MMM VS MTA
Modelling the future sales using statistical analysis techniques is the basis for sales planning to maximise profits. Timely and qualitative estimation combined with econometric modelling techniques can improve sales performance by up to 10% and more, depending on the market and competitor activity.
The most popular techniques are Multi-Touch Attribution (MTA) and Marketing Mix Modelling (MMM).
Today, 72% of industry respondents use MMM or MTA to measure the effectiveness of their marketing efforts.
The number of Fortune 500 companies as like P&G, AT&T, Kraft, Coca-Cola and Pepsi, use MMM. Lately, the technology has been spreading rapidly among pharma and FMCG compa-nies because of the availability of data in these industries and the high level of competition.
Marketing mix modelingis statistical analysis of all known factors (communication and sales channels, prices, seasonality, weather, etc.) to estimate the impact of various marketing tactics on sales and then forecast the impact of future sets of tactics.
«Multi-Touch attribution» or МТА, is based on the technology of measuring the multiple customer touchpoints that lead to a purchase. The major advantage of the method is by tracking the entire customer journey, as you need to understand how the customer experience is mapped online and offline at all micro-levels. It is therefore important to assess their impact.
The most popular method today, especially in markets with intense competition, is the combined method, which unifies MMM and MTA analysis. That’s because companies work constantly to improve the effectiveness of ad campaigns, across different channels of communication, with an abundance of data and factors affecting sales simultaneously at certain historical intervals. Therefore, measuring only is not enough.
- To estimate the impact of TV and pricing policies on demand within a single ad campaign, based on the history of activity in different channels, prices and sales
- To identify insights and build the most optimal sales model.
Types of Data Used: TV activity in the period (TRP, target rating point), price trends, sales volumes, number of sales points, measurements of main competitors' activity.
Conclusion 1: If marketing support is reduced, the product sales decline critically (over 50%). A continuous presence on TV is therefore recommended. It shows a high level of competition in the market.
Conclusion 2: Correlation analysis shows the volume of marketing activity has a statistical relationship with product sales. Distribution has almost no impact upon it.
The Research Purpose: to estimate the impact of TV, Digital, Radio and OOH separately by week and month.
Types of Data Used: TV activity in the period (TRP, target rating point), Digital (the number of ad impressions), Radio (the number of airings), OOH (projected investment volumes) and total online market sales.
Data used: base price $ 100, correlation from 0 to 1. The basis of this study is a model for forecasting product sales.
The chart is interactive, so you can set the correlation value of the price and the new price, you can assess the impact of price on sales.
