In our new guide, we walk through the process and philosophy behind converting more of your anonymous website traffic into bookings and loyal returning guests.
You can download or read the guide here: A Guide to Converting More Anonymous Website Traffic with Machine Learning
It starts with understanding the different ways of defining of known vs unknown audiences. On your site, “known” users might be based on a guest being logged-in on your site, recognized via cookies or another unique identifier, clicked from an email, or signed in to their browser (like Google Chrome). Unknown being, well, the rest!
Most online sellers’ sites have between 2% and 10% of traffic as known, which means over 9 of 10 site visits you get are from this anonymous cohort: no email address, no previous purchases, and little to no data about them. How can you act on this?
Learning about your anonymous users
There’s a secret with anonymous website traffic – it may seem you have no data, but in reality you have a fair amount of data about them from web analytics and tracking tools.
Our guide will go into more detail on this, but as a teaser: Google Analytics documentation can tell you quite a bit about all the possible information that can be captured and pushed into BigQuery and other accessible tools.
Different experiences for different site visitors
Depending on what data you have – and the various permutations – each visitor can have a personalized experience. Starting from website landing page, through content and promotions, and down in lower-funnel touch points.
The best case scenario to capture more conversions from all these unknown prospects floating in and out of your site is to engage them a bit more personally.
You can tailor content, recommendations, and interactions directly to them. Maybe obvious when you know someones booking history, but it can still be done for totally anonymous people!
To dig deeper into how to convert more anonymous prospects and leads through your booking funnel, check out the full guide here!
