Experience Email enables you to transform static emails into fully personalized experiences using a visual editor with drag-and-drop capabilities. Create your own, or select from a variety of preconfigured responsive templates that enable you to easily build your email message without any coding, while retaining full control over the merchandising and personalization algorithms.
How it works
|
Step 1: Use a drag-and-drop email builder to design your email, including blocks for dynamic content and recommendations. |
Step 2: Preview your design using mobile and desktop view while designing, or send a test email to see it on your device. |
Step 3: Generate an embed code snippet and paste it into your ESP as a new template, or into an existing one. |
Design an Experience Email campaign
- Go to Email › Experience Emails, and click Create New.
- Choose a method to create your email:
- Start from scratch. Create a completely new email using the editor, or create only the recommendation block, to drop into your ESP email code.
- Copy a previous email, and edit it for your current campaign.
- Use a template. A variety of out-of-the-box templates are available.
The builder opens. The following image shows an email-from-scratch in the builder; if you select to edit a template or block, some elements are automatically included or excluded. You can select the device view in the upper left corner of the builder.
Note: When you create an experience block (as opposed to a complete email), the option to define a responsive email (different design for different devices) is not available.
- Enter a campaign name, note, and labels for your campaign in the heading area.
- Whether you use a preconfigured template or start from scratch, you can now insert and edit the email building blocks. Drag and drop from the menu on the right of the screen to add, arrange, and edit elements (click the building block to see all its design options).
Email building blocks include:- Recommendations: A widget offering users fully-personalized recommendations.
- Dynamic Content: Target different promotions and messages to different audiences.
- Click Settings.
- Use the URL parameters to track clicks within your analytics software (optional). Add parameters to the defaults displayed as needed.
- Select an attribution window: Either 7 days (default) or 1 day.
- Click Save & Exit. You can return to edit all elements of the email at any time, until the code is generated. (After the code is generated, you can edit anything that does not affect the code.)
Note: To target by audience, make sure the identify Omnichannel Events (Signup, Newsletter Subscription, Login, and Identification) are implemented on your website.
Add an Experience Email content block
Experience Email offers several drag-and-drop blocks you can include in your email campaign. Each offers different design and personalization capabilities. These include:
- Recommendations: Enables you to set algorithms and filtering to serve users personalized content that's propagated when the email is opened.
- Dynamic content: Target different promotions and messages to different users based on affinity or audience.
- Maps: A personalized map shows users the nearest branch.
- Banner grid: A grouping of Dynamic Content blocks, displayed as a grid and ordered by affinity.
- Menu: Replace static top categories with an affinity-based dynamic menu.
Learn more about configuring Experience Email blocks.
Preview your email
Your email now appears in the Experience Emails main screen in the list of emails. Now, you can send yourself a test mail to make sure it's exactly right.
To send a test email:
- In the Experience Emails main screen, hover over the row of the email you want to test. The Send Test
icon appears.
- Click the icon, and then, in the popup, enter the email address to send the test email to.
- Click Send.
Prepare the embed code
- Configure ESP parameters (one-time setup)
- Generate the code
- Configure advanced options
Configure ESP parameters
If you do not have an ESP integration turned on, you must replace some parameter values that exist in the code. If you already have an integration enabled, you can view and manage the parameter values in the ESP Integration area.
Click the Code Parameters icon to set the ESP merge tags and apply them to all future emails.
Define the following parameter values:
- cuid_type: Set the user ID type in accordance with how you identified your users (such as by email address).
- cuid: Enter your ESP merge tag that will insert the user's CUID. For example, if you identify your users using their email address, you are required to enter the merge tag that will insert the user email address at send time.
-
locale: Enter your ESP merge tag that will insert the relevant locale code. The code should match what you specified in your product feed (for recommendations), or the site languages that you defined in the section settings (for dynamic content).
Note: Only appears for sites with the lng parameter defined in the feed or language defined in the site settings. - version: The ESP merge tag that represents the unique ID of the email campaign. By default, recommendations are cached for each user for a period of 4 days, so if they reopen an email they see the same content. However, you can use the same widget on multiple email campaigns (for example, using a "most popular" widget on every newsletter). Caching is managed per campaign version, so the user will see updated results if they open a different email with the same widget.
Add multiple integrations
You can add up to 5 ESP integrations, and define their merge tag variables here. Each integration appears in its own tab in the generated code/preview screen.
