Blogs

What Actually Makes MMM Predictable Some people imply that marketing is too unpredictable. Some even go as far as to claim that is like predicting movement of atoms (Brownian motion). I disagree. Marketing and MMM are by an large predictable. 📌 What Actually Makes MMM Predictable? At its core, MMM works because human behavior is not random. As someone rightly said “We are suckers of Habit”. 📌 User Habit: People don’t wake up every day and reinvent their choices. They predominantly go with: – Same brands – Same stores – Same time of purchase This creates structure in demand, which MMM can capture. Habit overall reduces randomness. 📌 Seasonality A seasonal

Why Defining “Base” as Just Trend + Seasonality is a Bad Idea In one of our recent MMM projects, we noticed that earlier vendor had modeled Base = Trend + Seasonality. Few months ago I wrote why the practice of including distribution in Base in MMM is wrong (link in comments). 📌 Base in MMM Statistically, Base is the intercept and it is interpreted as the ‘value of Y (dependent variable) when all your independent variables are made zero’. In marketing, this is interpreted as the sales one would get organically because the marketing / media variables are set to zero. Now apart from this definition and construct of Base,

Brand Equity ALSO Does Performance Marketing (Just Not Immediately) In my previous post, I had mentioned that Performance Marketing DOES build Brand Equity (Just not efficiently). Thanks to some interesting comments, it gave us some food for thought to consider the opposite. Hence Venkat Raman and I brainstormed to ask – “Does Brand Equity also perform Performance Marketing?”. The answer – Yes. But not immediately. Let me breakdown our thought process. 📌 Brand Equity is a “Delayed Performance Engine” Brand equity is essentially stored future conversions. Venkat in one of the posts likens it to Dynamo on a cycle (link to post in comments) “Brand equity is like a dynamo

Unpopular Opinion – Performance Marketing DOES build Brand Equity (Just not efficiently) Most articles that I have seen on the internet draw a clear distinction between Performance and Brand marketing. However I have a slightly different view. 📌 Performance Marketing DOES build Brand Equity Even the most “performance first” channels leave behind small deposits of brand memory. Think about what actually happens when someone sees your ad on Meta, TikTok or YouTube: – They see your brand name – They see your offer / positioning – They mentally register “this brand exists in this category” Even if they don’t click or Even if they purchase in a purely transactional way,

Is Going Niche a Bad Move for Small Brands? I came across a very interesting post from Elena Jasper on How small brands grow (link in comments). I also found in comments of that post that some people think ‘Going Niche’ is not a wise move. I disagree slightly. Firstly I believe, Small brands don’t “choose” to go niche. They are forced to go niche. Going niche is not the problem. Staying niche is. 📌 Survival First Many believe that If small brands are niche-focused, they should show high loyalty. I don’t think this is universally true. Niche ≠ loyalty strategy. Niche = constraint driven positioning. So what are those

The Power of Integrated Measurement System – MMM, Experimentation and Causality ▪️MMM alone is not Marketing Measurement. ▪️Experimentation alone is not Marketing Measurement. ▪️Causality alone is not Marketing Measurement. But together, they form the closest thing we have to a complete measurement system. 📌 The Problem of Solving Only One Piece ▪️MMM predominantly focuses on historical decomposition. ▪️Experimentation focuses on isolated lift measurement. ▪️Causality talks about causal frameworks. Each of these is powerful. But each is also incomplete. 📌 What MMM Does Well MMM gives you: – A holistic view across all channels – Budget allocation insights – Diminishing returns and response curves – Indication of long term effects –

The Inference-to-Description Ratio We just got a pat on the back from one of our clients, who said “Your MMM deck have a lot more inference than our previous vendor”. This made our day, we have always strived to provide more insights than superficial description of data. 📌 I call this the Inference-to-Description Ratio. I believe good MMM Vendors have a high Inference-to-Description Ratio. Basically, it is how much of the work is Inference vs Description Most MMM decks (especially in EDA stages) are full of descriptions: “Sales peak in December” “TV spend increased in Q3” “Digital contributes 35% of spend” These are not insights. These are mere narration. Even

The Effect of Meta’s Click-Based Attribution Recategorization Meta recently informed marketers that they are changing how click-through attribution is defined. Historically, Meta attributed conversions to all types of clicks including likes, shares, saves, comments and link clicks. However, most third-party platforms count only website link clicks. As Meta noted: “This difference in what is attributed as a ‘click’ conversion can lead to inconsistency between what an advertiser sees in Meta Ads Manager compared to third-party reporting tools.” To address this discrepancy, Meta has decided to restrict click-through attribution only to link clicks. At the same time, a new attribution category called “Engaged-Through Attribution” is introduced. This includes signals such as

Why you need much more than R Squared Value to Judge your MMM Around 2 years ago, a client asked us “Ridhima, I trust you and Aryma Labs but as they say, Trust but verify. Is there a way for us to grade your homework without you having to divulge your secrete sauce?” That question eventually led to the creation of MMM Diagnose. 📌 The problem with how MMMs are usually evaluated Traditionally MMMs are judged only on two metrics – R Squared Value – Prediction Accuracy These alone are not enough (you can check the link in comments to know more). A model can show good fit or good

MMM Model Update Cadence Is Often Decided by Budget and Not by What is Ideal So here is a unpopular opinion or fact – Most MMM model update cadence is decided by budget availability rather than what is ideal. One of the least discussed aspects of MMM is model refresh cadence. 📌 How often should an MMM be updated? In theory, the answer should depend on: – How fast marketing/media strategies change – How much new data arrives – How frequently budget decisions are made However, the cadence is often decided by something much simpler – Budget availability Once the model build is priced, the next natural question is –