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
- Messenger Protocol Support in Email Clients and Platforms
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
- Creating Pop-ups via Google Tag Manager or WordPress
- Sending Yespo Widget Events to Google Analytics
- Using A/B Tests for Widgets
- Collecting Contact Information Using Request Forms
Automation
- Building and Editing Workflows
- Configuring Workflow Start/Stop Conditions
- Start Block
- Popular Blocks
- Message Blocks
- Using One from Many Message Block
- Contact Blocks
- Conditions Blocks
- Other Blocks
- Message to Segment Blocks
- Time Blocks
- Advanced Workflow Block Parameters
- 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 Reminders at the Time Specified by the User
- Sending Campaign to Those Who Did Not Open the Previous One
- Using A/B Tests In Workflows
Personalization
Analytics
- Email Campaign Report
- Web Push Campaign Report
- Viber Campaign Report
- Mobile Push Campaign Report
- App Inbox Campaign Report
- Telegram 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
Receiving Recommendations to a Mobile App
You can personalize the user experience and increase sales by adding recommendations of your goods and services to an app.
The passed recommendations are based on the customer activity data and include the following options:
- Out of stock. A selection based on similar items.
- Cross-selling. Offer of related products. The selected items are based on those added to the cart.
- Upselling. Offering based on more expensive and complementary goods and services to increase the order value.
- Potential purchase. The selected items are based on the orders of users who have purchased this product.
- Personal recommendations based on the customer's purchase and browsing history.
- Other. An offer is created individually if the required algorithm is not available among our platform's pre-configured algorithms.
Note: Each type of recommendation uses different requests having their own algorithms and rules since they take data from different sources.
Preconditions
Before starting using recommendations you have to meet the following conditions:
- Subscribe to one of the Extra features pricing plans.
- Set up web tracking or tracking for mobile apps.
- Create a data source with a required algorithm for each recommendation type to use its ID when calling an API.
Setting up recommendation transmission includes the following steps, as detailed below:
- Getting an authentication token
- Getting recommendations via v1/recoms/{dataSourceId} request
Getting authentication token
To get a user authentication token (authToken), send a request via your application from your server to our API.
Request address | Request method |
https://api/v1/auth/contact/token | POST |
Authenticate the request using one of the methods described in the API instructions. For example, using API keys.
The request shall pass the known user fields listed in the table (at least one field is required).
Field | Value | Description |
string | Contact’s email | |
phone | string | Contact’s phone number |
externalCustomerId | string | Contact’s external ID |
userPseudoId | string | Firebase ID for tracking the contact’s behavior |
cookie | string |
cookie sc – You can generate the cookie file using the tracking script installed on the site |
Request example:
{
"email": string,
"phone": string,
"externalCustomerId": string,
"userPseudoId": string,
"cookie": string
}
Response example:
{
"token": string
}
Further on, authToken authenticates requests to get recommendations. It shall be passed in the ES-TOKEN request header. The current token gets invalidated after every request, and the ES-TOKEN response header contains a new one used for the next request.
When you receive the 401 status, repeat the token request.
Getting recommendations
Send the following request to get personalized recommendations based on customer behavior:
Request address |
Request method |
GET |
Request parameters:
Field |
Value |
Description |
dataSourceId |
Data source ID. Required parameter* |
|
products |
string |
Array of products. The required field for algorithms based on product data |
category |
string |
Array of categories. The required field for algorithms based on category data |
request header |
ES-TOKEN: authToken |
|
response header |
ES-TOKEN: authToken |
* To find out the data source ID, go to Account → Settings → Data sources.
The response contains every field filled with the data.
Response example:
{
// 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
}
After you receive recommendations from our platform, you can display them in the customer’s mobile app.
You have to configure the parameters of recommendations in the app itself (design, placement, and others).