Web analytics has been around in some format for over twenty years, with Google Analytics first making an appearance in 2005.
User’s online behaviours have changed an awful lot since then; users now have access to the internet on multiple devices and as such, the customer journey is much more complex. In the mid 00’s online behaviours were not as complicated due to less available internet access, meaning that browsing, purchasing and form submission were often all undertaken on the same desktop computer, in a more purposeful fixed context. This implications of this meant that tracking the user path was much more straight forward; analytics and marketing measurement tech could place a cookie on a user’s browser, which meant that marketers could easily see which touchpoints led to a conversion (or a non-conversion) and make decisions based on this information.
The introduction of mobiles and tablets with internet access has given users ‘always on’ internet access, and the impact has been substantial. User journeys have become much more proliferated; for example someone might start their journey on a desktop, move down the funnel on their phone, and convert on a tablet – or any combination of these devices. These interactions are all tracked, however the data collection technology (cookies) that analytics platforms use was designed in an era where users often performed all of their internet interactions on a single browser on a single device. By default, this technology cannot stitch together user interactions across devices, making it harder for marketers to see the full journey.
Then came Intelligent Tracking Prevention, or ITP, a privacy feature used by more recent versions of Safari to block third party cookies, reduce the persistence of first party cookies and prevent local data storage in website browsers, dramatically limiting a web analytics ability to link user interactions together, as well as reducing the ability of ad platforms to track users across many websites. ITP can influence how traffic and conversions are attributed within analytics platforms – as they are no longer able to stitch together all interactions from a given user. If seven days or more passes between interactions on the website (from the same browser), returning users may be recorded as new users.
The introduction of data regulations such as GDPR and CCPA have further decreased our ability to track users across the web. Privacy laws require users to give explicit consent to having their personal data stored and tracked, including online identifiers (such as cookies and User ID) and location. Now, rather than requiring users to manually opt out of having their data tracked, websites must require users to opt in to every aspect of data storage and processing, which means sites using multiple cookies need to gain consent from each user. With privacy concerns growing over the last decade, more and more users are choosing not to opt in to having their data tracked when asked – which means we cannot place any cookies on their browser, losing both the touchpoints from their journeys, and their conversions (or lack of conversion).
Being able to see the full customer journey is key to understanding how different channels and campaigns contribute to conversions.
When parts of the customer journey are taken away, we cannot see the full picture in how a user came to convert, or alternatively what prevented someone from converting. Without this data we cannot make informed decisions about where to put budget, how to optimize channels, and how to successfully engage with users. It becomes more difficult to know what activity is working well and what activity is not, leading to poor performance and inefficient use of budget.
Privacy requirements have evolved, so it is imperative that marketers adapt how they track and measure data, ensuring that regulations are adhered to and the user privacy is respected while collecting as much reliable data as possible. Rather than finding temporary workarounds, the focus now needs to be on preserving what data we can, so that we can piece together as much of the customer journey as possible.
There are currently three Google solutions which can help to preserve data:
If you would rather listen than read, our Founder, Ian Harris, is joined by our in-house experts to discuss this topic in our latest podcast episode.
Late last year, Google announced Consent Mode, a feature currently in beta which helps advertisers to adjust how they track and use data depending on what users have consented to.
For users who give consent, their cookie data will be tracked and stored as standard. For users who do not give explicit consent, consent mode allows marketers to still measure these conversions in analytics or Google Ads without using cookies or storing user data for advertising purposes, albeit at an aggregate level. This method provides anonymous cookieless pings to fill in the gaps and see conversions from your campaigns– according to Google, conversion modeling via consent mode recovers more than 70% of ad click to conversion journeys which would have otherwise been lost.
Consent mode is implemented via Google Tag Manager and can be used across Google Ads, Floodlight and Google Analytics, although this list may expand as the feature comes out of beta.
One thing to note with consent mode is that while the modeled data is reported in some analytics reports, we are unable to pull out the raw data from these conversions from analytics in raw hit event level exports (for example, to be used for data projects and attribution models). However, you can use the data you do have to train machine learning models to fill in the gaps if you do want to carry out bespoke projects.
When cookies aren’t available, enhanced conversions can help to fill in the gaps with what happens after a user engages with an ad. Enhanced conversions use first-party data from users who have consented to model how non-consenting users behave after clicking through an ad, allowing advertisers to measure the impact of their campaigns even in the absence of cookie consent.
Last year, Google announced the launch of their completely new analytics platform, Google Analytics 4 (previously App + Web).
Among other benefits, one of the key reasons to create a GA4 property is that it offers a much more robust solution for connecting the dots of user journeys. It does this by having multiple ways of understanding the user. Primarily GA4 will use USERID, this is a specific ID that is output by the website / app upon authentication (ie login). The second user identifier fall back is DeviceID, which is either the GA clientid from the first party cookie or an app instance ID from a mobile app. The third method to deduplicate users where necessary is ‘Google signals’.
It’s worth noting that these user definition methods are combined into a single view in GA4, whereas previously in universal analytics clientid and USERID had to be setup in different views.
Google Signals has been around for some time but its integration with GA4 offers a greater ability to identify users who have visited your site or app across different devices and time periods.
While Google Signals is not as strong a reporting identity as the DeviceID or User ID, being able to track Google Signals can help to restore in the holes in stitching together journeys from more users.
Preserving your first-party analytics data through the above methods will help to retain as much information about your customers and the sale journey as possible, but it is important to enrich and analyze this data to build up a more in-depth and accurate view of what is going on.
Additional first party data from locations such as a CRM can enrich the view we have of customers. This can then be used as information to build specific audiences to activate in your marketing efforts.
The end of cookies and web tracking doesn’t just impact first-party data collection. Advertising platforms use third-party data collected by cookies to profile and measure users; without cookies in place, targeting becomes less efficient and measurement becomes less accurate.
We have previously touched on how ITP impacts paid media here. With Chrome soon to join the browsers blocking cookies completely, now is the time for advertisers to move to a first-party centric strategy. We will cover the actions you need to take now to futureproof your advertising strategy over the next few weeks.
This webinar is part of our wider B2B Playbook that is designed to help B2B businesses with all aspects of their digital marketing from leveraging data, acquiring more traffic, creating assets that resonate and succeeding internationally.
In the data section we’ve compiled useful insights on everything you’ll need to know, from capturing data to building advanced machine learning solutions using your first-party data.
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