Email with last visited brand

A good way to personalize communication is to offer customers products from a brand they recently viewed. This is an especially good solution for companies offering multiple brands.

You can build this kind personalization in a very easy way and make it possible to send an email campaign with personalized offers from specific brands to people who have viewed this brand recently.

Example of use - Retail Industry

Challenge

One of our clients wanted to send to their customers personalized emails based on the last brand that the client viewed.

This company is an example of a multi-brand company in which you can select products based on brands. In the URL information of every product, they always have information about its brand.

Solution

Based on that we created an automation which lets us monitor the last-viewed product and the category it belongs to. Thanks to this, we were able to send personalized emails with brand-related AI recommendations. Every customer got a different email recommendation based on their previous behavior.

Screenshot presenting last visited brand

Requirements

General

  • Synerise tracker

  • Email campaign configuration

  • AI integration

  • Product feed

How to do it

First concept

Manual preparation without jinjava

  1. Prepare an Aggregate LAST, based on the event page visit URL and add a regular expression which indicates that the URL has to contain one of the following brands.

  2. Prepare the AI recommendations separately for every brand (you can choose the type of campaign on your own).

  3. Create email campaigns for every brand separately, adding the AI recommendation campaign prepared for each brand.

  4. Prepare the automation.

Screenshot presenting automation

  • Trigger client event; choose the event page visit which tells us if the client visits a specific website with a specific url, use regular expression – this indicates that the customer visited the products from one of the following brands.

  • Delay; which is optional

  • Customer filter; which checks every agreement which customers have (cookie agreements, email agreements and so on)

  • Split path to client filters, which checks what the last aggregate of the customer was. Every filter indicates a different brand and sends a different campaign. For example, if the last brand a customer visited was ABC, he will get an email with products from this specific brand.

We separated every segment in this place in the automation, which lets us check to which brand the customer is matched and send him personalized mailings.

Second concept

Preparation with jinjava

We helped our client to prepare this process in a smarter way. We changed the part with all client filters to single client filters and only one event.

  1. Create the aggregate the same as in the first concept.

  2. Create the AI campaigns for each brand separately.

  3. Create ONE email template with the special jinjava code.

    Based on the jinjava code we can create a smarter process for the whole campaign.

    We took the aggregate described above and checked the code to see the last brand the customer visited (what phrase customer had in the url).

    So if, for example, our customer viewed brand ABC, we added the code the title: ABC, an image and a link to the product. And the same applied to all other brands. So we prepared all such information in one place, in one code.

    So if in the aggregate we had the ABC brand – in the email template the ABC brand was added to a specific product along with a link to it.

    Also, we add a lot of IF’s in our jinjava code. This indicates that IF ABC brand was the last one the customer visited, then the ID of the AI campaign for the ABC brand will be used in that case.

    Using this method, we can change the content of the mailing dynamically depending on what we have in the aggregate. Information about the specific brand will go to the output in the form of dynamic code, which we have to paste in the email campaign in a specific place. Thanks to this it will change dynamically based on the results from the aggregate for a specific customer.

    Remember to add the AI campaign to the content of your email campaign based on the campaigns created earlier.

  4. Create an automation.

Screenshot presenting automation

The automation consists of 5 elements:

  • Client event (the same as in the first version)
  • Delay (optional)
  • Client filter (the same as in the first version)
  • Send email
  • End

So all of the elements are the same but the only difference is that we have added the jinjava code to the email template instead of adding it in the form of many brand filters, which makes the whole automation very large and more complicated.

Note: If you do not want to use jinjava you can use the first version of the automation. It is not forbidden but take into consideration that in this case you have to remember to add the appropriate email template and email name in the automation without any mistakes.

It is easier to create a second version with jinjava to avoid mistakes and make it faster and easier to build and to manage.

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