This article covers the topic of real-time website personalization both from a strategic standpoint and from a technical standpoint, including some considerations for Google Optimize and Google Optimize 360.
Strategically speaking, let’s consider the underlying value proposition of providing personalized experiences and then move to a discussion of some of the ways you can accomplish this personalization from a technical standpoint.
Using user intent signals derived from online behaviors is the key to providing exceptional experiences that improve overall website performance by enhancing a user’s experience on your site. In the broadest sense, user intent can be categorized in two ways: declared intent and inferred intent. Let’s get into the weeds for a moment and take a look at each.
There is nothing wrong with inferring intent, and we should be paralyzed if we could not make sound decisions based on inferences from data. However, declared user intent is superior when it is available. One of the keys of really successful conversion funnels is helping users tell you what they want or need as part of the conversion process itself. Below are some simple examples of some types of businesses and what you might like to know about a user’s wants and needs as quickly as possible:
| Dating Sites | X looking for Y |
| Job Sites | Are you a job seeker? Are you a company looking to hire? |
| Car Sites | New or Used? Have a trade-in? |
These are simple kinds of questions companies are already asking on their websites either as soon as you enter the site or shortly thereafter, and it helps guide your experience on the site real-time and early in the process. They are based on declared intent, and so the personalizations made based on this data is more reliable in terms of supporting the user experience you provide.
Inferred intent refers to the uncovering of specific user behaviors, such as search terms, content consumed on your site, engagement metrics, and website interactions that index higher for specific outcomes: conversion goals, specific product purchases, specific customer needs. The intent is inferred because no one is telling you specifically what their intention is in these cases, but you can make reasonable, data-supported decisions with enough data points because the correlation between behavior and an outcome can be very strong.
On B2B sites, lead generation sites, and sites with longer sales cycle getting users to declare their intent may be a slightly more complex and step-wise process. This is why lead generation processes that feel more like a guided journey than a long, onerous form can be so effective. When users download a gated white paper or select options on your guided journeys that let you know what they need, these are the key moments to provide real-time personalization based on what you now know.
If I download a white paper about SAP Supply Chain Management (SCM) Software, this is a key moment to stop giving me default content and experiences on the website. You can’t be 100% certain at this point, but this is a good time to validate a hypothesis that I may be interested in supply chain management. Wouldn’t you agree? Show me some additional articles and other resources around your solutions related to supply chain management. Show me a case study or two supporting the features and benefits of your product and the improvements your customers have realized.
Next time I visit your website, why not update the main home page graphic and content block to reflect what I have already told you about my interests and needs?
Here are some other critical points where personalization is appropriate and potentially powerful
Technically speaking, any time you alter your site’s default content or experience flow based on inferred or declared intent from your user, you are doing web personalization. So, you are probably already doing personalization even if only in rudimentary ways. Here is where we dive into some of the technical and platform-related details of personalization.
Real-time personalization involves that elusive goal of uncovering user intent. When paid search advertising first emerged on the digital marketing landscape, advertisers were pleased to have an advertising platform with a microscopic look into user intent. Someone typed some text into a text field, and they got a series of hopefully-relevant results, both organic and paid, and they decided which listings were most relevant and/or appealing. The more specific the search, the more likely an advertiser could infer user intent: black New Balance minimus 20v7 trainer indicates a lot more purchase intent than gym shoes, for example. Google Ads integration with Google Optimize makes personalization targeted to paid search behavior a simpler proposition.
Google’s Optimize/Optimize 360 platform was initially released as a website testing platform, but with recent feature updates, the platform has transformed into a proper user experience tool. Not only can you run A/B, Multi-Variate, Server-Side, and Redirect tests on the Optimize platform but you can also use the platform for serving up true website personalization based on a wide set of targeting criteria.
Personalization can be targeted around some simple, yet powerful criteria such as URL rules, user’s geolocation, and device type. From there, you can quickly step up to more sophisticated targeting criteria as well. With Google Ads integration, you can target the full Google Ads hierarchy: account, campaign, ad group, keyword.
There are additional options for targeting personalization as well: URL query string parameters, javascript variables, data layer variables, and first-party cookies. If we look back to the discussion of intent earlier in this article, all of these methods can be used to capture user intent as a datapoint real-time so that Optimize can trigger personalizations on the fly.
The sections above listed several targeting types that you could use in Optimize for real-time personalization. Below, we detail three specific examples, which are quite similar but use three different approaches for storing real-time information to use as a personalization targeting rule.
Example: DataLayer Variable (Product or Service Interest)
Now you can set up a data layer targeting rule for ‘supply chain management’ prospects. When I navigate through the site, show me some additional content that aligns with my interests in a specific product or service.
Example: Javascript Variable (User Type)
Now you can create a JavaScript variable targeting rule for job seekers on your job posting website based on a JavaScript variable with the rule variable named ‘userType’ equal to ‘jobseeker’. You could create complementary rules for other user types: jobposter, undefined.
When you do use variables, you must place JS variables or dataLayer variables in the section of your page code and above the Optimize snippet. This is crucial. In the sample header script below, you can see an example of a dataLayer variable placed prior to the Optimize code:
You can even use tools, such as Optimize/Optimize 360 on single-page web apps. The trigger feature, Custom Activation Event allows you to fire the activation event snippet whenever your page updates/refreshes so that Optimize can look for new trigger criteria to be present and to launch appropriate personalization or experiments at that point. To learn more about activation events for Optimize, check out the documentation here.
Though marketing automation and sophisticated personalization tools certainly bring value and have their place in enterprise marketing and sales initiatives, you don’t have to invest in the most expensive or most comprehensive toolsets to start doing real-time personalization on your site. You can realize the benefits of real-time personalization by following a few simple practical principles and leveraging functionality you likely already have available with web developer support.
To learn more about enhancing end-user experience through real-time personalization, contact us today.
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