I have dealt with hundreds of Google Analytics accounts in my career and I have seen a lot of issues ranging from incorrect tracking code, selecting the wrong KPIs to analysing data without using custom reports and advanced segments.

All of these issues prompted me to write the article: Common Universal Analytics Mistakes that Kill your Analysis, Reporting and Conversions.

But these articles don’t really solve the biggest problem of all in web analytics:

“Misinterpretation of analytics data”

Everyone seems to be making the mistake of crediting conversions and ecommerce transactions to the wrong marketing channel and that too over and over again.

Many marketers can’t help themselves because they believe that the reports provided by Google Analytics (and other web analytics software) are ‘what you see is what you get’ when they are actually ‘what you interpret is what you get’. 

Even today the majority of businesses and marketers will give the credit for conversions to the last campaign, ad or search that referred the visitor just before they completed a goal conversion (like making a purchase).

This has resulted in marketers making wrong business decisions and losing money.

All of the data you see in Google Analytics reports today lies to you unless you know exactly how to interpret it correctly.

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Let us consider three different scenarios:

Scenario 1:

The majority of marketers looking at this standard ‘All Traffic’ report in Google Analytics for the last three months will draw the following conclusions:

# Organic traffic is playing a secondary role to direct traffic.

# The majority of traffic and revenue are coming through direct traffic.

# We need to speed up content development and link building to increase organic traffic to the website.

Scenario 2:

One look at this monthly PPC report and many of you will declare this whole campaign a total failure. Look at the first campaign, just one conversion in the whole month and the cost per conversion is a whopping $531. You must be kidding, right?

Scenario 3:

This report shows that the majority of traffic and sales have come from your brand name. But do you really think your brand name generated revenue of more than $241k?

Welcome to the real world

Let us analyze these three different scenarios once again but this time in the real world.

Scenario 1:

The truth about direct traffic

All untagged or improperly tagged marketing campaigns from display ads to emails could be treated as direct traffic by Google.

Whenever a referrer is not passed, the traffic is treated as direct traffic by Google.

1. Mobile applications don’t send a referrer.
2. Word/PDF documents don’t send a referrer.
3. ‘302 redirects’ sometimes cause the referrer to be dropped.
4. Sometimes browsers don’t pass the referrer.
5. During an HTTP to HTTPS redirect (or vice versa) the referrer is not passed because of security reasons.

All such traffic is treated as direct traffic by Google.

So on the surface, it looks like 618,199 visits/sessions were direct, but it may actually be only 25,000 sessions that were from direct traffic and the rest were from display ads, email, organic,  social media and applications/campaigns in which the referrers were not passed.

But this analysis does not end here, because you are still not looking at the complete picture.

Here is the complete picture:

Visitors do not always access your website directly and then make a purchase straight away.

They are generally exposed to multiple acquisition/marketing channels (like display ads, social media, paid search, organic search, referral websites, email, etc) before they access your website directly and make a purchase.

So if you are unaware of the role played by prior marketing channels, you will credit conversions and e-commerce transactions to the wrong marketing channels, like in the present case to direct traffic.

If you look at the chart above, organic search is playing a key role in driving direct traffic to the website which eventually resulted in conversions and ecommerce transactions.

To get this type of understanding you need to understand and implement attribution modelling.

The conclusion that organic traffic is playing a secondary role to direct traffic is incorrect.

Related Article: Complete Guide to Direct Traffic in Google Analytics

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Scenario 2:

Visitors do not always click on your paid search ads and then make a purchase straight away. They are generally exposed to multiple acquisition/marketing channels before they click on your ad and make a purchase.

Sometimes visitors may click on your ads but make a purchase through a different acquisition channel or medium. For example, a person may click on your paid search ad through their laptop at work. Then later make a purchase via their home desktop PC through a branded organic keyword.

Sometimes your paid search ads play a bigger role in assisting conversions than directly completing conversions.

The ‘conversions’ and ‘cost per conversions’ (cost/conv) reported by Google Adwords in scenario 2 above, are all based on the last adwords touch attribution model (people click on the ad and buy) and hence provide poor analytical insight.

