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Is R-squared the Right Metric to Judge your MMM?
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 it around. But what does it really mean? Technically, it measures the proportion of variance in the dependent variable that is explained by the independent variables in a regression model. Mathematically, it's 1 minus the ratio of the residual sum of squares to the total sum of squares. In simpler language: R-squared tells you how well your model fits the data it was trained on. An R-squared of 0.80 means…
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Long-Term Effects in MMM: What You Can (and Can’t) Really Measure
Let’s say you spent millions last quarter on a brand campaign. Where does that show up in your MMM? Everyone…
How to Communicate Data So It Drives Better Business Decisions
“Storytelling with data” sounds great in theory – we all would love to have a single source of truth that…
Backward-Looking vs Forward-Looking MMM: How to Use It for Forecasting
Too many teams treat media mix modeling like it’s just a report card – something you pull out after the…
The Biggest Media Mix Modeling (MMM) Myths – And How Recast Challenges Them
Through countless conversations in the media mix modeling space, we’ve seen the same misconceptions hold models back again and again.…
Average vs marginal ROI in MMM: when to use each (and why both matter for your budget)
It’s tempting to evaluate a channel by its average ROI. If you spend $100,000 on Facebook and generate $200,000 in…
Gaussian Processes for Time Series
Time series data is special because the order in which observations occur is meaningful. For example, looking at sunglasses sales…
Why Marketing Measurement Always Comes with a “Tax” and How to Pay It Smartly
Every marketing measurement strategy comes with a cost. Whether you’re running incrementality tests, MMMs, or lift studies — there’s always…
How to Prioritize Marketing Bets for Maximum Incremental Return
Marketers love to talk about experiments. And experiments are great, but marketers who only focus on A/B tests and holdout…
What to Do When Your Marketing Experiment Isn’t Statistically Significant
If you’re treating p < 0.05 as the litmus test for your marketing experiments, it’s going to be really hard…
The Inaction and Panic Cycle: How Poor Measurement Traps Marketing Teams
The board just asked for ROI improvements by next quarter. Your growth is flat. Pressure is rising. Budgets are under…
What Are Priors in MMM – And Why They’re Difficult to Get Right (But You Need To)
How do you make sure your model doesn’t spit out negative ROIs on channels that are clearly working? Or attribute…
Why Lower Funnel Channels Can Mislead Your MMM (And What to Do Instead)
Lower funnel channels – branded search, retargeting, affiliate – always look like heroes in your marketing mix. They convert fast,…
Granger causality isn’t real causality. Here’s what it actually measures.
Every marketer wants to know what’s working. But in the world of time series analysis, one of the most misleading…
How to Use Lift Tests to Calibrate an MMM
There’s a lot of confusion from marketers about the right way to use lift tests or incrementality experiments to calibrate…
How to Prioritize Experiments When You Can’t Run Them All
Most marketers want to test everything. But you don’t have unlimited budget, time, or team capacity. So you need to…
The Hidden Cost of Over-Controlling for Non-Marketing Variables
A somewhat unpopular opinion we hold at Recast: yes, GDP, consumer sentiment, inflation, and interest rates do impact business performance…
How to Frame a Testable Hypothesis Before Running a MMM
The goal of any media mix model (MMM) isn’t just to describe past performance — it’s to inform decisions .That…
A Framework for Evaluating the Signal Quality of Incrementality Tests
Imagine a brand runs a geo lift test. They shut off ads in three regions for a few weeks, compare…
Recast Model Performance Metrics Explained
Model transparency and accountability are foundational to our work at Recast. We openly publish model performance metrics to customers and…
The Most Common Mistakes Marketing Teams Make when Interpreting Lift Test Results
More and more brands are running lift tests. That’s a good thing. Incrementality experimentation methods are not that complicated —…
How to Talk About Uncertainty in MMM Without Losing Executive Trust
Media mix modeling introduces statistical rigor, causal inference, and a more accurate picture of what’s driving growth across your marketing…
Why Attribution Breaks at Scale (And What to Do Instead)
Attribution systems break at scale because they can’t measure causality. As businesses grow more complex, they often fall into what…
Why Freezing Coefficients in an MMM is a Bad Practice
If you’re freezing coefficients in your media mix model, your model is broken. It’s one of the most common, and…
Fact and Fiction in Marketing Experimentation
“Incrementality testing” is extremely hot right now. And while I am personally extremely enthusiastic about this type of experimentation and…
Automated Data Quality Checks at Recast
Garbage in, garbage out. If a media mix model has any chance of working, the model has to be fitted…
Are Too Many Control Variables Damaging Your Media Mix Model?