- Click Add another integration. Another set of parameter fields opens. Note that now each integration also has a name field, so make sure to give your first integration a name as well.
- Define the values for the new ESP integration the same way you did for the previous one (or more).
- Click Save. The merge tags are now defined for all future emails in this ESP.
Generate the code
When you are satisfied with your email, the next step is to generate the code to embed in your ESP.
- In Experience Emails, click Generate Code in the campaign's row.
A confirmation message appears, cautioning that once the code is generated, only changes not affecting the code are possible for this campaign (learn more about editing the email). - Click Generate Code.
The code is generated, also displaying a preview of the email. - Click Copy to Clipboard.
You are now ready to embed the code in your ESP.
The URL that appears in the code includes the following elements, as illustrated in this sample URL. Each element in the URL is colored to correspond with the explanation that follows:
https://em.dynamicyield.com/v1/email/dc/click/8769401/648204/648203?utm_source=dynamic%20yield&utm_medium=email&utm_campaign=[CAMPAIGN NAME]&cuid=*|EMAIL|*&cuid_type=email&locale=default&version=*|CAMPAIGN_UID|*&tag_ids=648203"
- 8769401 – Section ID
- 648204 – Campaign ID
- 648203 – Block ID
- ?utm_source=dynamic%20yield&utm_medium=email&utm_campaign=[CAMPAIGN NAME] – Tracking parameters; these can be set or removed from the campaign settings or inserted anywhere in the URL, and will be added to the target URL for your use in tracking the campaign.
- The ESP variables you define in your ESP integration
Advanced embedding options
When using Similarity and Purchased Together algorithms, you must set a context for the recommendation. The context enables the algorithm to recommend products that were purchased together with a specific item or that are similar to a specific item.
To this end, when setting the algorithm, you must add one or more products to display. In the recommendation block menu, you can search by product name or SKU. You can also set the SKU in a merge tag directly in the code snippet.
Adding SKUs in the console:
Adding SKUs in the code snippet:
To set a dynamic SKU, add the SKU values to the parameter in the <img> tag of the recommendation items to serve as the context. The parameter is added automatically, and you can add up to 20 SKU values:
&email_context_[BLOCK_ID]=sku1,sku2,sku3
For example:
<a style="text-decoration: none;" href="https://em.dynamicyield.com/emclk/8765432/4074/75741/15126/3/0?dy_ts=1544426026941&dy_cuid=REPLACE_WITH_EMAIL&dy_version=REPLACE_WITH_CAMPAIGN_VERSION&utm_source=Dynamic%20Yield%20recommendations&utm_medium=email"
target="_blank"><img src="https://em.dynamicyield.com/emop/8765432/4074/75741/15126/3/0?dy_ts=1544426026941&dy_cuid=REPLACE_WITH_EMAIL&dy_version=REPLACE_WITH_CAMPAIGN_VERSION&&email_context_605290=REPLACE_WITH_PRODUCTS&utm_source=Dynamic%20Yield%20recommendations&utm_medium=email" alt="" />
</a>In some cases, you might want to dynamically exclude specific products from being recommended in the email based on what you are currently presenting in the email. In that case, you can add the following URL parameter to all links and images in each slot of the recommendation:
&exclude_list_[BLOCK_ID]=sku1,sku2You can either enter the SKUs for that specific email manually or use a merge tag from your ESP that dynamically inserts the SKUs you want to exclude.
You can exclude up to 50 products from each block.
Recommendation items are served as images in optimized quality (that is, minimized for fast loading). However, if you'd like to improve image quality for better visibility of small details—you can do that by adding a dy_zf=2 parameter to your <img> tags:
<a style="text-decoration: none;" href="https://em.dynamicyield.com/emclk/8765432/4074/75741/15126/3/0?dy_ts=1544426026941&dy_cuid=REPLACE_WITH_EMAIL&dy_version=REPLACE_WITH_CAMPAIGN_VERSION&utm_source=Dynamic%20Yield%20recommendations&utm_medium=email"
target="_blank"><img src="https://em.dynamicyield.com/emop/8765432/4074/75741/15126/3/0?dy_ts=1544426026941&dy_cuid=REPLACE_WITH_EMAIL&dy_version=REPLACE_WITH_CAMPAIGN_VERSION&dy_zf=2&utm_source=Dynamic%20Yield%20recommendations&utm_medium=email" alt="" width="195"/>
</a>If you use the dy_zf=2, images are rendered twice as large as the item template size.
