Understanding Missing Touchpoints in Attribution Modelling

In the context of attribution modelling in Google Analytics and Google Ads, a touchpoint is an exposure to a marketing channel.

There are two types of touchpoints:

  1. Online touchpoint – It is an exposure to an online marketing channel like paid search, organic search, social media, email, display, etc.
  2. Offline touchpoint – It is an exposure to an offline marketing channel like TV, Radio, outdoor advertising, point of purchase display, etc.

Note: Touchpoint 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 Google Ads, 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 Google Ads attribution modelling is based on only ‘known’ touchpoints

Google identifies 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 the Chrome browser on a desktop PC and then later converted via the 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 the Chrome browser on a desktop PC but didn’t make a purchase.
  • The second person visited your website via the ‘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’ behavior on your website. So your attribution modelling will be based only on known touchpoints.

Another example: 

If a person saw an ad on TV and then later converted via a 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. Again, your attribution modelling will be based only on known touchpoints.

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

So if you are heavily involved in 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 Ads, record and report attribution for only online touchpoints.

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 a paid search ad on a desktop PC, then both Google Analytics and Adwords will give all the credit for conversions to the 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.

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, which leads to conversions.

Needless to say, if you are heavily involved in 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.

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

For example:

Google Adwords records 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. 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 Ads, 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 a mobile device. Whereas Google Adwords will not record and report this conversion as it has not resulted from a click on an Adwords ad.

Both Adwords and GA completely fail to report the role, the desktop ad played in assisting conversions. So you may conclude that your desktop Adwords ads are not working but in reality, they are.

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 in 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 the 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 touchpoints in conversion paths

Look at Google Analytics multi-channel funnel reports in an unfiltered view. View filters can omit certain touchpoints in users’ conversion paths and can thus provide a 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 touchpoints and fixing attribution issues

In order to minimize the number of missing touchpoints in your conversion path and to get a 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 bottom line impacting metrics like revenue, cost, gross profit, etc

Without proper data integration, you will always get a 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

  1. How to analyse and report the true value of your SEO Campaign
  2. How to valuate Display Advertising through Attribution Modelling
  3. Understanding Shopping Carts for Analytics and Conversion Optimization
  4. 6 Keys to Digital Success in Attribution Modelling
  5. Google Analytics Attribution Modeling Tutorial
  6. How to Measure and Improve the Quality of SEO Traffic through Google Analytics
  7. How to explain attribution modelling to your clients
  8. Default and Custom Attribution Models in Google Analytics
  9. Understanding Missing Touchpoints in Attribution Modelling
  10. What You Should Know about Historical Data in Web Analytics
  11. Model Comparison Report Explained in Google Analytics Attribution
  12. Data-Driven Attribution Model in Google Analytics – Tutorial
  13. Conversion Lag Report Explained in Google Analytics Attribution
  14. Selecting the Best Attribution Model for Inbound Marketing
  15. How to do ROI Analysis in Google Analytics
  16. Conversion Credit Models Guide – Google Analytics Attribution
  17. Introduction to Nonline Analytics – True Multi Channel Analytics
  18. Conversion Types Explained in Google Analytics Attribution
  19. Attribution Channels Explained in Google Analytics Attribution
  20. Differences Between Google Attribution & Multi-Channel Funnel Reports
  21. Introduction to TV Attribution in Google Analytics Attribution 360
  22. Conversion Credit Distribution for Attribution Models in Google Analytics
  23. Conversion Paths Report Explained in Google Analytics Attribution
  24. Attribution Model Comparison Tool in Google Analytics
  25. Touchpoint Analysis in Google Analytics Attribution Modelling
  26. Attributed Conversions & Attributed Revenue Explained in Google Attribution
  27. Which Attribution Model to use in Google Analytics?
  28. Google Attribution Access and User Permissions – Tutorial
  29. Conversion Path Length Report Explained in Google Analytics Attribution
  30. How to set up a data-driven attribution model in Google Analytics
  31. View-Through Conversion Tracking in Google Analytics
  32. Offline Conversion Tracking in Google Analytics – Tutorial
  33. How to Create Custom Attribution Model in Google Analytics
  34. 8 Google Analytics Conversions Segments You Must Use
  35. You are doing Google Analytics all wrong. Here is why
  36. How to Use ZMOT to Increase Conversions and Sales Exponentially
  37. Connected Properties Explained in Google Analytics Attribution
  38. Marketing Mix Modelling or Attribution Modelling. Which one is for you?
  39. How is attribution modelling helpful for ecommerce and non-ecommerce websites?
  40. Conversion Time & Interaction Time Explained in Google Analytics Attribution
  41. How to Allocate Budgets in Multi Channel Marketing
  42. How Does Attribution Work?
  43. Data-Driven Attribution Model Explorer in Google Analytics
  44. Introduction to Attribution Beta – Attribution Project in Google Analytics

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Himanshu Sharma

Digital Marketing Consultant and Founder of Optimizesmart.com

Himanshu helps business owners and marketing professionals in generating more sales and ROI by fixing their website tracking issues, helping them understand their true customers' purchase journey and helping them determine the most effective marketing channels for investment.

He has over 12 years of experience in digital analytics and digital marketing.

He was nominated for the Digital Analytics Association's Awards for Excellence. The Digital Analytics Association is a world-renowned not-for-profit association that helps organisations overcome the challenges of data acquisition and application.

He is the author of four best-selling books on analytics and conversion optimization:

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