April 24th, 2023, YouGov
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‘Half the money, I spend on advertising is wasted; the trouble is I don’t know which half’ – John Wanamaker
Marketing mix modeling (MMM) answers the biggest question in marketing budgets, by suggesting ways to successfully spend in the most efficient and cost-effective ways to achieve your sales objective.
Data is the foundation of marketing mix modeling (or MMM), and the quality of the data used can have a significant impact on the accuracy and effectiveness of the modeling. To achieve the best results, as well as using sales and market data, marketing mix modeling requires modeling of high-quality research data. This article highlights seven key ways that research data improves the accuracy and effectiveness of marketing mix modeling.
Brand awareness and brand perception are essential components of marketing mix modeling, as they can significantly impact consumer behavior and purchasing decisions. Data from brand awareness and perception research is used in MMM to measure the impact of brand awareness on sales and profits.
By analyzing sales data and correlating it with brand awareness and perception data, models can identify the impact of these measures on consumer behavior and purchasing decisions. This information can be used to optimize the marketing mix by allocating resources to the most effective marketing activities, such as advertising and promotions, that are likely to increase brand awareness and perception and drive sales.
Market research data provides insights into the competitive landscape, including competitor pricing, product offerings, and marketing strategies. Tracking the brand health of competitors across key metrics is as essential as tracking your own brand – benchmarking within your industry or sector and identifying their growth highlights the state of the market.
By analyzing this data, businesses can identify the factors that are driving competition and use this information to develop a sales forecast that takes into account the impact of competition on sales.
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Research data collected from customer surveys can help identify the channels customers use to learn about a brand's products or services, as well as help identify which channels are most effective in driving sales.
By analyzing this data, businesses can determine which marketing channels are most effective in reaching their target audience and the media channels to consider investing in for greatest consumption, as reported by the very consumers they’re trying to reach.
Brand awareness data can be used to evaluate the effectiveness of marketing activities in building visibility. By analyzing the impact of various marketing activities on brand awareness and the subsequent impact on sales and profits, MMM can identify the most effective marketing strategies for increasing brand awareness. This information can be used to optimize the marketing mix and ensure that resources are allocated to the most effective marketing activities to boost a brand.
Research data can also be used to measure the effectiveness of marketing campaigns. Businesses can determine the impact of each marketing channel on sales and other key performance indicators by tracking customer behavior and analyzing data from various sources. This information can then be used to optimize marketing campaigns with data-informed strategies, spending in the places that yield the greatest impact and ROI, improving overall marketing effectiveness.
Market research data plays a crucial role in forecasting sales for new products. By conducting market research on consumer preferences, attitudes, and behavior, businesses can identify opportunities for new product development and forecast sales based on these insights.
This information can then be used to optimize the marketing mix and develop a strategy that maximizes sales and profitability.
Research data can be used to build predictive models that forecast sales and revenue based on different scenarios. Predictive analytics involves using statistical algorithms and machine learning techniques to analyze data and make predictions about future outcomes.
This information can then be used to develop a marketing strategy that maximizes revenue and profitability.
YouGov BrandIndex, our daily global brand tracker, measures brand changes continuously and highly sensitively, with new information released every single day. If this data is introduced into marketing mix modeling, it will strengthen the model and make it much more powerful by allowing you to understand where best to spend your budgets, to improve perceptions of your brand, to increase sales.
Get a snapshot of YouGov’s living data from our flagship brand health tracker YouGov BrandIndex, to strengthen the explanatory and predictive power of your marketing measurement. Increase the quality of insights generated from MMM by accounting for longer-term changes in brand equity and health. Integrate consistent, flexible brand health tracking data into your model to explore the ROI from improved brand equity and measure the impact of shifts in consumer sentiment.
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YouGov’s brand tracking data is well suited for modeling due to its coverage, consistency & history:
If you have the capacity to run marketing mix models yourself, or have a preferred partner for doing this, YouGov can provide with the relevant snapshots of our flagship BrandIndex data to work with.
If you don’t have the capacity to run models yourself, we have partnered with ScanMarQED a leading practitioner in this area. ScanMarQED can do simple models to understand the impact of media spend allocations on just BrandIndex metrics (we call this Brand Performance Modeling) or very complex models that take into account media spend, BrandIndex metrics, sales and perhaps non-media factors such as distribution, price promotions and seasonality.