Marketing Intelligence basics: Marketing Channel Mix

In the last 30 days I met 3 CMOs and their Marketing Teams with the same problem: nobody had a decent Marketing Channel Mix view.

Creating a Marketing Channel Mix view it has always been a marketer's nightmare.

In the last years due to privacy policies it became even worse.

A Marketing Mix view is the first step towards some significant form of marketing accounting and controlling. It unlocks clarity, strategy, efficiency in ongoing budgeting and performance optimization.

Here's what is it, what are the problems and the possible solutions.

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It is a view showing your marketing channels in basic terms like spend, results, efficiency. Below a simple example in terms of marketing channel classification and in terms of KPI monitored.

You can assume you can get this 10x more detailed on both marketing classification and KPI dimensions that are useful to monitor, plus all the variations items (WoW, YoY, actual vs target, absolute vs percentage variations, etc.).

It's generally very useful to look at this data on various occasions (end of the week, end of the month, annual results) as well as daily if you deal with lots of budget and pressure.

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1. you need to pull spend from different platforms and other sources too

2. you need to grab traffic data, classify it, attribute results (e.g. orders)

3. you need different timeframes

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4. as you use it you tend to see that it's very useful, you start craving to add more details on marketing channels (campaigns, audience levels). The more the data and splits you need, the more time-consuming it becomes to maintain it

5. overtime you start to feel the need to slice and dice the data by custom timeframes

6. 3rd party web analytics data is s**t because it lacks 30%+ of the data due to cookies and privacy policy acceptance

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A) Cheap and manual

Pull a source/medium custom report in excel, create a custom marketing channel classification full of conditions like "if traffic is X then marketing channel is Y". Pivot the data to aggregate it.

Assume this attribution is fine, assume its traffic and orders data is a reliable representation of the total which you then interpole to get to the right total of traffic and orders.

Repeat for every time you need it (every month, every week, every day).

B) Tools and patchwork

You decide to apply more conscious attribution, automatize marketing channel classifications, automatize pulling data in one place.

For this you start buying tools for both marketing data (e.g. Funnel.io, Hightouch, TripleWhale, Mixpanel, Amplitude, Google Analytics 360...) and data pulling (Zapier, Stitch, Fivetran...). Perhaps you add even data visualization tools (Power BI, Looker..) and data storage (AWS, GCP, Azure).

C) Horizontal taskforce

You decide to be more conscious on the technology decisions you make because you see they produce value, but they produce also constraints that become hard and expensive to change.

You decide to be more conscious on how you get privacy acceptance data, how you enrich it with 1st party data to get more reliable data, you want to model your own attribution and your own personalized marketing channel classification, create one or more data models according to the user case.

Most of all you want something that is reliable and automatic.

In this case the best is to create a multi-competent taskforce with marketers, data engineers and BI experts that are tech-agnostic. You don't want a vendor pushing down your throat one tool or one tech stack. Instead, you want to understand both technology and features tradeoff, decide your stack, implement you tailored Marketing Intelligence by starting with having a Marketing Mix view.