DIY Marketing Mix Modeling

Introduction

In-housing your marketing mix modeling (MMM) doesn’t have to be complicated. Until recently, most brands and agencies had to rely on external consultants or third-party platforms to understand how their marketing efforts drive results. But as MMM technology has advanced, it’s become more accessible. Today, a lot of the data crunching, modeling, and testing that used to take weeks can be done in-house—and faster. That’s the real advantage of tools like Alviss AI. They don’t just let you analyze your marketing mix; they give you the flexibility to do it yourself.

The steps to set up your own MMM model are simpler than you might think, especially if you’ve got a handle on your data. Here’s a quick guide to get started using Alviss AI.

1. Start with Good Data

The first step to setting up a marketing mix model is having the right data. For MMM to work well, you need historical data on your marketing efforts, ideally from different channels. This includes media spend, impressions, clicks, sales numbers, or any other key metric you track to understand performance.

Your data doesn’t have to be flawless, but it does need to be consistent. Make sure you have similar metrics over similar time frames across different channels. If TV ads are tracked monthly and digital ads are tracked weekly, adjust so that you’re working with matching intervals. If the data isn’t aligned, your model will get messy.

2. Upload Your Data to Alviss AI

Alviss AI was built to simplify the data upload process. Once you’ve collected and organized your data, the platform guides you through the upload step. You can either drag and drop files or import data from integrated sources.

During this step, Alviss AI will help you format the data so it fits with the model structure. That’s especially useful if you’re working with mixed datasets that cover different channels. And once your data is uploaded, Alviss AI immediately starts crunching numbers, cleaning outliers, and aligning variables.

3. Choose Your Model Parameters

This is where things get interesting. Traditionally, marketers have had to rely on complex statistical expertise to tune their models. With Alviss AI, the platform helps set your model parameters based on the data you’ve provided.

Alviss AI uses Bayesian modeling, which is great for marketing data because it adapts as new data comes in. You start by choosing the main parameters: your primary KPIs, the weight of each channel, and the budget you’ve allocated to them. Bayesian modeling lets you easily run scenarios to see how different variables—like seasonal changes or special promotions—affect your results.

4. Test and Simulate

After setting your parameters, Alviss AI can show you simulations of different marketing mixes. This is where the platform’s Bayesian approach really shines. You can adjust budget allocations and immediately see the effect of these changes on your overall goals. Instead of waiting for a consultant’s report to come back, you can test ideas on the spot.

Want to see what happens if you put more budget into social media? Or what about cutting back on TV to see if it impacts sales? Running these simulations lets you test assumptions before you commit any real spend.

5. Analyze and Refine

Once you’ve simulated different mixes, you’ll have a clearer picture of which channels are contributing the most to your KPIs. Alviss AI provides a breakdown of results, showing how each channel affects your outcome and how changes in budget influence performance.

At this point, you might see things you didn’t expect. Maybe a channel you’ve been relying on is actually underperforming. Or maybe a smaller channel, like influencer marketing, is giving a much higher return on investment than you’d realized. The insights from this analysis let you refine your strategy with data you understand—because you generated it.

6. Implement, Track, Repeat

Marketing mix modeling isn’t a “set it and forget it” tool. Markets change, competitors adapt, and your strategies should too. One of the strengths of Alviss AI is that it allows you to continually track and update your model as new data comes in. You can keep refining your parameters, simulating new scenarios, and adjusting your marketing mix as needed.

The more you use it, the more intuitive your modeling becomes. Instead of being locked into quarterly reports or waiting for insights from outside, you can be agile with your budget. You can act on trends as they happen.

Getting Started with Your Own MMM

Running your own marketing mix model in-house gives you more control over your data, budget, and insights. It also means you don’t have to rely on generic models or wait weeks for results. With tools like Alviss AI, brands and agencies can get more from their MMM by bringing it in-house.

So, start with good data, set up your parameters, and experiment. Once you’ve run a few scenarios and seen what’s possible, you’ll wonder how you ever trusted your budget to outsourced MMM in the first place.

This post is part of a 6 part series called “Mastering Marketing Effectiveness with In-Housed MMM”. The posts are outlined below.