Introduction to TV Attribution in Google Analytics Attribution 360

The following article is an excerpt from my best selling book: Attribution Modelling in Google Analytics and Beyond which I am sharing it here for the first time, to benefit the wider audience:

As such, a traditional MMM model is not suitable for carrying out digital marketing mix modelling aka attribution modelling.

I have added more information in this article so that it benefit even my book readers.

Introduction to TV Attribution Modelling

TV attribution modelling is the process of understanding the impact of:

  • TV ad network(s)
  • TV program(s) and
  • TV ad airing slot(s)

on your: website traffic, sales and other online users activities.

TV attribution is carried out to understand the role of TV in conversion paths.

TV attribution is carried out to determine the most effective: TV ad network(s), TV program(s) and TV ad airing slot(s) for investment in a particular point in time.

By using TV attribution you can get answer to questions like:

# Which TV ad network (e.g. CNN, MSNBC) generated maximum user engagement and sales on my website?

# How do the various TV ad networks perform relative to each other?

# Which TV ad networks are worth the reinvestment and which are not?

# Which TV program(s) are worth the reinvestment?

# Which TV ad airing slot work the best for my website sales?

# What time of the day and what day of the week work best for driving online sales?

# What type of online response I got from my TV ads? This response can be in the form of TV driven branded searches, TV driven website traffic, TV driven conversions and sales.

# What role did TV play in the conversion path? Is it helping more in assisting online conversions or directly completing online conversions?

# How does TV work with digital channels to create conversions and sales?

# How can I improve my TV ad campaigns to generate more online sales?

# Is TV advertising worth the investment or should I reinvest in other marketing channels?

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Introduction to TV Attribution Model

TV attribution model is an algorithmic attribution model which uses machine learning and statistical modelling for assigning conversion credit to various marketing touch points.

If you are a business which advertises its products or services on TV and you want to measure the impact of TV advertising on:

  • Online branded search volume.
  • Website traffic.
  • Online conversions.
  • Online sales.
  • Mobile app installs
  • Online customer’s behavior and activities.

You would need to use a TV attribution model.

Why You Need a Dedicated TV Attribution Solution

TV ads drive website traffic and sales.

If you monitor your GA real time reports during and after a TV ad, you are likely to see a huge uplift in website traffic and sales.

But there is no easy way to prove that the uplift is because of the TV ad and not because of some other marketing activity.

If you are running several TV ads on various ad networks then it becomes even more difficult to understand the impact of particular ad network, TV program and ad slot on website traffic and sales.

Here TV attribution model tool comes handy.

Through TV attribution model tool you can correlate TV ad airing with your website traffic, sales and other online users’ activities in real time.

This attribution model is not something which you can create in standard Google Analytics.

It is beyond its capabilities.

Also it is technically extremely difficult and expensive to create and maintain such an attribution model on your own (in-house) unless you have got a team of data scientists and do not mind spending $100k or more.

You would be better off using the services of a third party which specialises in TV attribution modelling.

Once such third party is Google.

Introduction to TV Attribution from Google Attribution 360

You can access ‘Attribution 360’ from your GA 360 Suite:

Google has got a competitive advantage over other companies which provide TV attribution solutions.

This competitive advantage is the power to leverage its enormous search data and Google products (Google Analytics, Google AdWords, DoubleClick bid manager etc.) for TV attribution.

Google Attribution 360 provides a TV attribution model tool with the aim to provide a detailed insight into the relationship between TV ad airings and customer online activities.

It uses machine learning and statistical modelling for TV attribution.

Watch this short video on ‘Attribution 360 TV attribution’:

Through Attribution 360 you can:

#1 Integrate your TV airing data with your digital data.

#2 Understand TV to online customer behavior, minute by minute, in real time.

#3 Carry out multi-screen analysis (see people searching for your brand on mobile phones, tablets or desktops after watching your TV ad).

#4 Measure TV ad responses by device and activity type. For example, see how many people are searching online for your brand vs. visiting your website directly after watching your TV ad.

Following is an hour long webinar on ‘TV attribution’ which is also worth watching:

Other Articles on Attribution Modelling in Google Analytics

  1. Touch Point Analysis in Google Analytics Attribution Modelling
  2. 8 Google Analytics Conversions Segments You Must Use
  3. Default and Custom Attribution Models in Google Analytics
  4. Attribution Model Comparison Tool in Google Analytics
  5. Which Attribution Model to use in Google Analytics?
  6. How to create Custom Attribution Model in Google Analytics

  1. How to do ROI Analysis in Google Analytics
  2. Data-Driven Attribution Model Explorer in Google Analytics
  3. Guide to Data Driven Attribution Model in Google Analytics
  4. Conversion Credit distribution for Attribution Models in Google Analytics
  5. You are doing Google Analytics all wrong. Here is why

  1. Marketing Mix Modelling or Attribution Modelling. Which one is for you?
  2. Introduction to Nonline Analytics – True Multi Channel Analytics
  3. How to set up Data driven attribution model in Google Analytics
  4. How to valuate Display Advertising through Attribution Modelling
  5. Understanding Shopping Carts for Analytics and Conversion Optimization

  1. View-through conversion tracking in Google Analytics
  2. Understanding Missing Touch Points in Attribution Modelling
  3. Guide to Offline Conversion Tracking in Google Analytics
  4. How to explain attribution modelling to your clients
  5. 6 Keys to Digital Success in Attribution Modelling

  1. How to use ZMOT to increase Conversions and Sales exponentially
  2. How to Measure and Improve the Quality of SEO Traffic through Google Analytics
  3. How to analyse and report the true value of your SEO Campaign
  4. How to allocate Budgets in Multi Channel Marketing
  5. What You Should Know about Historical Data in Web Analytics

  1. Google Analytics Not Provided Keywords and how to unlock and analyze them
  2. Selecting the Best Attribution Model for Inbound Marketing
  3. Google Analytics Attribution Modelling – Complete Guide
  4. Cross Device Reports in Google Analytics via Google Signals

Learn about the Google Analytics Usage Trends Tool

The Google Analytics usage trend is a new tool which is used to visualise trends in your Google Analytics data and to perform trend analysis.


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Attribution modelling is the process of determining the most effective marketing channels for investment. This book has been written to help you implement attribution modelling. It will teach you how to leverage the knowledge of attribution modelling in order to allocate marketing budget and understand buying behaviour.

Himanshu Sharma

Certified web analyst and founder of OptimizeSmart.com

My name is Himanshu Sharma and I help businesses find and fix their Google Analytics and conversion issues. If you have any questions or comments please contact me.

  • Over eleven years' experience in SEO, PPC and web analytics
  • Google Analytics certified
  • Google AdWords certified
  • Nominated for Digital Analytics Association Award for Excellence
  • Bachelors degree in Internet Science
  • Founder of OptimizeSmart.com and EventEducation.com

I am also the author of three books:

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