Market Mix Modeling is Not Just a Black Box: Decoding the Myth with Quantzig’s Marketing Analytics Services Leader Aviral Sinha
Aviral Sinha, Manager (Business Development Operations) and an Analytics Services Leader at Quantzig has over 5 years of cumulative experience across multiple types of analytics engagements including advanced customer and marketing analytics, price optimization, sales analytics and BI solutions. He has played an instrumental role in providing actionable analytics-based insights for clients across multiple industries [...]
Aviral Sinha, Manager (Business Development Operations) and an Analytics Services Leader at Quantzig has over 5 years of cumulative experience across multiple types of analytics engagements including advanced customer and marketing analytics, price optimization, sales analytics and BI solutions. He has played an instrumental role in providing actionable analytics-based insights for clients across multiple industries including Healthcare and Life Sciences, Retail, CPG, Food and Beverages, and Telecom.
With the introduction of digital media into the marketing landscape, gaining proper insights into campaign effectiveness and properly attributing the performances of each channel has become increasingly difficult. The growing demand in the emerging economies and saturation in developed countries has created a rapid shift in the market dynamics across the globe. Consequently, enterprises face immense difficulty in devising market expansion strategies to gain and retain market shares, optimizing its marketing investment, and identify revenue driving opportunities. Market mix modeling (MMM) helps businesses evaluate their past marketing activities and forecast the marketing return on investment (MROI) based on data driven insights. Also, market mix modeling enables organizations to bridge the gap between the marketing spend and the bottom line.
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Is market mix modeling a black box?
Aviral: Absolutely not! Since marketing mix modeling involves advanced statistical analysis of vast volumes of data, it can appear to be obscure process to non-practitioners. Some have accused marketing mix of being a black box, with inputs going in and results coming out with no transparency to the process. Without a clear understanding, how can one know if the model results are accurate? Though it is certainly a complex methodology, marketing mix is not a black box.
Rather market mix modeling is a proven analytic approach that incorporates science with business acumen to drive actionable insights. Today businesses are leveraging marketing mix modeling channelize spending to media with better ROI and optimize the media mix based on consumption patterns. Furthermore, market mix modeling solutions can help in improving customer targeting based on demographics, including indicator variables to control for seasonality and funnel effects. As a result, companies leveraging market mix modeling can develop a multi-channel strategy to execute and measure campaign across digital channels and improve conversions.
What are the current challenges in market mix modeling?
Aviral: In my opinion, evolving markets are leading to more competition, more products, more options and this has created a challenging marketing environment. Therefore, identifying and collecting data that is completely different from internal and external sources such as marketing, sales, advertising agencies etc. has become very difficult for businesses. Also, companies are facing difficulties in dealing with selection biases in ad targeting based on interest, seasonality in demand, and funnel effects that creates challenges in specifying market mix models. Another major challenge is the emergence of a complete digital landscape which has created a newly empowered customers with diverse personal interests.
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Is market mix modeling biased to promotions and fails to capture the true effects of advertising?
Aviral: Certainly not! Marketing mix is not biased toward promotions. However, some businesses, especially CPG, tend to be drawn into a promotion-heavy strategy. When promotions are applied over the long term, it is known as deep discounting. While these discounts may help the business and retailer in the short term, neither party flourishes in the end. A deep-discounting strategy conditions consumer to buy on deal, leading to a devaluation of the brand and the category and eroding margins for both the manufacturer and retailer.
Marketing mix is certainly not the cause of this situation, but it can be a part of the solution. Market mix modeling approach helps in identifying opportunities for the manufacturer and retailer. High-return promotional events can be prioritized in a way that does not erode margins in the longer term.
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What is it that companies should do to be future ready?
Aviral: To start with, some offline channels like TV are great for driving new customers to your online shop when considering the effects of investments in such channels it makes sense to try to measure the effects of these advertising on website traffic. What I am trying to say here is that the combination of both traditional and digital media options for advertising had led marketers across the globe to explore creative ways of attributing sales across channels. Organizations of the future will drive marketing excellence by connecting the online and offline journey with the help of the marketing analytics. Unique identifiers such as loyalty cards, email receipts, coupons and phone numbers can help in identifying and tracking a customer offline. Tracking an offline sale to the unique ID of a customer using data from their browsing history and location can help in attributing the sales to online touchpoints. By leveraging marketing analytics solutions, organizations will close the loop by integrating customer segmentation and market mix optimization and allocation under the same umbrella to develop a holistic marketing strategy.
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