If you wish to include the "dy_zf=2" parameter in the embed code by default, contact Support.
Editing an email
You can edit an email at any time, adding or removing building blocks, or changing their design (click a block, and all its design options appear in the Content pane. Also on the right side of the builder are tabs for Columns, Body, and Uploads.
After you generate the embed code for your email (and even after an email is sent), you can edit dynamic content. That is, anything that is personalized, and is served or changed at open time. This includes the recommendation algorithm, filtering rules, and templates. You cannot, however, edit anything that is static, and which affects the embed code. This includes text and image blocks, or in the recommendation block—the number of items.
The reason for this is that each email campaign needs its own unique code snippet. If the code changes, this means there is essentially more than one code snippet collecting data for the same campaign. This can affect the report for the email, which would then include items that no longer exist, or new items not accounted for before. If you need to, we recommend running multiple versions of a campaign, instead.
Note: When you edit an email, it might take up to 10 minutes to take effect.
Experience Email reports
You can view a report for each email by clicking the report icon in its row. The report displays performance over time for the email and its included Experience Blocks.
Create or edit an email template
In the Templates tab of Experience Email, you can create a template of one of the following types:
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Dynamic content for email: Create custom content that is served or changed at open time.
- Name the template. Optionally, add notes and labels.
- Create the dynamic content using HTML or CSS to define. Use variables to define what to pull into the block from your product feed, such as product URL, product image, product name, currency, and so on.
-
Recommendation item template: Define the look and feel of each individual item in the recommendation widget. The name, price, image, and currency are all defined in the template, and are later rendered into a single image that is served at open time.
- Name the item template, define the item size, and optionally, add notes and labels.
- Use HTML, CSS, or JavaScript to define the recommendation item. Use variables to define what to pull into the items from your product feed, such as product URL, product image, product name, currency, and so on. Note that the supported formats for product images in email are JPG, PNG, or GIF.
- Save the template.
- Name the item template, define the item size, and optionally, add notes and labels.
You can edit a template by clicking its Edit icon, and then editing variables as needed.
For example, you can edit an existing variable, such as currency (say, from $ to €):
Or, you can add a variable in the code by double-clicking the spot to add it, and then editing its settings:
| Font | Font-Family | Font Weights |
|---|---|---|
| 'Abril Fatface', cursive | 400 | |
| 'Anton', sans-serif | 400 | |
| 'Arvo', serif | 400, 700 | |
| 'Balsamiq Sans', cursive | 400, 700 | |
| 'Bangers', cursive | 400 | |
| 'Bebas Neue', cursive | 400 | |
| 'Bungee', cursive | 400 | |
| 'Cinzel', serif | 400, 500, 600, 700, 800 | |
| 'DM Serif Display', serif | 400 | |
| 'EB Garamond', serif; | 400, 500, 600, 700, 800 | |
| 'Josefin Sans', sans-serif; | 100, 300, 400, 500, 600, 700 | |
| 'Lato', sans-serif | 300, 400, 700, 900 | |
| 'Merriweather', serif; | 300, 400, 700, 900 | |
| 'Montserrat', sans-serif | 300, 400, 500, 700, 900 | |
| 'Oswald', sans-serif | 300, 400, 500, 700 | |
| 'Playfair Display', serif | 400, 500, 700, 800 | |
| 'Raleway', sans-serif | 300, 400, 500, 700, 800 | |
| 'Roboto', sans-serif | 300, 400, 500, 700, 800 | |
| 'Roboto Mono', monospace | 300, 400, 500, 700 | |
| 'Rubik', sans-serif | 300, 400, 500, 700, 800 | |
| 'Source Code Pro', monospace | 300, 400, 500, 700, 900 | |
| 'Special Elite', cursive | 400 | |
| 'VT323', monospace | 400 |
All supported fonts are distributed by Google Fonts under SIL Open Font License, 1.1.
