First steps
User Data
- Responsive Email Editor Review
- Designing your email
- Creating Synchronized Modules
- Setting Up Responsive Email Design
- Setting Up Smart Containers
- Creating a Gmail Promotions Annotation
- Adding The Rollover Effect
- Adding Anchor Links
- Module Library
- Adding a Table to an Email
- Adding Custom Fonts
- Creating CTA Button
- Working with Images
- Creating Timer
- Using AI in the Email Editor
Omnichannel
- Setting Up Widgets for Your Site
- Widget Calling
- Setting Up Locations for the Widget Calling Rules
- Storing data from widgets to contact fields
- Using Annoyance Safeguard
- Actions After Form Submission
- Replacing Double Opt-In System Workflow
- Using Yespo Extension for Google Chrome
- Creating Pop-ups via Google Tag Manager or WordPress
- Sending Yespo Widget Events to Google Analytics
- Using A/B Tests for Widgets
Automation
- Building and Editing Workflows
- Configuring Workflow Start/Stop Conditions
- Start Block
- Popular Blocks
- Message Blocks
- Contact Blocks
- Conditions Blocks
- Other Blocks
- Message to Segment Blocks
- Time Blocks
- Setting Up Allowed Send Time
- Using Workflow Launch History
- Webhook Workflows
- Workflow Troubleshooting
- Double Opt-In
- Welcome Сampaign
- Welcome Series Segmented by Category
- Launching a Workflow After a Contact Import
- Regular Workflow for a Segment
- Birthday Campaign
- Linking Workflow to the Button
- Using Variables from Order in Workflow
- Collecting Order Feedback
- Customer Reactivation
- Sending Extra Campaigns
- Sending Campaign to Those Who Did Not Open the Previous One
Personalization
Analytics
- Email Campaign Report
- Web Push Campaign Report
- Viber Campaign Report
- Mobile Push Campaign Report
- App Inbox Campaign Report
- In-App Report
- Widget Report
- Triggered Campaign Report
- AMP Campaign Report
- SMS Campaign Report
- Multilingual Campaign Report
- Setting up UTM Tags
- Revenue from Campaigns
- Tracking Campaign Performance in Google Analytics 4
- Message Analytics
Multilanguage Campaigns
Events and Behaviour Tracking
Recommendations
API
Security and Compliance
Integration
How to Send Product Recommendations via API
Product recommendations are an effective marketing tool. You can display personalized product recommendations in emails and on the site to generate repeat sales and grow customer retention.
Using the Contact recommendations based on web tracking resource, you can transfer data on customer preferences to other channels and offer recommendations based on it.
- Messengers;
- Call centers;
- Pickup points;
- Mobile apps.
How to Use Contact Recommendations Based on Web Tracking
The transfer of recommendations through Contact recommendations based on web tracking will allow operators/cashiers to generate repeat sales offering products based on customer shopping history.
Example 1
When calling the customer to confirm the order, the manager sees a list of recommendations for the bought products and personal recommendations for this customer, if any.
Example 2
When making an offline purchase, the customer provides their discount card or tells the phone number to earn account bonuses. The system identifies the customer and shows the additional recommendations for them.
What Product Categories Can Be Recommended
- Alternatives to out-of-stock products.
- Also bought. Cross-sell based on items added to the cart.
- You may also like. Upsell of more expensive items and complementary goods to increase the order price.
- Bestsellers. Recommendations based on orders by other customers.
- Personal recommendations based on the customer’s purchase history.
- Other. Recommendations created not using our algorithms.
Important
You need to send requests for each recommendation type because they have different data sources.
How to Use Recommendations
- Set web tracking and upload a product feed.
- Subscribe to a pricing plan covering Advanced Segmentation.
- Create a data source and select the necessary algorithm.
You need to create a data source for each recommendation type. Its ID will be used for an API call.
How to Send Recommendations
Specify request parameters:
| Parameter | Type | Description |
| dataSourceId | int |
Required. You can find data source IDs in Settings > Data sources. |
| contactId | long | You need to specify at least one of the parameters – contactId, email, phone, externalCustomerId, webI. |
| You need to specify at least one of the parameters – contactId, email, phone, externalCustomerId, webI. | ||
| phone | Phone | You need to specify at least one of the parameters – contactId, email, phone, externalCustomerId, webI. |
| externalCustomerId | String | You need to specify at least one of the parameters – contactId, email, phone, externalCustomerId, webI. |
| webI | String | You need to specify at least one of the parameters – contactId, email, phone, externalCustomerId, webI. |
| products | String | Product array. Required for algorithms based on product data. |
| category | String | Category array. Required for algorithms based on category data. |
Important
- This method doesn’t include the offset and maxrows parameters. The number of elements isn’t expected to be large and they are configured at the data source level.
- To receive recommendations on the site's backend, use the webId identification parameter.
Request and Response Examples
Go to your profile > Settings > Data Sources. Choose the data source and send a request
/api/v2/contacts/recoms/1244?contactId=162688150
where 1244 is a data source ID.
In the response, each field will be filled:
{
// Mandatory fields
id: string
name: string
url: URL
price: double
descr: text
brand: string
category: string[]
isInStock: int
// Optional fields which depend on a customer's feed format
// All such fields start from "tags_".
// Examples: tags_gender, tags_clear_size, tags_universal_size
}
