Can media mix modeling help boost word-of-mouth marketing efforts?
As a form of referral marketing, word-of-mouth (WOM) marketing can provide powerful results. This may be true for providers seeking referrals from other providers — or from satisfied patients who send family and friends their way.
Though WOM can be an effective marketing tool, in some instances WOM campaigns are treated as a bit of an afterthought funded by marketing budget leftovers. Perhaps that’s understandable, given the increasing pressure marketing departments face to justify how their dollars are spent — as well as the perceived difficulty of objectively measuring WOM results.
But what if WOM could be given the respect it deserves? What if it could be viewed as an integral part of the marketing mix? For some companies, that may be increasingly the case.
In a post for the American Marketing Association (AMA), one marketing expert underscores the effectiveness of WOM and says that many companies are “no longer content to simply let WOM happen organically” and are planning for it more strategically through the use of referral programs and online recommendations, among other tactics.
He also underscores the importance of measuring the results of such efforts.
“…as more and more companies are integrating WOM tools into their marketing plans, it’s important to consider whether the effectiveness of the tools depends on other marketing efforts,” he writes. “In practice, companies are often at a loss as to why their spending on WOM programs produces widely divergent results, and failure to consider how WOM interacts with other marketing mix spending may be an important part of the explanation.”
In this context, perhaps media mix modeling can help.
What is media mix modeling?
In a post for Singular, writer Haley Smith refers to media mix modeling (MMM) as “super-hot” due to the “massive focus” on privacy the marketing industry is facing.
“Marketing mix modeling, also known as media mix modeling (MMM), is a powerful but complicated technique used to optimize marketing activities on a broad scale,” Smith writes. “By analyzing historical data, MMM helps determine the impact of various marketing tactics on business outcomes. This statistical analysis provides valuable insights into return on investment (ROI) and the effectiveness of different marketing channels. With MMM, marketers can identify the contribution of major marketing channels and drivers, such as Facebook ads or IP partnerships, and make data-driven decisions for their marketing strategy.”
Noting that historically, MMM has been used by consumer goods companies and digital marketing teams to boost brand awareness and sales, she says it’s also now also available for mobile marketing, app marketing, and user acquisition campaigns.
“By measuring the contribution of different media channels such as in-app, CTV, traditional TV, social media, and influencer ads, MMM helps marketing teams allocate budgets to the most impactful tactics,” Smith writes. “It also analyzes the reach and frequency of marketing messages, providing valuable insights into optimizing brand awareness and customer engagement.”
In her in-depth explanation of MMM, Smith also distinguishes the difference between MMM and multi-touch attribution (MTA).
“MMM focuses on understanding the impact of different marketing channels on overall sales and return on investment,” she says. “It analyzes historical data and calculates the contribution of each channel, such as television, print, digital marketing, and social media, in driving sales and brand awareness. MTA, on the other hand, tracks individual customer touchpoints throughout their journey, allowing marketers to attribute credit to specific interactions and optimize future advertising efforts.”
Although the models differ, she says they can complement each other — and when leveraged together — can enable a more holistic view of the effectiveness of marketing efforts.
“By contrasting the top-down statistical analysis of MMM with the granular bottom-up attribution analysis of MTA, marketers can gain comprehensive insights into the effectiveness of their marketing efforts,” Smith writes. “This relationship between MMM and MTA allows marketing teams to understand the impact of various channels on consumer behavior, optimize their media mix, and make data-driven decisions to maximize return on investment.”
The growing importance of media mix modeling
Although MTA has been a staple of measuring marketing effectiveness, Smith notes that it’s getting increasingly challenging to make the most of this model in mobile marketing due to growing privacy restrictions.
“Thanks to privacy regulations and technologies, it’s generally no longer possible to track each individual touchpoint, ad view, or conversion,” Smith writes. “That’s especially true on iOS right now, and increasingly will be true on Android from 2024 and on to 2025, as Google deprecates the Google Ad ID, or GAID.”
In its recently released Outlook for Advertising, Marketing and Data 2024, the Winterberry Group underscores the growing importance of media mix modeling, also highlighting the impact of increasing privacy restrictions.
According to the press release, “The predictions from the strategic consultancy also included a variety of business drivers and trends, from macroeconomic influences such as interest rates and unemployment, to advertising-specific concerns, among them the loss of third-party cookies as reliable household and individual identifiers for advertising, and their attempted replacement by a variety of technologies and techniques.”
Related trends identified in the research include:
- The data layer: “Data is no longer (just) a channel play – data for direct mail, data for email, data for interest-based advertising online, data for addressable and connected television – but rather an enterprise-wide intelligence infrastructure that supports media mix modeling, omnichannel marketing, triggered marketing, targeting, attribution and other ad-focused measurements. Still, legacy customer relationship management systems mean data silos linger, and applied intelligence is hampered.”
- Name that identifier: “Agencies and brands are reassessing their media spend, as attribution becomes harder with the fading third-party cookie. A higher reliance on media mix modeling – and watching for incremental changes in sales, leads and traffic – and a renewed focus on attention metrics collectively should ensue.”
Jason McNellis, a senior director analyst in the Gartner Marketing Insights, concurs with the growing importance of MMM.
McNellis says the goal of this model is to “measure the impact of advertising and promotions across channels while controlling for external factors outside of a brand’s control, such as inflation or consumer sentiment.”
He lists three ways outputs from MMM are used:
- As a scorekeeper — “to show the overall incremental impact marketing investments are having on the overall business.”
- As a forecaster — “to predict the outcome that raising or lowering marketing budgets will have on marketing’s contribution to the overall budget.”
- As a coach — “to suggest shifts to current marketing investments that improve performance.”
“With increasing pressure to prove the value of marketing, smart CMOs are turning to marketing mix modeling, or MMM, to improve media performance and quantify their impact,” McNellis writes.
At Advance Healthcare Marketing, we specialize in partnering with healthcare organizations to craft bespoke marketing plans tailored to their unique needs and objectives. Our dedicated team is committed to developing compelling creative solutions and messaging that resonates with your target audience. Moreover, our proven track record underscores our ability to deliver tangible, measurable results, ensuring that your marketing endeavors yield the desired outcomes. Contact us today to get us started on your personalized strategy.