Email recommendation algorithms
You can select the algorithm that will be served in all items of the recommendation widget:
| Algorithm | Description |
|---|---|
| Automatic |
Let Experience OS select the best algorithm for you based on best practices for the page type you select. Algorithms per page type:
|
| Popularity |
Scores items based on the weighted sum of all product interactions – such as purchase, add to cart, and product view – favoring recent interactions over historical ones. You can expose the user to more products by intelligently reordering the algorithm's top results by checking Shuffle Results. This works by requesting more products from the main algorithms than required. For example, if a widget has 4 slots, this requests the 16 most popular products. All of the results get a weight based on their popularity, and then a lottery system that takes the weights into account randomly selects 4 items. The results should reflect that items that are almost as popular as the top 4 from the 16 returned results now have an almost equal chance of being displayed, but items that are nowhere near as popular now have a low chance. Without this option, the top four results are always displayed. |
| Purchased Together |
Recommends products that have been purchased together with the products you enter here. You can specify up to 10 items from your feed. It scores items based on the number of occurrences in which they have been purchased together in the same transaction, but demotes products that are typically purchased with many other items. Consequently, products that are strongly linked to one another are displayed, rather than having an arbitrary connection to a very popular product. |
| Similar Products To |
Recommends items that are similar to the products you enter here, factoring in item popularity. You can specify up to 10 items from your feed. The algorithm uses categories and keywords from the product feed to score similarities between items, assigning higher scores to rare keywords shared between a pair of products and lower scores to more common terms. |
| Viewed Together |
Recommends items that have been viewed in the same session as the items you specify here. You can specify up to 10 items from your feed. It scores items based on the number of occurrences they have been viewed together in the same session but demotes products that are typically viewed with many other items, implying a weaker connection. |
| User Affinity |
Personalized for each individual user and scores items based on derived user preference and product popularity. The algorithm bases its recommendation on the visitor’s interactions with the products (views, add to carts, and purchases) and their weighted scores. Then it analyzes the attributes of the products (brand, color, style, category, and so on) and calculates the user’s affinity profile. The strategy works in real time and can detect preference changes over time. When there is not enough data to produce a personalized recommendation, the algorithm offers a set of fallbacks strategies scaling from the most personalized to the most popular. |
| Purchased with Recent Purchases |
Items that are usually purchased together with items the current user recently purchased. |
| Purchased with Last Purchase |
Items that are usually purchased together with items in the last purchase by the current user. |
| Recently Viewed |
Items viewed by the user in the last 90 days. Unlike other algorithms, this algorithm serves out-of-stock items. |
| Recently Purchased |
Items purchased by the user in the past year. |
| Last Purchase |
Cart contents of the user's most recent purchase. |
| Similarity | Recommends items that are similar to the item currently displayed, factoring in item popularity. The algorithm uses categories and keywords from the data feed to score similarities between items, assigning higher scores to rare keywords shared between a pair of items and lower scores to more common terms. This algorithm is suitable for product/post pages. The similarity scores are recalculated whenever the product feed is updated. |
| Purchased Together Offline |
Recommends products that have been purchased offline together with the item currently displayed. It scores items based on the number of times they have been purchased together in the same transaction while demoting products that are typically purchased with many other items. Consequently, it recommends products that are strongly linked to one another rather than products that have an arbitrary connection to a popular product. The scores are recalculated every 24 hours. This algorithm is suitable for product pages and is not available for media or financial institution sections. This algorithm requires the import of offline purchase data. For more details, contact your Customer Success Manager. |
| Purchased Together Offline & Online |
Recommends products that have been purchased together offline or online with the item currently displayed. It scores items based on the number of times they have been purchased together in the same transaction while demoting products that are typically purchased with many other items. Consequently, it recommends products that are strongly linked to one another rather than products that have an arbitrary connection to a popular product. The scores are recalculated every 24 hours. This algorithm is suitable for product pages and is not available for media or financial institution sections. This algorithm requires the import of offline purchase data. For more details, contact your Customer Success Manager. |
| Viewed with Recently Viewed |
Items that are usually viewed in the same session as the last items viewed by the current user. |
| NextML |
Deep learning algorithm that predicts the next item that a user is most likely to interact with, based on similar engagement patterns of your users in the same locale. The algorithm is recalculated in real time, whenever there's a new recommendation request. This algorithm is available for customers with e-commerce sections on the following page types: Homepage, Category, and Any. To enable it, contact your Customer Success Manager. |
|
VisualML (Formerly Visual Similarity) |
A deep learning recommendation algorithm designed to identify and recommend items that are visually similar to the item currently displayed, matching things that the user can’t describe and that the marketers didn't tag into the metadata. |
- The following strategies have no fallback: Recently Viewed, Last Purchase, and Recently Purchased. This means that if there are no items that match the filter, the recommendation will display a blank slot.
