Why Google Analytics Doesn‘t Work

for E-Commerce

Customers – they are the core of e-commerce. Because their buying behaviour has

become so complex, businesses have placed importance in understanding customers’

navigation patterns, engagement opportunities and ultimately conversion trends, so that

marketing strategies can be optimized to best reach out to them.

In order to do this, many have chosen to use Google Analytics. To be exact, over 28 million

sites in total are presently using it.1 This has become attractive to marketers, especially

since Google Analytics is free of charge and has even released tools designed for

e-commerce over the past two years.2 But first, e-commerce players need to understand

how Google Analytics works with its data before making business decisions based on this.

Why Google Analytics Doesn‘t Work for E-Commerce

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In order to ensure that Google Analytics is actually tracking their digital business

landscape, marketers need to invest manual efforts in checking that JavaScript tags from

Google Analytics have been correctly implemented on every single webpage. Failure to

include these tags will result in no tracking, while adding them twice messes up the data.

On top of that, the tracking system from Google Analytics is cookie-based, while about

30% of users worldwide are actively deleting cookies regularly – and this trend is on the

rise. By deleting cookies, there will be huge data gaps on the customers’ decision-making

cycle. An e-commerce player that attracts 6 million visits weekly would be losing 1.8

million visits worth of information and any other collateral data linked to the user activity

around those visits, sales and leads. This means that marketers will lose the capability to

attribute the same percentage of sales to their media mix.

1. Google Analytics lacks tracking accuracy.

Tracking with Google Analytics costs manual resources and results in data loss.3

Loss of data

30%

3

When using Google Analytics, marketers are potentially losing large amounts of business

data because specific functionalities are getting blocked.

For instance, when marketers activate Google advertising functionalities within Google

Analytics such as AdWords remarketing, it occurs via the DoubleClick network and utilizes

3rd-party cookies.4 This poses a problem for marketers, as the number of users blocking

3rd-party cookies is constantly increasing. One such example is through the use of ad

blocking technologies, which is currently used by over 144 million users worldwide every

month.5 Specifically, many western countries including Germany have an ad-blocking rate

of about 20%.6 With such technologies, remarketing cookies could be disallowed to pass

through.7 What’s more: Safari blocks 3rd-party cookies by default.8 Since this browser is

the standard of Apple devices, businesses risk losing plenty of data behind their traffic.9

In addition, even if marketers are not using any advertising functionalities, ad blocking

technologies allow users to easily subscribe to additional lists which block Google

1. Google Analytics lacks tracking accuracy.

Google Analytics and its functionalities getincreasingly blocked.

4

Analytics fully.10 The same applies to the usage of Google Tag Manager. This tool has been

gaining tremendous ground in the past years, although it is also blocked by popular filters

within some of the current ad blockers. This is even more problematic for marketers, as

the tag manager is not only often used for Google Analytics tracking code but also for

important e-commerce setups, such as tracking switches and event tracking. Due to the

inaccurate data collection and tracking gaps, drawing conclusions from these data and

making business decisions become very difficult, thereby putting their e-commerce at

risk.

1. Google Analytics lacks tracking accuracy.

5

For paid advertisements, Google Analytics works best with its own tools, like Google

AdWords and Google Display Network.11 When marketers use the Google suite, reporting

functionalities are automated with the click of a button.

However, with any other ad network or even Google’s DoubleClick for Publishers (DFP),

user activities may not be generated on the reporting at all due to the lack of automation.12

In order to overcome this, marketers will need to fully configure and manually include

UTM parameters for each and every ad. For established e-commerce with thousands of

ads, this usually costs tons of resources and increases the room for error.

2. Google Analytics pursues its own interests.

Google only automates with its own advertising tools.

6

With the exception of the Multi-Channel Funnel, all standard reports of Google Analytics

favour Google search engine, including Google paid advertisements.

To illustrate this, let’s say a customer looks up a product using Google search and clicks

on a paid ad for an e-commerce at the top of the search results. He arrives at the site but

leaves shortly after. 20 minutes later, he visits this e-commerce again by typing in the URL.

While this click would normally be reported by other analytics platforms as a direct

type-in, Google Analytics assigns this traffic to the preceding channel. Therefore, reports

on Google Analytics would show that only one click was generated in total and it was made

via a paid ad.13

Alternatively, if a customer visits the e-commerce by clicking on the same ad from an

advertising partner outside of the Google environment twice, Google Analytics reports this

as one click. However, if the customer first clicks on the paid ad, and later the same paid

ad to visit the website again, Google Analytics will report that there were two clicks

generated, and both clicks were made via paid ads.