A common mistake in media mix modeling (MMM) is the belief that “more control variables are always better.” This mindset…
Taking Your Media Mix Models from Stable to Truly Robust
Marketers often look for stability in their media mix models (MMM), assuming that if a model produces consistent results over…
Running an Open-Source MMM Is Easy. Trusting Its Results Is Hard.
The marketing measurement space has seen a surge in open-source marketing mix modeling (MMM) tools like Google’s Meridian and Meta’s…
Why Internal Validation Metrics Are the Wrong Way to Judge Your MMM
The most dangerous media mix model (MMM) isn’t the one that’s obviously wrong—it’s the one that looks right but quietly…
Introduction: How to Build an Incrementality System
Setting the scene Marketers have been given an impossible task. They are being asked to grow the business in the…
The MMM Checklist
At Recast, we often speak with practitioners who are trying to build their own MMM in-house. While we think there…
How to Help Your Finance Team Understand the Value of Incrementality
If your executive and finance team has become addicted to only looking at the last-touch attribution report in Google Analytics,…
Why Building a Robust MMM Is Tough: Tackling Diminishing Returns, Data Limits, and Time Shifts
What should companies doing (or thinking about doing) media mix modeling beware of? At Recast, we’ve seen the biggest MMM…
The 3 Hurdles of Estimating a Bayesian MMM: Saturation, Divergences, and Multimodality
At Recast, we’ve built our media mix modeling (MMM) platform based on Bayesian methodology because we believe it provides the…
Optimize Your Marketing Mix Modeling with the Ideal Data Window
One of the most critical factors in building an accurate media mix model comes down to choosing the optimal historical…
Product Update: Multi-Stage Models
Many businesses face tough challenges when it comes to measuring marketing incrementality because the nature of their product implies conversions…
Why Model Configuration Makes or Breaks Your MMM
Media mix modeling (MMM) isn’t theoretically hard to do, but it’s really hard to do well. Every step of building…
Why Good Priors Are the Key to Accurate Bayesian MMM
Not all MMMs are created equal. At Recast, we’ve embraced a Bayesian approach to MMM because it allows for more…
Why Measuring Brand Campaigns with MMM is So Hard – And What You Can Do About It
You spent millions on a brand awareness campaign – great! But now you’re left with a tough question: how do…
Why Marketers Must Own Their MMM Results, Not Outsource Them Entirely
1. Introduction This article will sound counterintuitive – Recast is an MMM vendor (within our incrementality system). So why are…
The Rise of Incrementality: What 2024 Taught Us and Our 2025 Predictions
Two learnings from 2024: it was a great year for incrementality, but MMM took a much bumpier path. First, incrementality…
MMM Isn’t Always the Answer: What Early-Stage Brands Should Prioritize First
It will surprise you to hear this from us, but media mix modeling (MMM) is not the right solution for…
How do new media channels fit in with your MMM?
Every few years, a new media channel rises and leaves marketers wondering how it fits in their current channel mix,…
What Makes a Good Marketing Mix Model?
