Why Google Analytics Doesn t Work for E-Commerce

Why Google Analytics Doesn t Work for E-Commerce

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. 2

1. Google Analytics lacks tracking accuracy. Tracking with Google Analytics costs manual resources and results in data loss. 3 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. Loss of data 30% 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. 3

1. Google Analytics lacks tracking accuracy. Google Analytics and its functionalities get increasingly blocked. 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 4

1. Google Analytics lacks tracking accuracy. 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. 5

2. Google Analytics pursues its own interests. Google only automates with its own advertising tools. 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. 6

2. Google Analytics pursues its own interests. Google favours its own technology. 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. 7

3. Google Analytics reports your data inaccurately. Your user-defined reports are based on sampled data. 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 8

4. There is no consistency across Google Analytics reports. Metrics are defined differently across reports. 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. Time delay Apart from the real-time section of Google Analytics for current visitors 19, 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. 9

5. Google Analytics cannot provide the attribution modelling flexibility that marketers need. The attribution models on Google Analytics do not reflect the customers reality. 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. 10

6. Your data belongs to Google. Your business data can be used and leveraged by Google and authorities outside Europe. 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 world 22, Google is headquartered in the US and uses the collected data for internal optimization purposes 23. Also, as the data does not belong to the account owner 24, 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. 11

Bottom line 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. 12

Bottom line Google Analytics (basic) Ingenious Enterprise Specialty Web analytics Business analytics 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 13

References 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. 14

References 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 15

References 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 16

References 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 Copyright 2015 Ingenious Technologies. All rights reserved. Ingenious Technologies AG Französische Straße 48 10117 Berlin T +49 30 577 02 60 00 F +49 30 577 02 60 99 www.ingenioustechnologies.com info@ingenioustechnologies.com 17