When I paused these campaigns, I saw a decline in revenue. These campaigns are in fact profitable and their assisted conversion value is also very high.

Related Article: Google Adwords Analytics – Complete Guide

Scenario 3:

This scenario is not any different from scenario 1 and scenario 2. Here too you don’t see the complete picture.

Visitors do not always search for your brand name and then make a purchase straight away.

They generally start their search with a non branded and generic search term then they refine their search queries as they get a better understanding of what exactly they are looking for.

Sometimes they make a purchase right after making a search but often they come back later to your site via a branded search term.

Since a website or brand name is easiest to remember among all branded search terms, it often ends up being attributed a lot of conversions and transactions by Google Analytics.

A user journey is complicated

Users do not always use the navigation path you expect them to follow.

There is no guarantee that a person who lands on the website via a PPC landing page will not navigate to the home page before making a purchase.

Users switch between marketing channels

A user may visit your website the first time via a paid search ad but can return to your website via branded organic search or directly to make a purchase. So you may think that your paid search ad is not working but in reality, it is.

Users do not always use the same device when they return to a website.

They may browse your product page via a laptop at work and then browse the rest of the website via a tablet at home and may buy your product the next day via a mobile at work.

For Google Analytics the person who browsed the product page via a laptop at work is different from the person who browsed the rest of the website via a tablet at home and also different from the person who bought the product via a mobile the next day, as cookie information is not shared across devices.

In such case here is how Google Analytics will record user activities:

User 1 browsed the product page via a laptop but didn’t make a purchase. So the AdWords ad will not get credit for the conversion.

User 2 browsed a lot of pages on the website but didn’t make a purchase.

User 3 came to the website directly via a mobile device and made a purchase.

So the online user journey is complicated.

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Marketing channels affect each others performance

Because of multi-channel and multi-device attribution, any improvement or decline in the performance of one marketing channel impacts the performance of other marketing channels. So if you suddenly switch off all of your PPC campaigns, you are most likely to see a decline in direct traffic.

Organic traffic can impact the CTR of PPC ads, as when people see double listing (both paid and organic listing) they are more likely to click on an ad. As such, a decline in organic traffic can reduce the CTR of PPC campaigns.

Similarly, people who are exposed to a brand for the first time via paid search may return to the website via a branded organic search or directly. So any decline in PPC traffic may negatively impact branded organic search traffic or direct traffic.

In a multi-channel, multi-device world, different marketing channels and devices work together to create user experience and conversion. We don’t optimize just for SEO or just for PPC. We optimize for users regardless of the channel or device they come from.

Takeaways

1.  Web analytics reports are not ‘what you see is what you get’. They are ‘what you interpret is what you get’.
2. Direct traffic is polluted so find ways to clean it. The first step should be to correctly tag all of your campaign URLs. Use Google Analytics URL Builder.
3. Visitors do not always access your website directly and then make a purchase straight away.
4. Visitors do not always click on your paid search ads and then make a purchase straight away.
5. Visitors do not always search for your brand name and then make a purchase straight away.
6. Understand the role that various website referrals, social media, display, email, paid/organic search, etc played prior to conversions via multi-channel funnel reports before you discard or label any marketing channel as ineffective or you over-invest in any particular channel.
7. Understand how different acquisition channels work together to create conversions and transactions.
8. No one acquisition channel is solely responsible for sales in the world of multi-channel marketing. 
9. Do not overestimate or underestimate the impact of other marketing channels.
10. Understand that when you change the budget of one marketing channel it will have an impact on the performance of other marketing channels. Nothing is black and white in the world of analytics.

You can learn more about budget allocation from this article: How to allocate Budgets in Multi-Channel Marketing

If you wish to learn more about attribution modelling and attributing conversions and ecommerce transactions to the right marketing channel then read this article: Google Analytics Attribution Modeling – Beginners Guide

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
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25. Touchpoint Analysis in Google Analytics Attribution Modelling
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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