Not all MMMs are created equal. A good MMM can uncover causal relationships, provide actionable insights, and transform your marketing…
Why Traditional MMMs Fails to Capture True Holiday Impact (And How to Model it)
“What impact did our Black Friday promo really have on revenue?” It’s one of the most common questions we hear…
Why Every Marketing Mix Model Should Be Treated with Skepticism (Including Recast’s)
Our customers trust us to make $100M budget allocation decisions. We take that very seriously. Decisions will be made. Money…
Why Time-Varying ROIs Are Crucial for Accurate Marketing Mix Models
Any MMM that doesn’t account for time-varying ROIs is fundamentally flawed. It’s that simple. Ask any marketer, and they’ll tell…
How Omnichannel Brands Leverage Marketing Mix Modeling (MMM)
In today’s rapidly evolving retail environment, it can be a real challenge for omnichannel brands to measure the incremental impact…
How Recast Configures the World’s Most Rigorous MMM: A Step-by-Step Guide
At Recast, our mission is to build the world’s most rigorous Marketing Mix Modeling (MMM) platform. And this starts right…
How Recast Is Building the World’s Most Rigorous MMM Platform
At Recast, we set out with an ambitious goal: to build the world’s most rigorous Marketing Mix Modeling (MMM) platform.…
7 Things to Look Out for When In-Housing Marketing Mix Modeling (MMM)
In-housing your Marketing Mix Modeling (MMM) can seem like it gives you more control over your data and insights, but…
10 Ways to Build a Bad MMM (Marketing Mix Model)
Building a Marketing Mix Model (MMM) that actually works and you can trust isn’t easy. A great model can radically…
How to manage uncertainty in Media Mix Modeling
In marketing, every forecast comes with some level of uncertainty – whether you’re predicting sales growth, estimating the impact of…
The Importance of Out-of-Sample Goodness of Fit Metrics in Marketing Mix Modeling (MMM)
The goal of MMM is not just prediction—it’s understanding causality. When marketers ask how much each channel contributed to sales,…
The Hidden Pitfall in Marketing Experiments: Understanding Uncertainty
“I ran an experiment showing positive lift but didn’t see the results in the bottom line.” Sounds familiar? I think…
Carry-Over Effects: Why They Don’t Limit Media Mix Model Updates
Does the carry-over effect problem mean you can’t refresh your media mix model more than once a quarter? No. Sadly,…
The Hidden Truth Behind Incrementality Testing Results
Is your incrementality testing partner hiding something from you? We’ve seen it too many times: brands come to us very…
Recast Validation: Model Stability
“There is nothing so stable as change” – Bob Dylan Why Measure Model Stability? Media mix models (MMMs) need to…
Understanding Overfitting in Media Mix Modeling: Risks, Metrics, and Validation
MMMs are powerful models and that means they’re subject to what modelers call “over-fitting”. The idea is that you can…
How do Causal Directed Acyclic Graphs (DAGs) work in Marketing Mix Modeling:
Correlation vs causation is a huge marketing measurement problem that traditional methods often fail to account for and can lead…
5 Key Lessons for Successful Enterprise-Level Media Mix Modeling
Media mix modeling at the enterprise level can be quite complex but, when done well, has a huge impact across…
The Replication Crisis: Challenges and Lessons for Modern Statistical Practices
Over the past few decades, the scientific community has grappled with what is now known as the replication crisis—a widespread…
Evaluating Media Mix Model Accuracy: The CRPS Score in Backtesting
Can you trust your media mix model? That is an obvious but not asked enough question that everyone using MMM…
Could AI revolutionize media mix modeling?
Is AI revolutionizing media mix modeling? People have been asking about how AI is changing media mix modeling, and the…
What should be in your Marketing Mix Modeling (MMM) Request For Proposal (RFP)?
We see a lot of media mix modeling RFPs here at Recast. Unfortunately, a lot of them don’t emphasize what…
What are interaction effects in marketing (with examples), and how to model them in your MMM
If you’re doing media mix modeling in-house or through a vendor, being thoughtful about interaction effects will be key to…
Dynamic Spend Deployment and Forecast Checking: How to Validate your MMM Through Use
If a tree falls in a forest and no one is around to hear it, does it really make a…
How To Do Stability & Robustness Checks for Marketing Mix Models (MMM)
We hate when people say that statistical modeling is more art than science. It’s generally what someone says right before…
The Decline of Tracking Pixels: Marketing Measurement in a Privacy-Focused World
That digital tracking is breaking should be of no surprise to any marketer by now. The things that have worked…
How to Get Marketers to Actually Use the Insights from your MMM
One of the biggest challenges in marketing mix modeling that we don’t see get talked about enough is how to…
Google Meridian MMM: Features and Limitations
Last updated: March 11, 2024 Google’s Meridian MMM platform was just announced last week and is currently in closed beta…
Recast vs LightweightMMM vs Robyn
If you’re considering working with a marketing mix modeling vendor, you’ve probably heard of Google’s open-source MMM tool, Lightweight MMM,…
How Geo-Testing Enhances Marketing Mix Modeling Accuracy
Now that digital tracking is breaking and brands are using alternative measurement methods, we will see much more “triangulation” and…
Burn In: How Recast Handles Carry-over Effects
One of the ever-present problems with marketing mix modeling is that you always have to choose some start date. And since you always need to choose a start date, there’s always some period before the start date that’s impacting your results. Here's how Recast handles these carry-over effects.
