In this article, we will share some best practices on how to enrich profiles with custom data that is only relevant to a specific target. Using custom data is helpful to personalize even more your customer shopping experience, and you can create as many advanced filters as you want. Some examples could be age triggers or profiles who logged in to your website or not.
What can I do with this Custom data?
You can create segments based on custom data. The segments can be used in Google Ads, content from Datatrics, Facebook Ads, and some ESP(Email service providers) to retarget these profiles in the way you would like to.
Website touchpoints based on custom data
You can use custom data for website touchpoints, one example could be if you sell both to B2B and B2C and you want to show relevant prices for direct clients or customers who got a business: if you set Incl. VAT on profile level you can show customers product recommendations with the correct price.
Suppose someone makes an appointment for treatment in a salon. You can save this via custom data on profile level. If you segment those people, you can personalize the email with content that is in line with the treatment they will have in the future. You can even follow up with products that are used during the treatment to sell this afterwards.
Here you can find additional examples, such as interest, service type, or age data.
Service type (example: treatment)
It could be helpful to save also appointment dates and the treatment type of that appointment so that you can personalize based on their choice.
People within a specific date range could be set in a segment. This segment can be synced to an email tool, and you can follow up via email with products that could be helpful to have after a particular treatment.
Incl. Excl. VAT
Suppose you set the choice, incl. or excl. VAT on profile level you can show the correct prices to the customers. So, for example, if the customer got a business, you don’t have to pay VAT prices, so you don’t want to show them the price including the VAT.
With a recovery hash, you can recover every product in your cart. So with an abandoned cart email, it does not matter if you open the email with your mobile phone or laptop, the cart will be restored due to that hash.
1) The website with the shopping cart where you see the hash,see point 3 (whether or not in the UI). Therefore, this is unique per visitor/device and must be stored server-side.
2) You must have this hash available in the data layer at the checkout value. So you can always read/use value in any tool.
3) Then, if you go to the same URL from mobile, you can retrieve the exact value of the cart.
Some customers do not have an email tool that can be connected with Datatrics, but there is a way to retrieve known profiles: with custom data, you can retrieve this data from the source website. If you would like to do this in Datatrics, we can set something in our back-end so these will become known profiles and be visible in the audience section of the platform. Please contact our customer support team to enable this for your project.
var _paq = _paq || ;
"profileid": "xx", (mandatory)
"profilesource": "website", (mandatory)
"firstname": xx, (not mandatory)
"lastname": xx, (not mandatory)
"var": "var_value", (not mandatory)
This will create a new profile source on the audience page:
Logged in user, not logged in user.
Within some websites, it is possible to log in. It could be beneficial to set this on profile level to show a logged-in customer different personalizations (think about discounts).
Age could also be an important data to have on profile level, read down below an example of an age filter and how to extract it via Google Tag Manager (GTM):
How to extract custom data via Google Tag Manager (GTM)
Our partner Pubmarket works for a company in the travel industry. They wanted to retrieve age data from their customers on the website. They need this information to show personalized content to specific age groups on their homepage, so they do not have to navigate via the menu on the homepage, but get there via a direct link.
The customer's website makes it possible to filter on age, and the selection is synced to Datatrics on the profile level.
Via Google Tag Manager, they have created a tag that captures the age category.
They also created a Datatrics Tag in Google Tag Manager.
They did this so they could also use those filter options to create segments in Datatrics and show personalized content to their customers based on their age.
This data is also pushed to Google Analytics via a Google Analytics Tag.
By doing this, they could also see this information in Google Analytics.
How to use
So on profile level, we retrieve custom event data based on age. It is called “leeftijd filter” (ie. “age filer”) and the number contains 65 in this example.
On the platform, you can go to audience targeting. If you go to targeting options, you choose a custom variable. You can select “leeftijd filter” (ie. “age filer”). Due to the above example of 65, you also set 65 in Datatrics to filter on that number.
So everyone that meets this targeting will be set into the segment you just created. This segment can be used in the examples mentioned earlier.