True 1:1 personalization — where content is personalized to each visitor of a website or portal — remains the Holy Grail of B2B marketing. However, much like its mythical counterpart, true 1:1 personalization lives mostly in the realm of fantasy.
Better Data and AI are Critical
For many companies, personalization is in practice an attempt to glean a few takeaways from inconsistent data. Maybe a marketing team can see that traffic from a specific social platform or website tends to show interest in a specific product. From there, they build a few buying personas and create supporting content. Keep in mind that wading through the analytics likely took a month and the process of fine-tuning messaging and creating content could have taken several more.
This is neither scalable nor particularly well-informed — which is why data is so important.
By contrast, consider the biggest online retailers (Amazon, Walmart, etc.). As soon as a consumer visits their home page, they are shown products of interest based on previous behavior and purchases. This isn’t because of a scenario like the one described above, it’s because of artificial intelligence (AI). While many companies can only dream of content and/or product recommendations of such granularity, creating a plan to collect the necessary data and automate recommendations is a great place to start.
Getting to 1:1 Personalization
AI can’t operate effectively unless it has a good data set from which to draw conclusions. In the case of a website, this often starts with the implementation of correct tagging. When discussing the don’ts of LinkedIn Sponsored Campaigns earlier this year I made a point of emphasizing the importance of using proper tags – lest attribution data become lost or fragmented. Websites operate the same way. Data regarding visitor preferences cannot be accurately collected and aggregated if pages themselves lack the necessary tags or tracking.
In Liferay’s case, we’re updating our use of Facebook’s Open Graph (OG) meta tags to categorize content. From there, we’re implementing Idio to aggregate the raw data and automatically create a personalized “card” with recommended content based on what a visitor has previously engaged with or consumed. Not only does this save the marketing team time, it also enables us to surface content a visitor might otherwise miss – helping us to better leverage existing assets.
While the specific tool(s) and tagging methodology you use may be different, you should have a system in place (or be working towards implementing a system) to collect visitor data and make recommendations based on their interests in an automated fashion. Automation – and the AI that it requires – is absolutely critical due to scalability concerns. Even a small business is likely to experience thousands (if not tens of thousands) of visitors coming to its site every year. It’s simply impossible for any degree of personalization to be implemented for that many people by hand. AI fills that gap but it cannot do so in the absence of large, reliable, data sets.
The Challenge of Regulation
The fact that 1:1 personalization is only possible where data exists — which it often does not — is a serious limitation. It’s also a barrier marketers need to accept they may never fully get around because of the regulatory landscape. Today’s consumers are becoming increasingly wary of the ways in which their data is being harvested and used by private businesses and government regulation is catching up to public sentiment.
Perhaps the most well-known example of recent regulation with applicability for marketers is the European Union’s General Data Protection Regulation (GDPR), which codifies a customer’s “right to be forgotten” and power to ask a business to delete all information they have collected about them. The law went into effect in 2018 and has forced companies of all kinds (including Liferay) to rethink how they engage with customers and prospects.
2018 also saw the passage of The California Consumer Privacy Act (CCPA), with the legislation scheduled to go into effect in just a few short months – on January 1, 2020. Among other things, the law requires that businesses with exposure to California residents (whether or not they have a physical presence in the state) notify consumers as to what personal information they are collecting and (like GDPR) delete it upon request. Given that California is the world’s fifth largest economy, the repercussions of CCPA will be felt far beyond the state’s borders.
GDPR and CCPA both directly affect the ability of business to personalize website content – particularly by offering visitors the ability to opt-out of tracking/analytics cookies. Businesses need to start paying attention to these kinds of rules (if they haven’t already) and make adjustments as necessary.
Implementing a Strategy
While personalization is often depicted as a binary – either you have it or you don’t – the truth is that it operates on a continuum. On one end you have a site where all visitors see the exact same content (the easiest to do but the least impactful) and on the other you have a site where each visitor sees content that’s completely unique to them. While true 1:1 personalization is more feasible now thanks to the emergence of AI, it still requires a great deal of resources (even in cases where the regulatory landscape makes it possible).
Greater personalization is obviously more likely to be impactful but that doesn’t necessarily mean it’s “better” from a business perspective. There is no clear cut, right or wrong answer and the optimal point between personalization and resources depends on the unique characteristics of your business. However, by making proper use of tags and tracking, implementing a tool to leverage the resulting data and being aware of the regulatory landscape, you’re giving your business the best chance of success.