Consideration period is not the same thing as advertising effect length
In the context of marketing analytics in general and marketing mix modeling in particular I often encounter confusion about the…
Should you set a non-marketing baseline in your marketing mix modeling for exogenous factors?
There are thousands of non-marketing factors that can make an impact on your company’s base sales. Consumer sentiment, GDP growth,…
Does marketing mix modeling (MMM) work for multi-channel, multi-market campaigns?
Is it possible to have a multi-channel, multi-market campaign and still get actionable insight from your media mix modeling on…
What are Halo Effects and how do they impact MMM?
We live in an omni-channel world, and that has drastically changed the way consumers buy. It’s no longer a linear…
Revolutionizing Marketing Measurement: Recast’s Journey to Building Modern Marketing Mix Modeling (MMM)
It is said that the best product ideas come from having to scratch your itch – from facing a big,…
The Correlation vs Causation Challenge in Marketing Mix Models
The distinction between correlation and causation is a fundamental challenge within MMM, and it has significant implications for the efficacy…
3 Key Indicators That Your Company Might Not Be Ready for MMM
With digital tracking breaking and marketers losing visibility, many are turning to Marketing Mix Modeling (MMM) as an alternative measurement…
Google is Deprecating Cookies. How will it Impact Marketing Measurement and Marketing Mix Modeling?
For years, third-party cookies have been the backbone of digital tracking, and have enabled advertisers to tailor their strategies based…
Integrating Marketing Mix Modeling Into Your Decision-Making Process
What channels drove our revenue last week? What happens if we 2x our spend on Meta? What happens if we…
The Tax of Learning from Marketing Experiments
The future of marketing measurement goes through understanding how to use multiple methods in conjunction and not in a silo. …
Integrating Marketing Mix Modeling (MMM) with Multi-Touch Attribution (MTA): A Guide by Recast
Brands looking for 100% clarity in marketing measurement by using just one method won’t find it. Multi-touch attribution won’t give…
How Negative Underwear Found Their Measurement Source of Truth
Negative Underwear is a women’s underwear company that believes all women should feel confident and comfortable in their own skin.…
How Mockingbird Measures True Incrementality with Recast
Mockingbird empowers parents with premium, well-designed baby gear like their signature Single-to-Double Stroller. With a complex buyer’s journey and an…
How to do holdout accuracy and backtesting for your MMM (and why it matters)
You don’t just want an MMM model. You want a model that can be trusted. But since MMM models are…
Why is validation challenging in MMM? What are the different ways to validate?
“How do we know if the model is right?” That’s one of the most important questions in MMM. Most MMM…
High-velocity Marketing Testing
As more marketing teams understand the need to add new measurement methods beyond digital tracking, we expect more and more…
9 Questions to Ask Your MMM Vendor (or Internal Marketing Science Team)
Introducing Media Mix Modeling (MMM) into your organization is a decision that requires careful consideration and due diligence. MMM is…
MMM 101: How to pitch your finance and executive team on Media Mix Modeling and Incrementality (Template)
If you want your company to start using MMM, you’ll have to get buy-in from your finance and your executive…
Is TikTok’s New Attribution Analytics Measurement Tool a Game-Changer for Marketers?
TikTok’s new Attribution Analytics was just launched in September 2023 and it is meant to be a significant advancement…
How to reduce bias in your marketing mix modeling (MMM) with better parameter settings
Marketing Mix Models (MMM) are very complex, and the choice of the parameters your data scientists choose can really influence…
What Data is Needed for Marketing Mix Modeling (MMM)?
MMM is hard enough — but it’s just impossible if you don’t have the right data. Getting good, clean, and…
How to use MMM for planning and forecasting
Marketers hate planning season. It can often feel like an impossible task: you’re being asked to predict the future in…
How is Recast so Fast?
