Measuring the Long Term Effects of Brand with MMM - Recast
Our belief at Recast is that it’s not Brand versus Performance, but that it’s more of a Brand-Performance spectrum.| Recast
Our belief at Recast is that it’s not Brand versus Performance, but that it’s more of a Brand-Performance spectrum.| Recast
Multicollinearity makes it difficult to make confident marketing decisions. This article will help you with what you can do to solve for it.| Recast
Creative is the biggest factor driving performance, yet it's missing from most marketing mix models. How and when should you incorporate it?| Recast
When setting up e-commerce conversion tracking, you’ll often find that most of the events worth tracking are online such as add to cart, checkout sessions or online transactions. However this conversion tracking model doesn’t work well with bespoke, high cost e-commerce shops. I quickly discovered this whilst working with william […]| Recast
Most media mix models can’t be proven wrong. That’s a problem. You’re supposedly using your model to forecast and allocate millions of dollars on marketing spend… and you can’t tell if it’s right or wrong? The issue is that most models don’t make testable claims – and that needs to […] The post What Is Falsifiability (and Why It Matters in Media Mix Modeling) appeared first on Recast.| Recast
According to CreatorIQ’s “State of Creator Marketing: Trends and Trajectory 2024-2025” report – which surveyed 457 marketing decision-makers at brands – measuring program success has become the #1 challenge in influencer marketing. And it makes sense: influencer data is messy – scattered timelines, unclear impressions, unpredictable performance. It doesn’t behave […] The post How to Actually Measure Influencer Marketing (Even When the Data’s Messy) appeared first on Recast.| Recast
Most marketing mix models break because they assume that marketing effectiveness is constant over time – but that’s not how marketing works in the real world. Marketing effectiveness changes constantly. Sometimes dramatically. It changes when you update creative. It changes when your audience saturates. It changes when new competitors enter […] The post Why Time-Varying Covariates Matter More Than You Think in MMM appeared first on Recast.| Recast
Let’s start with the “bad” news: the true incremental ROI of any campaign is unknown and unknowable. Marketing performance lives in a world of noise, lags, and missing data. We would all love to be able to report numbers like “3.7x ROI” as if they were the objective truth – […] The post Why You Should Use Forecast Ranges in Media Mix Modeling (Not Single-Point Predictions) appeared first on Recast.| Recast
Not every lift-testing or incrementality experimentation platform is created equal. Customers have used GeoLift by Recast to design and analyze hundreds of incrementality experiments using the platform’s best-in-class algorithms. We believe these have led to the most accurate and actionable test results in the market. In fact, many Recast customers […] The post Why Recast’s Synthetic Control Methods are Better appeared first on Recast.| Recast
Reanalyze past geo-based incrementality tests with GeoLift by Recast. Validate results & apply synthetic controls with a step-by-step guide.| Recast
Explore the replication crisis, P-value pitfalls, and their impact on Marketing Mix Modeling. Learn best practices for reliable analysis.| Recast
Recast is fast and accurate incrementality measurement, comprising Recast's Causal MMM and Recast GeoLift.| Recast
Learn 5 crucial lessons for implementing enterprise-level Media Mix Modeling. Discover strategies for success and avoiding common pitfalls.| Recast
GeoLift by Recast measures the incremental impact of your marketing with geographic-based lift tests—separating true revenue-driving channels from channels that only claim credit.| Recast
Considerations when designing geographic based lift tests in GeoLift by Recast or other experimentation tools.| Recast
Explore why integrating non-marketing factors like GDP growth and inflation into your Marketing Mix Modeling might not be the best strategy.| Recast
Explore the complexities of affiliate marketing, from diverse partnerships to understanding true purchase drivers.| Recast
Discussion of why model weekly refreshes would be useful, even if you weren't planning on making changes to your marketing budget every week.| Recast
What are probabilistic estimates? When using models to make decisions, quantifying uncertainty about your model’s estimates is crucial to making informed decisions. Recast expresses uncertainty in both our in-sample parameter estimates and our estimates of future performance. For example, last quarter you ran a 6-month estimate of revenue using your […] The post Using CRPS to Evaluate Recast Models appeared first on Recast.| Recast
Designing lift tests can be tricky for businesses that have substantial amounts of natural or induced seasonality in their business.| Recast
This post will focus on understanding the history of econometrics to explain the wider context of trends that have shaped the field.| Recast
You have probably seen R-squared everywhere. It is one of the most widely taught and commonly cited metrics in statistics. It’s taught in every introductory stats course. It’s included by default in nearly all statistical software packages. Run a regression, and R-squared is going to be the metric they base … Is R-squared the Right Metric to Judge your MMM? Read More » The post Is R-squared the Right Metric to Judge your MMM? appeared first on Recast.| Recast
Turn your MMM into a forward-looking decision engine, not a backward-looking report card. Here’s how to make it actionable.| Recast
Introduction The macro-economy in the US is tough right now. Inflation is up (driven in large part by insane gas prices) and although consumer spending remains high, many are nervous about how consumers will respond to having an ever-larger chunk of their monthly budget eaten up by fuel costs. Many … Marketing in Times of Uncertainty Read More »| Recast
