Predictive Analytics

Pecan AI adds MMM to automated predictive analytics sol suite

Pecan’s marketing mix modeling uses state-of-the-art machine learning to solve marketers’ measurement and planning needs
Pecan AI

Pecan AI, the leader in AI-based predictive analytics for BI analysts and business teams, today announced the addition of marketing mix modeling (MMM) to its suite of low-code, automated predictive analytics solutions. As a result, marketers who must demonstrate and improve marketing results can now easily use this machine learning-driven innovation to understand and proactively plan for maximum marketing impact.

Pecan will share how AI and machine learning, especially marketing mix modeling, can benefit marketers at a live virtual event featuring Neil Hoyne, Google’s Chief Strategist for Data and Measurement, at 2 p.m. ET on March 1, 2023.

Pecan’s Marketing Mix Modeling Helps Marketers Measure and Boost ROI
Marketing mix modeling offers an excellent way to understand marketing ROI across all channels. However, MMM has traditionally been expensive, inflexible, and infrequently updated. Pecan’s approach to MMM takes the company’s highly accessible, automated approach to predictive analytics and makes this method available to all marketing teams.

It can be impossible for marketers using standard attribution methods to understand the real return on investment from marketing efforts, especially offline channels. Even digital channels now offer less detailed information due to changing privacy policies and data limitations.

Even without specialized data science resources, marketers can now add Pecan’s MMM to their planning and measurement strategies. MMM provides invaluable insights into channel performance, even channels otherwise difficult to measure. Models allow marketers to simulate budget allocation options to identify those that maximize return on ad spend. Pecan integrates state-of-the-art machine learning and automation into classical MMM, making it possible to have models ready for use in 1 to 3 weeks.

Pecan’s innovative approach makes it easy to connect to data, iterate on models, refresh data analysis, and simulate “what-if” scenarios using customized constraints. Marketing teams can view the ROI of every channel with granular detail in Pecan’s easy-to-interpret dashboards. In addition, simulation tools allow for rapid experimentation and marketing agility in today’s fast-changing environment.

“In a very short time, Pecan’s MMM solution granted our team a new way of analyzing our marketing spend and its revenue contribution, while exposing opportunities for budget allocation and channel ROI optimization,” said Evyatar Livny, senior director of advertising technology at global mobile game publisher SciPlay. “We can now leverage both attribution data and MMM contribution to have a more holistic understanding of our marketing investments.”

“We’ve seen marketing mix modeling have tremendous benefits for companies struggling to understand how well their marketing spend is working for them,” said Zohar Bronfman, co-founder and CEO of Pecan AI. “MMM has historically taken in-depth expertise and a long time to build and deploy, making it available only to the largest companies with specialized data science teams. Pecan is making this sophisticated approach much more accessible and agile, helping our customers gain the most impact from every marketing dollar they spend.”

Live Marketing + AI Event with Google Expert and Author Neil Hoyne
Neil Hoyne, Google’s Chief Strategist for Data and Measurement and bestselling author of Converted: The Data-Driven Way to Win Customers’ Hearts, will join Yehonathan Barnea, Pecan’s Vice President for Customer Success, for a live virtual discussion of how AI can help resolve today’s marketing challenges.

In addition to discussing MMM’s potential, Hoyne and Barnea will address how marketers can integrate AI into their strategies, and why predictive approaches ensure the most efficient uses of marketing budgets.

The event will live-stream at 2 p.m. ET on Wednesday, March 1, 2023. Registration is available now:

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