Marketers are moving faster and data needs to keep up. The most successful brands rely on constant feedback to optimize their tactics. They get ahead of the competition by shifting budget from underperforming or over-saturated tactics to higher performing campaigns to drive growth.
Large scale reviews of a company's investments and outcomes should be no different. Marketing mix modeling is a tool many CMOs use to get strategic insight into marketing performance. But historically, speed and data quality have been at odds, and marketers have made tradeoffs to get one or the other.
Today, Nielsen’s focus on innovative modeling techniques and automation offers marketers the best of both worlds. Our clients are already seeing results (more on this later). First, let’s set the stage with some definitions.
What is Marketing Mix Modeling?
Marketing mix modeling is a strategic marketing measurement approach. It involves the application of regression and other statistical approaches to estimate the impact of marketing elements on incremental sales. Summary-level historical data is used to fit the model, which then can be used for prediction of future sales.
These models assess the effectiveness of spending by channel over and above a baseline of sales that would have occurred without any marketing efforts in an effort to reallocate budgets across channels and subchannels. The data is often provided in multiple formats. This requires either vendors to manually scrub and normalize the data or marketers to provide the data in a common format.
This approach also allows for the modeling of exogenous data – essentially understanding the impact of factors that fall outside of an advertiser’s control such as weather, economic conditions and strategies taken by competitors.
The benefit of this approach is that it can be used across both online and offline channels to incorporate an advertiser’s entire marketing mix. The downside of traditional marketing mix modeling is the speed.
Modeling occurs on a less frequent basis, typically quarterly, and insights can take 16 to 24 weeks from data collection. Results are of limited value when the actions they’re based on are months old. This dramatically impacts an advertiser’s ability to get early insight into performance and adjust plans quickly.
But Nielsen is reimagining mix modeling for the modern marketer, integrating automation to drive faster time to insights. Now you don't have to sacrifice quality for speed.
Nielsen’s Marketing Mix Modeling Solution Delivers Timely Results
When Alcon, the world’s largest eye care device company, developed an innovative solution for dry eyes, it needed answers to critical questions to ensure the product’s success. Nielsen’s marketing mix modeling solution delivered timely, actionable insights Alcon needed to assess the impact of its 2018 360-degree marketing campaign and determine the optimal level of investment for 2019.
With Nielsen’s strategic insights, Alcon grew Systane’s share of equity sales by 8.7%, driven in large part through the launch of Systane Complete. The team has since received funding for continued media support, and is basing its marketing investment decisions on recommendations from the analysis.
In order to deliver the results in time for the planning deadline, Nielsen worked with Alcon’s Systane brand team to prioritize the business questions and factors that were most critical to understand, including competitive actions, retail distribution, price changes, promotions, TV, online video, print, online display, social media and coupons.
Answers to Key Business Questions
Nielsen was able to leverage proprietary media and sales data, as well as its unmatched access to data through partnerships, to speed up the data collection process. Once collected, the data inputs were integrated into a robust regression model to tease out the incremental impact from each factor.
The analysis revealed four insights and optimization opportunities that the Alcon team could use to get a head start on its 2019 planning:
1. The marketing efficiency of each channel.
The analysis enabled the Alcon team to compare the efficiency of different marketing channels and tactics, including social media, digital display ads, print, online video and addressable TV, against one another. For instance, the analysis revealed that addressable TV was highly effective at reaching the target market, drove a sizable portion of incremental sales during the Systane Complete launch, and had a strong “halo” effect on the entire Systane brand portfolio. With an objective, big-picture view of the ROI of each channel, the team was able to make smarter and more effective budget allocation decisions.
2. The importance of granularity.
In addition to understanding individual channel performance, the Alcon team was able to layer in additional analysis to drill down to evaluate the performance of different dimensions within each marketing channel. For instance, the team was able to see specific results for each of its addressable TV vendors, and remix its spending among national and regional providers to help improve sales lift and ROI.
3. How performance fluctuates over time.
Since this was Alcon’s second marketing mix modeling analysis with Nielsen, the team was able to compare and contrast performance over time. By understanding and isolating these fluctuations within and across channels, the team was able to plan its go-forward marketing strategy with confidence.
4. The effectiveness of the overall mix.
Perhaps most importantly, the analysis confirmed that Alcon’s media mix was solid, its creative was resonating with its audience, and that the team had the right plan in place. With sales volume and brand equity for Systane Complete on the rise, the team could turn its focus to refining the plan to optimize results going forward.
Measuring the Impact of Marketing on Sales
Marketers in every vertical have adopted a marketing mix modeling approach to measurement because it serves their businesses’ operating cadence and supports strategic planning.
Nielsen’s Marketing Mix Modeling solution provides an understanding of what’s driving sales including online, offline and the trends and competition that can affect demand for your products—without compromising speed or data quality.
To learn how you can be a better marketer in the digital era, download our ebook: Untangling Attribution's Web of Confusion: A Primer for Marketers
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