Validating marketing mix models through practical application and comparing forecasts to actual results. Test and learn for continuous improvement.| Recast
Learn why stable MMMs can still be wrong and how to build robust models that adapt to real changes while resisting noise in your data.| Recast
Enhance your Marketing Mix Model's (MMM) trustworthiness: Learn the crucial role of holdout accuracy and backtesting.| Recast
Discover how Recast builds the most rigorous MMM platform with scientific validation, transparency, and actionable results.| Recast
Google recently announced the launch of their new open-source MMM software called Meridian. We break down both its features and limitations.| Recast
Marketing Mix Modeling (MMM) has been around since the 1960s, where it was used to correlate spikes and dips in sales to marketing activity. There has been a recent resurgence of interest in marketing mix modeling, as consumers increasingly opt out of digital tracking and digital-first brands mature to offline … Marketing Mix Modeling Software: Build vs Buy Calculator Read More »| Recast
Learn why internal validation metrics mislead when judging MMMs and how to validate models with real-world testing.| Recast
You cannot double your spend and expect sales to double. Advertising on auction-based platforms exhibits diminishing returns.| Recast
Recast challenges the biggest MMM myths, showing why they fall short and how better models drive smarter marketing decisions.| Recast
Learn the difference between average ROI and marginal ROI in media mix modeling (and why both are so important to consider).| Recast
In this article, we discuss what are the pull forward and pull backward effects and how these can help you run more ROI-positive sales.| Recast
Airbnb famously turned off their paid media and argued it turned out to be a successful decision. But was it?| Recast
Guide execs beyond last-touch—learn why incrementality matters and how to drive data-driven marketing decisions.| Recast
Learn how Gaussian Processes model time series data using covariance matrices and kernel functions with practical examples.| Recast
MMM works based on historical data, which you don’t have when launching a new channel. How do you get around this?| Recast
Ad platforms use their attribution models to tell you which campaigns contributed to conversions (leads, sales, subscriptions or whatever is most important to your business). The way they measure attributed conversions is an opinion based on the data available to the platforms. It’s subject to limitations (for example, conversions need … Attribution is opinion, canonical conversions are fact Read More »| Recast
The sharpest marketing teams think in bets, not tests. Here’s how to prioritize for impact, uncertainty, and feasibility.| Recast
Recast's media mix modeling (MMM) platform updates on-demand and continuously verifies out-of-sample forecast accuracy.| Recast
A guide on how to prioritize marketing tests by impact—not just precision—when you can’t run them all.| Recast
A guide on how to prioritize marketing tests by impact—not just precision—when you can’t run them all.| Recast
Why controlling for too many macro variables in MMM can backfire—and how to model external shocks the right way.| Recast
How three Recast model performance metrics are calculated, including Median Holdout Accuracy and Marketing Dollars Saved.| Recast
How can marketing experiments be done quicker and more often? This is what we'll be discussing in this article.| Recast
At the highest level, marketing attribution is about estimating the relative effectiveness of different advertising channels. While the term is used quite broadly to cover lots of different techniques and tools, the goal is the same: determine which marketing dollars are driving business value and which aren’t. “Half the money […]| Recast
Dive into the evolution of MMM and how Recast is revolutionizing traditional practices to meet today's dynamic marketing needs.| Recast
One of the top challenges you might be facing working on TOFU channels is showing the ROI (Return on Investment) of your work. Here's why:| Recast
Explore the nuances of Marketing Mix Modeling (MMM) and learn if your company is ready for this advanced measurement method.| Recast
Marketing Mix Modeling’s main goal is to find the incremental return of every marketing investment, but how can you validate your model?| Recast
You’ve spent countless hours building an MMM model. How can you be sure that your model is not completely misguided?| Recast
Explore the effects of Apple's iOS 17 update on marketing and email campaigns and its new Link Tracking Protection feature.| Recast
Your marketing performance isn't independent of external factors like GDP (gross domestic product). But that brings with it many questions.| Recast
Explore how Causal Directed Acyclic Graphs (DAGs) improve Marketing Mix Modeling by clarifying causation and preventing bias in analysis.| Recast
Business environments are messy; people with different responsibilities need to work together on decisions quickly and without perfect information. That means that sometimes the statistically perfect approach isn’t the best one; faster or less-risky methods that are just good enough can work better than a fully reliable approach that takes … Brand Incrementality Testing in Practice Read More »| Recast
Discover 10 common mistakes in Marketing Mix Modeling (MMM), from mis-using R-squared to ignoring seasonality.| Recast
How can marketers track what cannot be tracked? The ‘dark funnel’ is one of the main challenges we all face when it comes to attribution.| Recast
The Search Advertising Market has been valued at 178 Billion in 2021 and is expected to grow at an 8.5% Compounded Annual Growth Rate from 2021 to 2018. Search is an important part of the Marketing Mix for most companies. One of the drivers of Search Advertising’s rise is its … Are you wasting money on Branded Paid Search? Read More »| Recast
