects. This lets you gain a good scope of the user experience in just an hour or so.

2. Dive Deep with Individual Interviews

The deepest insights come from individual interviews, whether it be through questioning about their experience or observing the way they behave with a product or platform. Trade shows and industry conferences make great environments for gathering several viewpoints in-depth. For example, one client that Cabello worked with wanted to target customers via old-school mailers. But when Cabello, who’s based in New York, spoke directly to this audience at an industry trade show with her team, they found that the target audience felt annoyed by mailers. After taking this insight back to the client, the business shifted focus on other channels that would better engage their customers.

Cabello advises researchers to gather perspective from several roles, personas and stakeholders with this method, and to keep interviews short and sweet: “At some events there is limited time between talks, so strategically selecting about five questions is best for keeping the conversation focused.”

Monk Thoughts You’re not going to change people’s mentalities; supporting user behavior is key.

User testing, meanwhile, is key for understanding an audience’s thought process and to test whether a design process makes sense. “What I love most is when people do workarounds, they find a way to do it differently rather than how it’s designed. That’s the perfect moment to ask why they did this, leading to valuable results.”

When applying these insights, it’s important that the brand supports—not replace—user behaviors. “No matter what you build or create, you’re not going to change people’s mentalities,” says Cabello. For example, a cloud computing service Cabello worked with wanted to build a documentation portal to help users learn how to use the platform effectively. But Cabello found that users already met this need by sharing tips through community-building. The insight prompted the brand to pivot away from a documentation portal and toward a community platform that would empower users to instruct one another and bounce off ideas.

3. Gain Insights Over Time with Diary Studies

When you need to know how a user engages with a platform, service or need over time, diary studies make for an excellent tool. Whether they really shine is by placing those interactions in the context of daily life: what motivates them to use the product? What barriers exist? For Gonzalez, prompting users to regularly reflect and record engagements as they happen leads to fresh results.

“By being involved in the day-to-day rather than taking subjects outside of the experience for gathering research, diary studies can result in more information than sitting subjects down and asking them to remember tasks from their day,” says Gonzalez. The approach is ideal for seeking inspiration before zeroing in on a specific solution to validate.

Monk Thoughts Use two research methods that fit directly with your objective.

4. Poll Internal Stakeholders, Too

Consumer research shouldn’t just target consumers. In some cases, you’ll want to talk to other roles or stakeholders within the organization to understand how their interactions with customers can shape their experience with the brand. Goodwin has worked with clients in which their headquarters and roles working more directly with customers have become misaligned. In this situation, Goodwin recommends interviewing those with consumer-facing roles.

This practice not only aligns organizational goals, but also casts a wide net on user experiences. “Consumers have just one viewpoint: theirs,” says Goodwin. “But someone who interacts with them each day has a broad view of the different problems they run into.” By interviewing people with these roles, you can identify several opportunities to better support an audience’s need in little time.

Each of the methods outlined above aim to gather perspective on the customer experience without taking them out of the everyday. By engaging with research subjects out in the field and on their level, brands can achieve actionable insights without disrupting users or asking them to provide responses they think brands want to here. Instead, the approach should focus squarely on individual user need in the context of their daily lives.

Focus groups can certainly be useful for consumer research, but not in every case. In fact, effective market research requires multiple methodologies--here are some of our Monks' favorites. 4 Focus Group Alternatives for More Varied Consumer Research The most effective consumer research includes multiple methodologies, not just one.
consumer research market research brand strategy focus groups research methodologies

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