People who have been around the world of marketing mix modeling (MMM) for a while are often shocked that Recast…
How Recast handles “lower funnel” channels
It’s a question as old as Adwords: is my branded search spend truly incremental? Branded search ads are those that…
Upcoming Privacy Changes by iOS 17 and its Impacts on Tracking
Every marketer whispers “here we go again” to themselves every time a new iOS update from Apple is announced. And…
10 Common Mistakes MMM Consultants Make:
MMM is hard – we totally get that, but there are common mistakes made by consultants in the MMM space…
How to Measure YouTube Ads
YouTube is a powerful advertising platform with over 2 billion active users. However, measuring the effectiveness of YouTube ads can…
From Digital Tracking To MMM: How Brands Scale Through Marketing Experimentation
Most small e-commerce brands probably don’t need anything more complicated than digital tracking tools for measuring marketing performance. But when…
How to Measure Affiliate Marketing
Affiliates are really hard to measure. Brands that do affiliate marketing will often face these three main challenges: 1 –…
Traditional MMM vs Modern MMM
When we talk to consumer brands about MMM, the concerns about its capabilities are sometimes slightly outdated. MMM has historical…
The Brand-Direct Response Spectrum: Why All Marketing Should Be Performance Marketing
Marketers often talk about the brand-performance spectrum, but we look at this differently at Recast. We believe that all marketing…
How do lift tests fit in with MMM
With digital tracking breaking, consumer brands that relied on multi-touch attribution are now looking for alternatives to measure marketing effectiveness.…
Why isn’t everyone Bayesian?
Recast’s MMM uses Bayesian statistics, but why doesn’t everyone else? We asked this to Recast’s co-founder Michael Kaminsky, and the…
3 Methods To Validate Your Marketing Mix Modeling for True Incrementality
Marketing Mix Modeling’s main goal is to find the incremental return of every marketing investment – how many sales did…
Recast’s Lift Test Calculator [Download + Video Walkthrough]
Today, we introduce the Lift Test Calculator – an open-sourced tool designed by Antonio Vargas, a senior data scientist at…
How we do holdout testing at Recast
The central modeling challenge for an MMM is the following: given any set of marketing inputs (budget decisions, promotion dates,…
Recast vs LightweightMMM
People often ask us about the differences between Recast’s next-generation MMM platform and Google’s open source MMM tool, Lightweight MMM.…
Why should we refresh our MMM every week?
Quite often we encounter people who have been working with legacy MMM vendors for 15+ years who are shocked when…
Top consumer brands don’t pick one measurement method: they triangulate.
There are three main ways that consumer brands measure marketing effectiveness: digital tracking (MTA), marketing mix modeling (MMM), and testing/conversion…
The 4 phases in the marketing measurement journey:
Marketers are in a tough spot when it comes to measurement: iOS14 made everyone conservative about tracking, performance marketers are…
How and when to upgrade from MTA to MMM
With digital tracking breaking and privacy concerns on the rise, more consumer brands are looking for alternatives to multi-touch attribution. …
How to Test the Incrementality of New Channels
Brand new channels can be very difficult to measure out of the gate, so it’s important to be thoughtful about…
Not All Experiments Are Created Equally: Navigating the hierarchy of evidence
Many marketers have been turning to experiments to help them get a true read on incrementality for their marketing channels.…
Recast vs Robyn: Feature Comparison
People often ask us about the differences between Recast’s next-generation MMM platform and Facebook’s open source MMM tool, Robyn. In…
How D2C Brands Can Deal with Multicollinearity in their Marketing Mix Modeling
Multicollinearity is one of the hardest problems in marketing analytics. If you took a statistics course in undergrad, you might…
Understanding How MMM Works
When we talk to folks who are new to Media Mix Modeling (MMM) and tell them there’s no pixel or…
The Evolution of Privacy: A Timeline of Events Reshaping Identity-Based Tracking and Analytics
To prepare for the future, we must understand the past. This stays true in marketing, and it is particularly appropriate…
How Marketers Should Think About Attribution at Different Stages of Growth
Coca-Cola does not think about attribution the same way an early-stage D2C brand thinks about it. Everything is different: budgets,…
‘How did you hear about us?’ survey and the limitations of current measurement techniques
In the world of website analytics, the concept of “dark social” has emerged as a significant challenge for accurate channel/source…
Why You Can’t Trust Google Analytics
Google Analytics has recently gone through significant changes that have sparked concerns among marketers around its bias and validity. As…
Why You Need to Stop Controlling for GDP Growth (and what to do instead)
Your marketing performance doesn’t live in a silo and it’s not independent of external factors. One of those that will…
Should You Be Using the GeoLift Library to Run Geo-Testing Lift Tests?
