Discover the optimal mix of channels based on your target revenue and budget levels
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Marginal ROAS, CLV, and CAC curve modelling
Brand lift and cross-channel incrementality studies
Media Mix Modelling and allocation recommendations
Channel-level predicted outcomes by spend amounts
Marketing mix modeling assists marketers in optimizing future spends and maximizing effectiveness
Towards Data Science
Ridhima Kumar
Marketing mix modelling uses aggregate data, not user-level data, and explores the impact of a wider range of channels and factors, including non-digital media
Gartner
Chris Pemberton
Frequently Asked Questions
What is Marketing Mix Modelling? How can it help?
Marketing Mix Modelling (MMM), also known as Media Mix Modelling, is a statistical technique that enables teams to quantify the impact of various marketing inputs on Revenue or Return on Ad Spend (ROAS).
The goal of MMM is to explain how much each marketing channel contributes to revenue and how much to spend on each marketing channel. It is the foundation for effectively optimizing a paid media budget across different channels.
OutPoint's models apply MMM principles and rely on machine learning and causal inference techniques. Our models are optimized to simulate new and current channels to empower your team to make more reliable spend decisions.
How do we decide how much to spend on a given channel?
OutPoint's marginal return curve analysis allows you to see how much additional budget you should invest into a channel (or how much you should dial back!)
How should we analyze and measure offline channels?
OutPoint's advanced growth modelling imputes value to each of your online and offline channels using econometrics, machine learning, and causal inference.
Other methods we can help your team incorporate and model include Brand Lift/Incrementality tests and "How Did You Hear About Us" surveys.
We need to increase our revenue target this quarter. Where should we put our next $100k of spend to drive new revenue?
OutPoint scenario planner is a tool that allows you to plan different spend scenarios across channels and project the impact on incremental revenue.
What will happen if we double or triple spend next month?
OutPoint lets you model 'what-if' type questions, taking into account diminishing marginal returns. You may observe that your customer acquisition cost rises by a disproportionate amount when you increase ad spend. Rising acquisition costs are related to the concepts of Diminishing Returns and Marginal CAC.
How much does OutPoint cost?
The first round of insights are on us. If we can't identify any upside, you pay $0. After that, there is a flexible cost of using OutPoint based on monthly ad spend. You can learn more about our pricing here.
With these data-driven insights, companies can maintain their existing budgets yet achieve improvements of 10% to 30% (sometimes more)
Harvard Business Review
Wes Nichols
Media mix modeling allows advertisers to map spend to revenue on the basis of incremental value & diminishing returns
Mobile Dev Memo,
Eric Benjamin Seufert
World-class team and investors
OutPoint's leadership team is Sean Billings (CTO), a senior engineer who built econometric machine learning models at Amazon, and Rob Palumbo (CEO), who led growth at companies like Properly and Borrowell.
OutPoint's advisory board includes senior growth executives from companies like Wayfair, PolicyGenius, and McKinsey & Company.
OutPoint is funded by Entrepreneur First (EF). EF is a $140M venture builder backed by leading investors including Reid Hoffman, Greylock Partners, Founders Fund, Mosaic Ventures, and Lakestar.