2. Google Analytics pursues its own interests.

Google favours its own technology.

7

While looking up web analytics is rather straightforward, analysing the performance of

e-commerce is not. In order to do so, marketers will often need to apply more advanced

dimensions to their data, and this is a challenge with Google Analytics.

If marketers use customized reports and specify a time range which contains more than

500k website visits, they will be presented with sampled data.14 In other words, due to

capacity limitations, Google is only working with a subset of the total data. Depending on

the total number of visits, reports can even be projected based on not more than 5% of

total data.

The main problem, however, is that these presented figures are not always accurate. To be

exact, a test has shown that when analysing e-commerce metrics in Google Analytics such

as transactions, revenue and e-commerce conversion rate, the accuracy of the reports

based on sampled data can deviate by up to 16%.15 Precise allocation of marketing spend

therefore becomes nearly impossible, as marketers are unable to gain the real

perspective of their e-commerce. The accuracy that comes with unsampled reports is only

available through the premium version of Google Analytics, which costs USD 150 000

annually.16

3. Google Analytics reports your data inaccurately.

Your user-defined reports are based on sampled data.

8

When using Google Analytics, most marketers also tend to rely on the Multi-Channel

Funnel report to supplement their analysis on how the marketing channels have attracted

traffic to the e-commerce websites. However, the standard report and the Multi-Channel

Funnel report are not based on identical calculation methods.17

For example, “direct traffic” is commonly known as any traffic arising from directly typing

in the website URL. This is also how Multi-Channel Funnel reports in Google Analytics

recognize them. However, with standard reports, any referral from a channel that is

unknown or untagged is classified as “direct traffic”.18 This means that marketers will be

unable to evaluate the true performance of marketing channels.

Apart from the real-time section of Google Analytics for current visitors19, all standard

reports have a time delay of about 8 hours, whereas the Multi-Channel Funnel reports

have a delay of up to 48 hours, depending on the size of the website.20 While marketers are

frequently confronted with day-to-day businesses like testing campaigns, Google

Analytics does not support any time-sensitive needs.

4. There is no consistency across Google Analytics reports.

Metrics are defined differently across reports.

9

Time delay

Gone are the days where last-click models made the most sense for businesses. Instead,

marketers are turning to attribution modelling to allocate contribution percentages to

specific channels according to their importance to the business.

However, via Google Analysis, marketers are restricted to common, rigid attribution

models in the market.21 These models are neither complex enough to accommodate

customer journeys, nor do they reflect the efforts marketers have made to increase brand

awareness prior to sale. The only customizable model available with Google Analytics is

the “position-based model”, which allows marketers to determine the percentages for the

first and last touch points.

Furthermore, the attribution models available on Google Analytics are only for reporting

purposes. Any actual payouts according to these attribution models need to be done on a

3rd-party platform. This not only costs extra resources, marketers are also unable to

accurately measure the value of their marketing efforts. In other words, businesses will

not get the real picture of budget spent versus revenue generated.

5. Google Analytics cannot provide the attribution modelling flexibility that marketers need.

The attribution models on Google Analytics do not reflect the customers‘ reality.

10

One of the key concerns of most businesses is the ownership of data. While the data is

supposed to be stored in Google’s data centres all around the world22, Google is

headquartered in the US and uses the collected data for internal optimization purposes23.

Also, as the data does not belong to the account owner24, it cannot be guaranteed that all

European data protection standards are taken into consideration and that the data will not

be misused, for example by authorities or other institutions outside Europe.

6. Your data belongs to Google.

Your business data can be used and leveraged by Google and authorities outside Europe.

11

Google Analytics may be a tool sufficient enough for web analytics but it is insufficient in

measuring the performance of e-commerce. In terms of web analytics, some

discrepancies on GA may be acceptable, as you can still use it to monitor the performance

of your website, and identify an increase in visitors to your website or their session

durations.

However, the danger is in using this tool to measure the performance of e-commerce.

Tracking gaps and inaccurate data affect e-commerce more gravely, as they could lead to

poor business decisions. In fact, implementing false business strategies may result in

substantially losing out on customers and thus sales for your e-commerce. Also, Google

Analytics is solely a tool with reporting functionalities. Any active management of online

marketing and e-commerce purposes is not supported.

As online business are increasingly confronted with the need to draw fast and reliable

conclusions from their data analytics, the right technology for e-commerce also needs be

able to manage and optimize of all business activities proactively. This guarantees

marketers to be most efficient in their industry, save costs and gain more business

opportunities.