With privacy concerns on the rise and digital tracking becoming less reliable, marketers need advanced tools to measure the impact…
How to fix heteroskedasticity in your Marketing Mix Model
Disclaimer: This blog post was written by an external contributor about detecting and addressing heteroskedasticity in marketing mix models. The…
Who is talking about using MMM?
Brands have been using models to understand the effectiveness of their marketing activities since the ‘Golden Era’ of advertising in…
Adventures in Brand Health Modelling
Disclaimer: This blog post was written by an external contributor about their experience attempting to work with brand health data. This…
Diminishing Returns: Accounting for Channel Saturation
You cannot double spend and expect sales to double. Advertising on auction-based platforms like Meta or Google exhibits diminishing returns,…
Validation Through Testing
Marketing Mix Modeling (MMM) is hard. The core difficulty is that MMM is trying to solve a causal inference problem…
Is Recast Just a Regression?
MMM is about Causation not just Correlation At the highest level, the idea behind MMM is to look at the…
Do Data Clean Rooms Really Solve the Attribution Problem?
With digital tracking breaking since iOS14, the death of the cookie, and new privacy laws like GDPR and CPRA, media…
Unraveling the Impact of Pull Forward Promotions: Are They Really Incremental?
Sales and promotions are a tricky concept and many ecommerce brands struggle to measure them correctly. We’ve all seen the…
The Conundrum of Brand Search: Is it Incremental and Actually Driving You That ROI?
Knowing whether brand search is incremental for your brand or not is often a question worth tens of thousands, hundreds…
Shining a Light on the Dark Funnel: Overcoming Attribution Challenges with MMM
How can marketers track what cannot be tracked? The ‘dark funnel’ is one of the main challenges we all face…
Halo effect: measuring the impact between different marketing channels
Marketing efforts in one channel can impact traffic and attribution in other channels. This positive or negative interaction between different…
MER is a Road to Ruin
As a former agency owner, I know first-hand the importance of measuring marketing performance accurately. In the world of Direct-to-Consumer…
Is Less Really More? The Art and Science of Experimenting with Channel Cuts
Airbnb famously turned off their paid media and argued it turned out to be a successful decision. But was it?…
How to Measure Influencer Marketing
Influencer marketing is the technique of compensating a celebrity or someone well-known in your industry for promoting your product or…
The incrementality test that got my boss’s boss fired
Early on in my career, I learned a valuable lesson in incrementality that I’ll never forget. Ever since I had…
Vanity metrics vs actionable metrics: Quantifying quality
Any metric that doesn’t have a strong causal link with sales outcomes is a vanity metric. For example while Clickthrough…
Recast Model Validation Process
At Recast we believe that in order for our customers to get value out of Recast, the model needs to…
Why “Brand Effects” are so difficult to measure in MMM
Updated: August, 2024 Many brands want to know what the long-term effects of their marketing efforts are. The theory is…
Marketing Mix Modeling for Scenario Planning
Scenario planning or demand forecasting decides everything an enterprise does. Right from quantities of raw material sourced to the inventory…
You’re losing more traffic to ad blockers than you probably realize
As the use of ad blockers continues to grow, ad buyers are losing visibility on the effectiveness of their marketing…
The right way to cross-validate your Marketing Mix Model
Disclaimer: This blog post was written by an external contributor about techniques for validating marketing mix models using cross-validation. The…
The History of Econometrics in Marketing
Marketers are often very focused on the future as their jobs rely on anticipating and meeting the needs of consumers…
The case against using impressions in MMM
At Recast we generally recommend using spend — not impressions — to represent channel activity in a marketing mix model.…
The Problem with Modeled Conversions
We’ve been seeing more and more advertising platforms promote some form of “modeled incrementality” estimates and often marketers aren’t sure…
Lift analysis for taking back the credit SEO is stealing from your campaigns
I once ran a new PR campaign for a website that I knew did not have any previous backlinks. The…
Predictive Modeling in Marketing: The What, Why and the How
Disclaimer: This blog post was written by an external contributor about applications of predictive modeling in marketing. The approach laid…
How confounding variables and company silos can ruin your analysis
You can boost revenue by scientifically optimizing your marketing spend. What could go wrong? Statistical mistakes could de-optimize your marketing…
The ADPPA — Data Privacy Comes to the USA (and how not to lose sleep over it)
In July 2022, the American Data Privacy and Protection Act (ADPPA) became the first bicameral and bipartisan online privacy bill…
