Marketing mix modeling is the new buzz word that has taken the industry by storm. The concept might have caught the attention of the management recently, however, in reality, it is an age-old concept. MMM’s popularity is on the rise as marketers realize its value proposition that helps companies to forecast the marketing return on investment (MROI). Marketing mix modeling is a statistical analysis that helps in evaluating past marketing activities and forecasting its impact on actual sales. MMM helps in bridging the disconnect between marketing spend and the organizations bottom line.
Marketing mix modeling enables marketers to gain an in-depth understanding of the marketing variables and their impact on sales and conversion. It also empowers the management to make strategic business decisions and identify the opportunity costs thereby optimize strategies from a long-term perspective. Theoretically, there are two marketing mix modeling strategies i.e. longitudinal and cross-sectional, that are pursued by organizations. Longitudinal analysis means evaluating the sales and profits over a fixed time period and comparing it with the marketing spend for that period. While cross-sectional analysis entails allocating different levels of funds to each territory or region and then comparing the spend with the outcome. These strategies are individually strong and highly efficient but often a combination of the above-mentioned strategies is used to yield the best results.
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Thumb Rules of Marketing Mix Modeling
Marketing mix modeling may include a wide range of marketing variables, however, the organizations must understand that it does not follow a ‘one size fits all’ approach. Every brand is unique and so are the variables that impact that particular brand. This is just one of the few pointers or thumb rules that marketers must keep in mind while identifying the right marketing mix modeling solution. The other heuristic approaches or thumb rules are as follows,
- Setting realistic levels or baseline so as to determine the marketing activities that meet this minimum requirement to be an important marketing variable that has a positive impact on the marketing spend. In marketing mix modeling, if the baseline or threshold level is set too high, a certain marketing activity might never be able to meet it and would never come up as an important variable in the analysis.
- Marketers should be aware that some of the marketing activities might have an immediate effect while others might demonstrate the effect in future. Therefore, they should not hasten in making decisions.
- When integrating marketing mix modeling in the organizations performance measurement system, marketers should start small and include few variables or test on selective marketing campaigns instead of cluttering the model with unnecessary activities and complicate things.
- The marketing mix modeling is not a sure shot way to success, it takes hard work, rigorous trial and error approach and time to identify the marketing variables and optimize the marketing mix. It is a very time-consuming process and requires patience on the marketers’ part.
- Involvement and participation of every person in the organization, especially the top management to achieve desired results. Organization-wide participation ensures the success of marketing mix modeling as it leverages the knowledge and industry-level understanding from every employee.
- Lastly, organizations must understand that the underlying factor for the success of marketing mix modeling depends entirely on accurate and reliable data. If the data used is more cluttered, then the forecast or outcome will not be accurate.
These are the few thumb rules that organizations must imbibe in order to leverage the benefits of marketing mix modeling and drive profitability. At Quantzig, we offer a wide range of marketing analytics solutions including marketing mix modeling that enables the organization in gaining granular actionable insights and thereby driving profitability and cost savings opportunities.