- For the algorithms Purchased Together, Similar Products To and Viewed Together: Some ESPs support setting the reference items dynamically instead of specifying them individually.
Fallbacks
If the strategy returns fewer items than the number of slots, the system first "loosens" any constraints imposed by the basic filters. If there are still fewer results than the required items, the recommendation engine runs a respective fallback algorithm:
- User Affinity → Viewed with Recently Viewed → Popularity (shuffled results)
- Collaborative Filtering → User Affinity → Viewed with Recently Viewed → Popularity (shuffled results)
- Similarity → Viewed with Recently Viewed → Popularity (shuffled results)
- Purchased Together → Viewed Together (cart & product pages) → Similarity (cart & product pages)→ Popularity (shuffled results)
- Viewed Together → Similarity → Popularity (shuffled results)
- Viewed with Recently Viewed → Viewed Together (cart & product pages) → Popularity (shuffled results)
- Purchased with Last Purchase → Purchased Together → Viewed with Recently Viewed → Viewed Together (cart & product pages) → Similarity (cart & product pages) → Popularity (shuffled results)
- Purchased with Recently Purchased → Purchased Together → Similarity (cart & product pages) → Popularity (shuffled results)
- NextML → User Affinity → Viewed with Recently Viewed → Popularity (shuffled results)
- VisualML → Similarity → Viewed with Recently Viewed → Popularity (shuffled results)
FAQs
What happens when a recipient returns to an email in which one or more of the items are no longer available?
Because we cache the images of recommendations, when a recipient returns to an email they will still see the image. However, when they click the item, it will redirect them to the ‘yoursite.com/404’ page. We grab your main domain from the site settings.
What happens if the recipient or email client blocks external images?
For security reasons, some email clients do in fact block external images until the recipient opts to display external images; this will prevent the recommendations from displaying until the recipient either changes the settings or clicks “display external images”.
Why am I not seeing any images in some or all of my email recommendations?
Make sure that your SKUs do not contain the string "//". It is not supported and will cause an error when trying to render the email recommendation.
Is Dynamic Content supported by all ESPs?
We provide out-of-the-box snippets for a number of ESPs. For details, see Integrations. However, the code is easily customizable for all other ESPs.
Can I embed a GIF instead of an image in the Dynamic Content?
Unfortunately not.
When should I use Recommendations and when Dynamic Content?
Email Recommendations is designed for product recommendations (promoting the most relevant products from your product catalog) based on a selected algorithm, whereas Dynamic Content for Email is suitable for banners and promotions.
Are there any limitations to be aware of when setting up Dynamic Content in my email?
Although the flow is designed to be flexible and customizable, there are a few guidelines to abide by:
- Audience conditions are the only conditions that apply to Dynamic Content experiences.
- Item List is not supported.
- Unit CTR as a primary metric is not supported.
- Variation size must be equal for all variations.
- Because variation code is flattened to an image, custom fonts need to be embedded directly in the custom template.
- The click-through link is applied to the entire image; therefore, only one click-through link is assigned for the entire variation area.
- GIFs are not supported.
- Because the variation code is flattened to an image, custom fonts are embedded directly into the custom template, and we can't display different layouts based on device or screen size. The flattened image is generated using the template code when the email is opened, and Dynamic Yield can't detect which device or browser is being used.
What happens when I target an audience group but a recipient does not belong to the audience?
The default variation is served.
What is displayed when a recipient returns to the email for a second time?
The same variation is served, unless:
- The user opened the email, clicked the dynamic content before his first visit to the site, and opened the same email again.
- The user opened the email, logged in to the site for the first time, and opened the same email again.
What should I do if I see broken image icons in the Experience Email preview and test message?
Add the following UserAgent to your allowed list on your image CDN:
DY-Webshot/3.0 (Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) HeadlessChrome/99.0.4844.0 Safari/537.36 (operated by Dynamic Yield https://www.dynamicyield.com)
Also add the following IP addresses to your allowed list:
- 3.92.38.28
- 3.227.221.249
- 54.145.37.112
- 75.101.154.167
- 3.127.189.219
- 18.197.234.165
- 18.158.108.19
- 18.192.189.87