Make a business case for TOFU channels via first-touch attribution
As a content marketer working on top-of-the-funnel channels like social media, PR, podcast, etc. one of the top challenges you…
Monte Carlo Simulations: A Tool for Predictive Analysis and Informed Decision Making
Monte Carlo simulations are a powerful tool for doing predictive analysis. By running multiple simulations with different input variables, analysts…
The pitch deck we used to raise $3 million
I’m happy to announce we just raised $3.4 million at a $25 million post-money valuation! This year, a slowdown in…
MMM Template
We made this template because honestly it’s a lot of work to do MMM manually if you don’t have the…
Measuring the Long Term Effects of Brand with MMM
Brand vs. Performance marketing has been a growing battle online since digital advertising grew to be the dominant share of…
Adstocks: Accounting for the Lagged Effect of Advertising
One of the core problems to solve when doing marketing mix modeling (MMM) is handling how the results from a…
Meta Sustainable Measurement Summit
The team at Meta did another Marketing Mix Modeling summit last week, and given the popularity of the last one…
Why Marketing Mix Modeling doesn’t work for new channels (and how to fix it)
Disclaimer: This blog post was written by an external contributor about approaches for measuring new marketing channels with marketing mix…
Meta Marketing Mix Modeling Summit Highlights
The Marketing Science team at Meta set the Marketing Mix Modeling world alight when they released Robyn, their open source…
Your email open rates aren’t as good as you think they are
In the advertising world the impact of iOS14 has been apocalyptic. Offering users the ability to turn off tracking, has…
Some Testing is a Waste of Time: Making Business Cases for Big Bets
This is our second feature in the much exalted Reforge blog, this time talking about how to make big bets…
How to Measure Podcast Advertising
Podcast advertising is a form of digital advertising that allows companies to place ads in podcasts. This type of advertising…
Brand Incrementality Testing in Practice
Business environments are messy; people with different responsibilities need to work together on decisions quickly and without perfect information. That…
Recovering 300% More Revenue by Matching Online Activity to Offline Sales
When setting up e-commerce conversion tracking, you’ll often find that most of the events worth tracking are online such as…
Not all revenue is created equal
A few years ago I was running Facebook advertising for an eCommerce store selling print-on-demand products across Europe: think posters,…
How to Measure TV Advertising
TV advertising is the process of promoting a product or service on television, across broadcast, cable, or satellite. This can…
Google’s Data-Driven Attribution: a $40,000 mistake
For years after I left my agency I described myself as a “recovering agency owner”, and it would always get…
Attribution is opinion, canonical conversions are fact
Ad platforms use their attribution models to tell you which campaigns contributed to conversions (leads, sales, subscriptions or whatever is…
The difficulty measuring ‘dark social’ traffic and word of mouth
There’s a commonly cited Neilsen study that revealed that 92% of consumers trust referrals from family or friends more than…
Are you wasting money on Branded Paid Search?
The Search Advertising Market has been valued at 178 Billion in 2021 and is expected to grow at an 8.5%…
Limitations of GeoLift Experiments
At Recast, we generally believe that most brands should be running more experiments, including geographic lift tests. However, we think…
Is there a good way to do a test of statistical significance for ROAS?
Someone posed the following query in a marketing measurement slack I’m in: At first, this question seemed really easy. Hubristically,…
Cleaning URLs for Accurate Channel Attribution
Anyone who’s ever run an online marketing campaign has encountered URL parameters. These are an additional section you add at…
Google Analytics Channel Attribution Made Us Switch Off Our Growth Engine
Nobody sits down to make a channel investment decision they hope will immediately lose millions of dollars and get them…
How much data do you need for your Marketing Mix Model?
One commonly asked question from clients just getting started with Marketing Mix Modeling (MMM), is how much data they need…
What does ‘Incrementality’ mean?
In the context of marketing measurement, marketing analysts and marketing scientists use the term “incrementality” to refer to causality. Incrementality…
Why R-squared is worse than useless
At Recast I have the privilege and challenge of introducing advanced statistical concepts to people who have a strong desire…
When Promo Codes Aren’t Enough: Measuring Influencer Campaigns with Marketing Mix Modeling
This post talks about how to do Marketing Mix Modeling when you’re investing heavily in influencer marketing. We teamed up…
How Uber Orbit Works
Disclaimer: This blog post was written by an external contributor about Uber’s open-source Orbit library for time series forecasting and…
Media Mix Modeling for Mobile: What Data is Needed?
