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Navigating the Marketing Complexities With 2.0 Marketing Mix Modeling

Published on March 4, 2024
Published by Mark10
Viewed by 3 people
#378302
Services
Free

Description of item

Introduction
As we transition to a digital era, the chief marketing officers (CMOs) need to move away from the traditional method of tracking (which relies on clicks) and choose a better marketing model that fits well in this era. The solution to this problem is the implementation of MMM (Marketing or Media Mix Modeling) or rather, what we will call -MMM 2.0.

Also Read - AI Strategies for C-Suite Leaders and Marketers
The Evolution of Marketing Mix Modeling (MMM)
Marketing mix modeling isn’t a buzzword. It has been around in the marketing world for decades as a powerful tool for measuring the effectiveness of marketing campaigns. Back in the 1980s, MMM was first deployed by Procter & Gamble (P&G) into their analytics system to measure their marketing forecasts, conversion rates, and incremental experiences.
The Present Scenario of 2.0 Marketing Mix Modeling
After a leap of thirty decades, the current scenario of 2.0 marketing mix modeling is built on the foundation of machine learning, artificial intelligence, predictive analytics, and a mixture of correct business knowledge and external factors in the business world.
CMOs can simplify their marketing by applying “smart constraints” and assumptions that will enable them to find the real application areas of implementing MMM 2.0 in this digital era.

The Future of 2.0 Marketing Mix Modeling
When compared with the traditional MMM, the 2.0 MMM has unlocked doors for new technologies and it eases the manual workload of marketers by automating the data collection, cleansing, and preparation process. It is believed by marketing stalwarts that MMM will continue to evolve and influence the next generation of MMM. Let’s check out some of the MMM trends that we can expect in the coming years

Increased Usage of AI and ML
Multinational companies and large organizations are advancing their models by using LLMs (Large Language Models), such as Google Gemini and ChatGpt. As we expect these models to mature, they will play a prominent role in improving actionability and accuracy in MMM results.
For more such updates, follow us on Google News Martech News

Location

Country
United States
Region
CA
City
Lake Los Angeles
Address
Capital Tower, 168 Robinson Road, Singapore

Other information

Contact Email: martcehcubepal@gmail.com
Website: https://www.martechcube.com/

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