Bottom line

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Bottom line

13

Specialty

Tracking of clicks

Tracking not only based on cookies

Automatic detection of untagged ads or traffic outside Google environment

No data limits within reports

Real-time data

Automatic deduplication

Flexible attribution modelling

Consistency across all reports

Data protection

Data ownership

Web analytics Business analytics

Google Analytics (basic) Ingenious Enterprise

1 BuiltWith. Websites using Google Analytics. Retrieved on 31st March 2015, from http://trends.builtwith.com/websitelist/Google-Analytics

2 Google Analytics (2014, May 28). Google Analytics Summit 2014: What’s Next And On The Horizon For Analytics. Retrieved on 1st April 2015, from http://analytics.blogspot.de/2014/05/google-analytics-summit-2014-whats-next.html

3 Google Analytics. Tracking Site Activity. Retrieved on 2nd April 2015, from https://developers.google.com/analytics/devguides/collection/gajs/asyncTracking

4 Google Analytics. Universal Analytics Web Tracking (analytics.js). Retrieved on 28th April 2015, from https://developers.google.com/analytics/devguides/collection/analyticsjs/cookie-usage

5 Pagefair and Adobe (2014). Adblocking goes mainstream. Retrieved on 11th March 2015, from http://downloads.pagefair.com/reports/adblocking_goes_mainstream_2014_report.pdf

6 Martin Hamann. Ad-Blocking, measured. Retrieved on 28th April 2015, from http://de.slideshare.net/arttoseo/clarity-ray-adblockreport

7 While some ad blocking technologies may allow these to pass through, an experiment conducted with the most popular ad blocking technologies, such as Adblock, has shown that the remarketing cookies will be blocked immediately.

References

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8 Apple. Safari 6/7 (Mavericks): Manage cookies and other website data. Retrieved on 28th April 2015, from https://support.apple.com/kb/PH17191?locale=en_US

9 While there have not been any official reports available, multiple tests were conducted by the Ingenious team between 28th April and 6th August 2015 and it was found that DoubleClick cookies were not allowed through by the default settings of Safari. However, these DoubleClick cookies might be allowed through when users have clicked on a Google ad before.

10 One of the most popular lists is the easy-privacy list. The actual filter settings are listed here: https://easylist-downloads.adblockplus.org/easyprivacy.txt

11 Google. Policy requirements for Google Analytics Advertising Features. Retrieved on 2nd April 2015, from https://support.google.com/analytics/answer/2700409?hl=en

12 Google. How a session is defined in Analytics. Retrieved on 2nd April 2015, from https://support.google.com/analytics/answer/2731565?hl=en

13 Google. How a session is defined in Analytics. Retrieved on 2nd April 2015, from https://support.google.com/analytics/answer/2731565?hl=en

14 Google. How sampling works. Retrieved on 2nd July 2015, from https://support.google.com/analytics/answer/2637192?hl=en

References

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15 Chase, Ryan (2013, February 21). Blast Analytics and Marketing. Can You Trust Your Google Analytics Data? Retrieved on 2nd April 2015, from http://www.blastam.com/blog/index.php/2013/02/can-you-trust-your-google-analytics-data

16 In the premium version of Google Analytics, data sampling occurs when there are more than 25 million visits within a customized report. Users will need to access the API to retrieve unsampled data. Google. Management API – Unsampled Reports Developer Guide. Retrieved on 2nd July 2015, from https://developers.google.com/analytics/devguides/config/mgmt/v3/mgmtUnsampledReports

17 Google Analytics. About Multi-Channel Funnels data. Retrieved on 2nd April 2015, from https://support.google.com/analytics/answer/1319312?hl=en

18 TagMan (2013). The Truth About Google Analytics Tracking.

19 Google Analytics. Real-time reports. Retrieved on 2nd April 2015, from https://support.google.com/analytics/answer/1638637?hl=en

20 Google Analytics. About Multi-Channel Funnels data. Retrieved on 2nd April 2015, from https://support.google.com/analytics/answer/1319312?hl=en

21 Google Analytics. Attribution modeling overview. Retrieved on 2nd April 2015, from https://support.google.com/analytics/answer/1662518?hl=en

References

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22 Google has data centers operating in the US, Latin America, Europe and Asia. http://www.google.com/about/datacenters/inside/locations/index.html

23 Google. Google Privacy Policy. Retrieved on 2nd July 2015, from https://www.google.com/intl/en/policies/privacy/

24 Google regularly gets hold of user data for internal optimization processes. Users need to personally uncheck the box under “Google product & services” from their “Account Settings”, in order to officially declare that they do not wish for Google to gain any access to their information.Google. Data sharing settings. Retrieved on 2nd July 2015, from https://support.google.com/analytics/answer/1011397

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References

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