We teamed up with mobile growth agency Phiture to create this post for those in the mobile space looking to…
The brand-direct response spectrum
One of the biggest misconceptions holding back marketers to day is the myth of the brand–performance marketing dichotomy. Many newer…
Why Recast Doesn’t Control for COVID
Occasionally, prospective customers react with shock when we tell them that we don’t “control for the COVID pandemic”. “The pandemic…
Being Thoughtful About “What’s My Email ROI?”
For many businesses, email programs are a huge revenue generator. For every $1 marketers spend on email marketing, they receive…
Marketing in Times of Uncertainty
Introduction The macro-economy in the US is tough right now. Inflation is up (driven in large part by insane gas…
How to automate marketing mix modeling with an MMM data feed spreadsheet
We partnered with Supermetrics to bring you this post on how to build an MMM feed automatically in Google Sheets.…
Calibrating Your Marketing Mix Model With Post-Purchase Survey Data
In this post we cover a common way to make your marketing mix model work with your other attribution methods:…
How Google LightweightMMM Works
Disclaimer: This blog post was written by an external contributor about Google’s open source marketing mix modeling tool LightweightMMM. The…
Setting Realistic Expectations Between Marketing and Finance
One of the hardest things to do is get buy in from the finance team when requesting marketing budgets. This…
How to make a marketing report that accounts for macro trends
In this post we collaborated with Funnel.io to show how you could use their various ad platform connectors to do…
Marketing Mix Modeling Software: Build vs Buy Calculator
Marketing Mix Modeling (MMM) has been around since the 1960s, where it was used to correlate spikes and dips in…
The Best Marketing Attribution Software For 8 Measurement Methods (2022)
The global marketing attribution software market is set to grow by 14.4% to USD 3.6 billion by 2023. However the…
The Attribution Stack: How to Make Budget Decisions in a Post-iOS14 World
In this post we cover the attribution stack, and how it relates to the impact of iOS14. This is a…
Why MMM is so hard
Marketing mix modeling is hard. Trust us. When we were starting Recast, we thought it’d be easy: we’d use some…
What is Linear Regression?
Linear regression is one of the most well known and well understood algorithms in statistics and machine learning. Anybody with…
Causal Inference: Where does it sit in the hierarchy of evidence?
If there’s one thing everyone knows about statistics, it’s that ‘correlation is not causation’. Ice cream sales and shark attacks…
Creative performance drives 47% of sales: why is it missing from most models?
In 2017 Nielson conducted a study of 500 advertising campaigns across all major media platforms: TV, digital, magazines and radio.…
The Four Pillars of Media Measurement
In the marketing world, there are four main ways to measure marketing effectiveness. Each of these approaches have their strengths…
The Attribution Stack
The Attribution Stack was featured in our post on Reforge: “The Attribution Stack: How to Make Budget Decisions in a…
Negative ROMI: Lose money to make money
In 2014 McKinsey published a study entitled “Grow Fast or Die Slow”, which examined thousands of software and services companies…
Decomp RSSD: Optimizing for Politics
Most people aren’t aware that Facebook (Meta) invented a new ‘accuracy’ metric. Their own documentation calls it a ‘major innovation’…
How Facebook Robyn Works
Facebook (Meta) bet on Marketing Mix Modeling (MMM) to save their ads business, after Apple’s iOS14 update gave users the…
You’re probably modeling seasonality the wrong way
Nearly every business has an annual cycle: seasons where the business waxes or wanes, or specific dates like Cyber Monday,…
What does “Bayesian” mean and why is it better?
Elon Musk believes we live in a simulation. His argument goes: “If you assume any rate of improvement at all,…
What is attribution?
At the highest level, marketing attribution is about estimating the relative effectiveness of different advertising channels. While the term is…
Introduction to Bayesian Methods for MMM
Introduction Note: this post was developed in partnership with Mike Taylor over at Vexpower where they’re working to educate marketers on how…
The Recast Philosophy
Last updated: August, 2024 At Recast, we hold strong views about the right way to do Media Mix Modeling (MMM)…
Shifting from Legacy to Modern Marketing Mix Modeling
The popularity of Marketing Mix Modeling (sometimes known as Media Mix Modeling, or simply MMM) has increased rapidly over the…
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