Understanding Missing Touch Points in Attribution Modelling

In the context of attribution modelling in Google Analytics and adwords,

A touch point is an exposure to a marketing channel.

There are two types of touch points:

#1 Online touch point – It is an exposure to an online marketing channel like: paid search, organic search, social media, email, display etc.

#2 Offline touch point – It is an exposure to an offline marketing channel like: TV, Radio, outdoor advertising, point of purchase display etc.

Note: Touch point is known by the name of ‘interaction’ in GA multi-channel funnel reports and Adwords attribution reports.

You need to be aware of the following drawbacks and technical constraints involved in attribution modelling in Google Analytics and Adwords, before your interpret the attribution/multi channel funnel data and take business and marketing decisions based on such data:

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#1 Google Analytics and Adwords attribution modelling is based on only ‘known’ touch points

Google identify a person through his/her web browser and device in GA multi-channel funnel reports and Adwords attribution reports.

For example:

If a person visited your website via ‘chrome’ browser on a desktop PC and then later converted via ‘safari’ browser on an IPAD, then Google Analytics will report that they are actually two people who visited your website.

The first person visited your website via ‘chrome’ browser on a desktop PC but didn’t make a purchase.

The second person visited your website via ‘safari’ browser on an IPAD and made a purchase.

Clearly this is not true but that’s how you will be reported of the customers’ behaviour on your website.

So your attribution modelling will be based only on known touch points.

Another example

If a person saw an ad on TV and then later converted via paid search ad on a desktop PC, then Google Analytics will report that a person clicked on a paid search ad and made a purchase.

GA will completely ignore the role of the TV ad, prior to conversion.

So again your attribution modelling will be based only on known touch points.

So we can conclude that in certain situations, we can get distorted picture of conversion paths from our multi-channel funnel reports.

So if you are heavily involved into multi-channel and multi device marketing, both online and offline, your conversion path reports could be way off the mark.

#2 Both Google Analytics and Google Adwords, record and report attribution for only online touch points.

In other words, both Adwords and analytics, do not record and report attribution for non-digital marketing channels.

They show attribution only across ‘digital’ marketing channels.

Consequently offline users interactions, like via phone calls and in-store visits are not taken into account while determining which marketing channel should get credit for sales and conversions.

For example,

If a person saw an ad on TV and then later converted via paid search ad on a desktop PC, then both Google Analytics and Adwords, will give all the credit for conversions to paid search ad.

They completely fail to report the role of the TV ads, in assisting conversions.

So you may conclude that your TV ads are not working but in reality they are.

So you can get a distorted picture of conversion paths from your GA multi-channel funnel reports and Adwords attribution reports.

In the context of attribution modelling, a conversion path is the sequence of interactions (sessions, ad clicks, ad impressions) with digital marketing channels during the 1 to 90 days period, that lead to conversions.

Needless to say, if you are heavily involved into online and offline marketing, you can not 100% trust your attribution reports.

Note: Google Adwords can report on offline conversions (phone conversions, store visit conversions) but they are not part of its attribution reports.

#3 Both Google Analytics and Google Adwords, do not record and report attribution for ‘all’ digital marketing channels.

For example,

Google Adwords record only those users’ interactions in a conversion path which resulted from Google Search network ads and/or Google Shopping ads.

It does not record the users’ interactions in a conversion path which resulted from Google Display network ads or mobile apps.

So if a customer viewed one of your Google Display Network ad, couple of times and then later returned to your website by clicking one of your Google Search network ads, then both Google Analytics and Adwords, give all the credit for conversions to the search network ad in their attribution/multi channel funnel reports.

They completely fail to report the role, display network ad played in assisting conversions.

So you may conclude that your display ads are not working but in reality they are.

So you can get a distorted picture of conversion paths from your multi-channel funnel reports and Adwords attribution reports.

#4 Both Google Analytics and Google Adwords, do not record and report attribution across devices and browsers

In other words, both Adwords and analytics, record and report attribution for only one device and one browser (by default).

So if a customer clicked on your Google Adwords ad via ‘chrome’ browser on a desktop PC and then later returned to your website and made a purchase through organic search made via ‘safari’ browser on his IPhone, then Google Analytics will give all the credit for conversions to the organic search made via mobile device.

Whereas Google Adwords will not record and report this conversion as it is not resulted from a click on an adwords ad.

So both Adwords and GA completely fail to report the role, desktop ad played in assisting conversions.

So you may conclude that your desktop Adwords ads are not working but in reality they are.

So you can get a distorted picture of conversion paths from your multi-channel funnel reports and Adwords attribution reports.

Needless to say, if you are heavily involved into multi-device marketing (marketing across desktop, tablets and mobile devices), you can not 100% trust your attribution reports either in adwords or in analytics.

Note: Google Adwords can report on cross device and cross browser conversions but they are not part of its attribution reports.

#5 Adwords conversion paths in Google Analytics do not include impression interactions

In Google Analytics multi channel funnel reports, all the adwords conversion paths (keyword path, ad group path and campaign path) are made up of only ad clicks interactions.

Whereas in Google Adwords, the adwords conversion paths are made up of both ad clicks and ad impressions.

Thus Adwords conversion paths reported in Google Analytics multi channel funnel reports are less reliable than the Adwords conversion paths reported in Google Adwords report in terms of understanding the performance of your Adwords campaigns. 

Note: Through Google display network impression reporting, you can get display ad impression interactions in your conversion path report. But this a GA premium feature, which is not available to all.

#6 Filtered views omit certain touch points in conversion paths

Look at Google Analytics multi channel funnel reports in an unfiltered view.

View filters can omit certain touch points in users’ conversion path and can thus provide distorted conversion path.

For example if your filtered view, exclude social media traffic then you won’t see social interactions in the users’ conversion paths and thus will get muddy insight.

Data integration is the key to minimizing missing touch points and fixing attribution issues

In order to minimize the number of missing touch points in your conversion path and and to get holistic view of your marketing, you need to integrate as much data as possible from different data sources.

These data sources can be (but are not limited to):

  1. Google Analytics
  2. Google Adwords
  3. Google Webmaster tools
  4. Google Merchant Center
  5. Bing ads
  6. Kissmetrics
  7. Qualaroo
  8. Facebook Insight and other social analytics data
  9. Compete
  10. Survey Monkey
  11. Phone Calls data
  12. CRM data
  13. Point of Sale (POS) data
  14. Data from Customer Support
  15. Financial data and data from other departments.

Once you have integrated all the marketing and business data in one place, you can quickly track various aspects of your marketing campaigns, analyze the overall performance and above all take timely decisions.

Data integration can help you correlate all of your data with business bottomline impacting metrics like revenue, cost, gross profit etc

Without proper data integration, you will always get SILO view of your marketing campaigns.

You need to create a robust data integration system in order to carry out any meaningful analysis.

In fact if you are a big organization then it is completely pointless to collect and analyze big data without proper integration.

You have to invest in data integration technologies if you are really serious about carrying out attribution modelling.

Start by upgrading your Google Analytics account to Universal Analytics (if you still have not already) and then gradually move to custom built applications.

Universal Analytics (UA) provides many more ways to collect and integrate different type of data than Google Analytics (GA). Through UA you can integrate data across multiple devices and platforms. This is something which is not possible with GA.

Consequently UA provides better understanding of relationship between online and offline marketing channels that drive sales and conversions than GA.

Source: Difference between Google Analytics and Universal Analytics

Eventually you have to use customized applications because no single tool/software alone can minimize all of your data integration issues.

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

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  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
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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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