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This article will explain in detail how to analyze the content design and product recommendation functions of SAP Marketing Cloud marketing activities. The content of the article is of high quality, so the editor will share it for you as a reference. I hope you will have a certain understanding of the relevant knowledge after reading this article.

The following will introduce the functions of the two modules of marketing campaign content design and product recommendation in SAP Marketing Cloud.

After the marketing person in charge has identified the Target Group through the steps introduced in the second article, the next step is to design the content of the activity. This part of the work is done in Content Studio.

We can create different types of marketing campaign content. Personalized settings for customers can be made in the content, such as adding products in the user's shopping cart, user names, and so on. At the same time, you can also set the content you create as templates and reusable blocks for later reuse.

The design of personalized content is realized by clicking Insert Attribute where it needs to be inserted and selecting the desired personalized attributes. This function enables marketing activities to be carried out more intelligently and accurately.

For example, offer different discounts according to user portraits, recommend goods of different origin, and so on.

In the Condition Assignment interface, you can configure dynamic display rules for content elements based on certain conditions. For example, in the content element display layout, if you can get the user's First name, then the name is displayed, otherwise the default value is displayed.

The operation of offering different discounts to people of different ages is similar. Click the plus sign to set the display of different age groups.

When the Target Group and the content of the event are ready, we can begin to carry out the marketing campaign (the word Campaign is used below).

There are many Campaign templates to choose from, and we can choose according to our needs, or we can create our own templates for marketing activities for easy reuse.

Here is an example of Email Campaign.

As shown in the following figure, we select Target Group for the marketing campaign.

Add content to the marketing campaign, such as joining the A _ hand B test, send two different content emails to Target Group, and then collect business data from these groups to see the marketing results and help us adjust our marketing strategy.

Click on the trash can icon to delete unwanted content.

Make changes to the test settings for Aswab B. Conducting the Aamp B test before conducting a large-scale marketing campaign will help to find a better implementation.

Select the previously prepared Email for the mail module to populate.

You can add a trigger to a message, such as selecting "Open message" as the trigger condition:

If the email is not opened within 5 days (the number of days can be changed), send a message to the user to remind you. To implement this behavior, you just need to add the event and select the appropriate content to populate.

After setting up, we select Done and click Start to start the marketing campaign. Click Save as Template to create as a marketing campaign template. If the set start time has not yet arrived, the activity will be carried out automatically when the time arrives.

View the results of the marketing campaign on the Campaigns details page.

Since it is a marketing activity, product recommendation is of course necessary.

First of all, clarify some concepts and terms:

(1) recommended scenario Recommendation Scenarios

There can be only one model type per recommended scenario. Maintain the type of model assigned to the scene in the recommended scenario. In addition to providing recommendations to client applications, recommendation scenarios can also publish interactive data to an SAP HANA database.

(2) Model type Model Type

Represents the type of recommendation provided by the model. There can be only one active model per model type at any one time. The activity model provides recommendations to client applications.

(3) Model Model

A model type is assigned to a Model when it is created. The model type properties of the model cannot be changed after creation.

(4) algorithm Algorithm

The model consists of one or more algorithms. The algorithm uses historical data to retrieve recommendations.

In Manage Recommendation's Scenario Overview interface, we can search, view, and maintain recommended scenarios.

Scenario 1: display product recommendations on the web page according to the best-selling products within a defined period of time

Through the search, we find and select the Top Sellers In Web Home Page scene.

We can add a new Model to the scene. Enter the model name and select the model template, where you select the "sales ranking in interactive sales orders in the past 60 days" template. In addition, there are a variety of model templates to choose from, such as "items most viewed in the past 15 days" and "items viewed together on the Web product details page".

Select the algorithm contained in the model to go to the algorithm details page.

We can modify the parameters of the algorithm, delete unwanted pre-filters and add pre-filters.

Make changes to the model description:

These settings also need to be maintained:

Maximum recommended quantity: the default is 20

The algorithm generates refresh rate: the default value is 1 day.

Save and activate, and the model will take effect on the set date.

Scenario 2: cross-selling in the Web product details page

The recommendations displayed on the product details page are based on items that are often purchased with the items on the details page. For example, people who buy laptops usually buy mice.

Select the cross-sell scenario on the Web product details page, and add a new Model to the scenario, enter a name, and select cross-sell based on the interactive purchase history of the past 60 days as the model template.

If you only care about the items purchased in the same sales order, you can delete the unwanted algorithms preset in Model.

Check the algorithm details here:

Change the parameters in the same way as before:

You can use the pre-filter to set the Target Group for our algorithm:

Use the Add Algorithm or Rule function to add algorithms with different Target Group to make recommendations for different target groups in the same model.

Model is saved and activated in the same way as mentioned above.

Scenario 3: custom Model for recommendation

When establishing the Model selection model template, a number of options were mentioned above, such as: "sales ranking in interactive sales orders in the past 60 days", "items most viewed in the past 15 days", "items viewed together on the Web product details page", "cross-selling based on interactive purchasing history over the past 60 days", etc. However, we can also select an empty template, select the algorithm according to our own needs, and set the algorithm parameters.

On how to analyze the SAP Marketing Cloud marketing campaign content design and product recommendation functions to share here, I hope the above content can be of some help to you, can learn more knowledge. If you think the article is good, you can share it for more people to see.

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