If you’re a business that relies in any way on user-level data to shape your marketing strategy, that’s not much to be hanging on to.| Recast
Explore how Google Analytics is letting marketers down based on recent changes, their implications, and alternative solutions.| Recast
The core problem of MMM is not running a model and simply getting results, it is actually validating that those results are correct.| Recast
How does Google LightweightMMM work? We break down the core features of Google's open-source media mix modeling package.| Recast
Lots of advertising platforms promote some form of “modeled incrementality” estimates and we need to discuss these and their limitations.| Recast
Explore the impact of Google's cookie phase-out on marketing measurement and the rise of privacy-focused Marketing Mix Modeling (MMM).| Recast
Explore overfitting in Media Mix Modeling: Learn risks, misleading metrics, and out-of-sample validation for accurate model assessment.| Recast
This article clears up common confusion, and discusses six myths, around important incrementality testing concepts.| Recast
MMMs are holistic models operating at an aggregate level. That means if any of the data isn't correct, it puts the whole model in jeopardy.| Recast
Explore why good priors are critical for Bayesian MMM accuracy, how they shape insights, and Recast’s rigorous process for setting them.| Recast
Internal metrics won't prove your MMM works. Learn how to validate models with real tests before making million-dollar budget decisions.| Recast
In this article, we will explore the concept of data clean rooms and their effectiveness in solving the attribution problem.| Recast
View Recast's suite of forecasting, insights, optimization, and goal-tracking tools. All powered by a best-in-class Media Mix Model.| Recast
How do we judge our model’s ability to accurately predict what our customer’s performance will be? This turns out to be somewhat complicated.| Recast
In this article, we will explore the implications of ad blocker adoption for advertisers and how to adapt to this trend.| Recast
Create an incrementality system of continuous planning, experimentation, validation, and optimization for your marketing organization.| Recast
Coca-Cola does not think about attribution the same way an early-stage D2C brand thinks about it. How should you?| Recast
What is incrementality? It's about measuring what actions would not have happened without a specific intervention. For example if you spend money advertising a product, you need to know how many people bought that product because of the ad.| Recast
The Conundrum of Brand Search: Is it Incremental and Actually Driving You That ROI?| Recast
This article recaps the key events that have changed how brands think about tracking and analytics, and the implications this comes with.| Recast
Combining MMM with Conversion Lift Studies offers a clearer insight into marketing efficiency. But how do they enhance the accuracy of MMM?| Recast
Explore how to build an experimentation mindset, measure the value of tests, and modernize your marketing approach with Recast.| Recast
Explore how integrating geo-testing with MMM transforms marketing accuracy, helping to validate strategies and optimize spend.| Recast
Is brand search incremental for your brand or not? This can be a question worth from tens of thousands, up to millions of dollars.| Recast
Highlighting the importance of transparency & minimizing bias in Marketing Mix Models (MMM) with systematic and unbiased parameter selection.| Recast
Learn how to pitch MMM and Incrementality to your finance and executive teams with our practical template guide.| Recast
Discover the top 9 questions to ask MMM vendors or your marketing science team to ensure effective media mix modeling.| Recast
Facebook Robyn is a popular Marketing Mix Modeling tool. It's open-source so anyone can see how it works, but we'll explain the statistics.| Recast
At Recast I have the privilege and challenge of introducing advanced statistical concepts to people who have a strong desire to be more data driven, but who do not have much of a background in formal statistics. While word has gotten out that “statistical significance” isn’t all it’s cracked up … Why R-squared is worse than useless Read More »| Recast
Discover the 5 key features of a great marketing mix model: causality, transparency, validation, stability, and actionable insights.| Recast
Learn why traditional Marketing Mix Models fail to capture holiday promotion impact accurately, and how Recast's Spike Modeling provides deeper insights into true revenue effects.| Recast
Much has been written about iOS14, but far less ink has been spilled on the iOS15 software update and its impact on emails.| Recast
You can boost revenue by scientifically optimizing your marketing spend. What could go wrong? It turns out that many things can.| Recast
How does Uber Orbit work? We break down Orbit's methodology, how long it takes to run and how to action the MMM's output.| Recast
At Recast we believe that in order for our customers to get value out of Recast, the model needs to be correct. Here's how we validate it.| Recast
Since GDPR, iOS14, and newer privacy regulations, digital tracking has become broken. This is where Modern Marketing Mix Modeling comes in.| Recast
There are three main ways that consumer brands measure marketing effectiveness. Here's why you should use all three of them together.| Recast
If you’re seeing that MTA is less and less effective, and you have your eyes on MMM, here's what you need to know.| Recast
Since iOS14, marketers have been scrambling for a new attribution method, and Geo Testing shows promise. Unfortunately it has serious flaws.| Recast
Discover the synergy of lift tests and marketing mix modeling in modern marketing to drive long-term value for your business.| Recast
