Monday, September 30, 2024
HomeUncategorizedPublicis Media launches marketing mix modeling tool Markriti

Publicis Media launches marketing mix modeling tool Markriti

Publicis Media India introduces Markriti, a achine-learning based Marketing Mix Modeling (MMM) tool. Powered by Meta Open Source and supported by an interactive UI, Markriti aims to deliver efficient, cost-effective, and cutting-edge MMM solutions to brand managers and CMOs across industries, further enhancing Publicis Media India’s AI footprint and strengthening its overall client servicing capabilities.

Understanding that we live in a competitive world, brands are actively adopting a data-driven approach. They are seeking tools and metrics that can help measure return on investment (ROI), which allows them to optimize campaigns for better results. While there are many campaign measurement tools available in India, Markriti comes in as an integrated MMM solution that enables marketers to measure their ROI across various marketing channels, even before the launch of a campaign. An intervention by Publicis Media India, Markriti aims to help marketers achieve their targets and optimize budgets.

While Markriti inherits its open source from Robyn, it is a step ahead by providing a top-down UI that allows for a low-code and hassle-free MMM workflow. It empowers strategists and analysts in post-modeling to not only engage in MMM studies but also access insightful data in under an hour. With the time saved in running the model, the Data Scientist can now focus on fine-tuning the model and insights. With capabilities across investment, strategy analytics, data, performance marketing, and content, Markriti has truly completed Publicis Media India’s suite, further reinforcing the group’s ‘Power of One’ business model.

Rajiv Gopinath, Chief Solutions Officer, Publicis Media India said, “In the dynamic world of marketing, which is highly influenced by consumer behavior, our clients have always been posed with the challenge of finding a way to measure the impact generated through their efforts accurately. With Markriti, we aim to empower marketers by supporting them from inception and ideation to execution and measuring impact. We also empower Data Scientists with a cloud computing solution and a UI that gives them flexibility in hyperparameter tuning. We are sure that Markriti will enhance marketing strategy building across industries and evolve as the partner of choice for all MMM solutions.”

Dabur, having worked with Publicis Media India for close to a decade, recently deployed Markriti for the Karnataka market to address issues around brand growth and return on investment through their marketing efforts. The problem at hand was to create a comprehensive MMM that could quantify the ROI, determine the optimal marketing mix, and provide strategic insights for improved marketing efficiency. Markriti, with its transformative approach and user-friendly nature, efficiently analysed their past marketing campaigns and helped Dabur optimize the existing budget, alongside a significant boost in the overall return on ad spend.

Rajiv Dubey, Vice President, Head of Media & Brand Activation at Dabur India said, “Publicis Media India has been our analytics partner since 2015. Every year, they bring something new to the table regarding analytics. The Markriti innovation is a great initiative and it’s great to have a partner thinking about driving our business goals. It was used for the Karnataka MMM this year.”

Additionally, Augustus Daniel, Head of Marketing, Oral Care, Dabur India, having seen the usage of Markriti in his category, shared, “We’ve been using Publicis Media India for MMM services for quite some time now, and this year they’ve introduced a new modern approach to MMM through their tool ‘Markriti’, through which the results for the Karnataka market were developed. Markriti uses the powerful Meta Open Source library Robyn and represents some of the best the industry offers in the field. We look forward to more innovations from Publicis Media India in the analytics area.”

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