About the use case

Cart abandonment is one of the biggest challenges negatively impacting any online store's conversion rate and revenue. The common solution is to send simple cart reminders to nudge users into completing their purchases. However, this one-size-fits-all approach rarely works if the customers do not notice the email immediately.

With Intempt, you can go several steps further by creating multistep conditional workflows that leverage their behavioral data and use predictive attributes so you send personalized reminders and offers for each user's segment.

Benefits

• Increased revenue recovery. Tailored messaging can effectively re-engage customers and encourage them to complete their purchases, recovering lost revenue.
• Enhanced customer experience. Personalized follow-up messages based on browsing behavior and cart contents provide a more relevant and engaging experience.
• Higher conversion rates. Targeted recovery campaigns can lead to higher conversion rates and improved sales performance.
• Data-driven optimization. Leveraging user behavior data allows for continuous optimization of recovery strategies.

How It Works

To illustrate the use case, we will refer to a made-up project management app, "Otto."

Step 1. Set up tracking for new user activity

1. Install Intempt's iOS SDK:
   
   • Integrate Intempt's SDK into your e-commerce website to start tracking user activities. Follow Javascript SDK or Shopify integration guide to ensure proper setup.

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Step 2: Define key user events and attributes

1. Identify key events:
   • Track user activities such as browsing products, adding items to the cart, starting checkout, and completing a purchase. For example, page_view, add_to_cart, checkout_start, and purchase.

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2. Set up event tracking:
   1. Add a tracking script to record events in your application following the Javascript SDKor iOS SDK documentation.

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Good to know

Ensure that you track usersemail attribute so you can send emails to them. This can be done by a separate popup for newsletter subscriptions or by incentivizing users to sign up before starting the checkout process.

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Step 3: Create segments based on user behavior

1. Create segments in Intempt:
   • Navigate to the Segments section and create new segments based on the tracked events. For instance:
     • Cart Abandoners: Users who added items to their cart but did not complete the purchase within 1 hour.
     • Frequent Browsers: Users who frequently browse products but rarely add items to their cart.

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Step 4: Set up the journey for abandonment recovery

Journeys allow you to automate the sending of emails based on user behavior. In this case, we will create a journey that sends a series of tailored recovery emails to users who abandoned their carts.

1. Create a new journey:
   • Go to the Journeys section and create a new journey named "Abandonment Recovery".

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2. Add the trigger:

1. Trigger: Cart abandonment (add_to_cart event without a corresponding purchase event within 1 hour).

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3. Add email actions:

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• Email 1: Friendly Reminder
  
  • Subject: Did you forget something?
  • Body:

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Hi [User Name],

We noticed that you left some items in your cart.

Don't miss out on these great products!

[View Your Cart Link]

Best,

The [Your Store] Team

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• Email 2: Special Offer
  
  • Subject: Here's a special offer for you!
  • Body:

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Hi [User Name],

We noticed you left some items in your cart.

As a thank you for shopping with us, here's a special offer just for you.

Use code SAVE10 at checkout to get 10% off your purchase.

[View Your Cart Link]

Happy shopping,

The [Your Store] Team

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• Email 3: Last Chance
  
  • Subject: Last chance to complete your purchase!
  • Body:

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Hi [User Name],

This is your last chance to complete your purchase.

The items in your cart are going fast, so don't wait too long!

Use code SAVE10 at checkout to get 10% off your purchase.

Offer expires in 24 hours.

[View Your Cart Link]

Best,

The [Your Store] Team

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4. Add controls:
   • Delay: Add delays between emails to space out the communication. For example, delay 1 hour after the first email and 1 day after the second email.
   • Condition: Use conditions to check if the user has completed the purchase. Adjust the journey flow based on these actions.

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Example Journey Flow

1. Trigger: Users that enter the Cart abandoners segment.
2. Send Email: Friendly Reminder.
3. Delay: 1 day.
4. Condition: Has the user completed the purchase?
   • Yes: End journey.
   • No: Add a condition to check if the user is a Frequent Browser.
     • Frequent Browser: Send Email with 20% Discount.
       • Email: Special Offer
         • Subject: Here's a special offer for you!
         • Body:

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Hi [User Name],

We noticed you left some items in your cart.

As a thank you for shopping with us, here's a special offer just for you.

Use code SAVE20 at checkout to get 20% off your purchase.

[View Your Cart Link]

Happy shopping,

The [Your Store] Team

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• Not Frequent Browser: Send Email with 10% Discount.
  • Email: Special Offer
    • Subject: Here's a special offer for you!
    • Body:

Hi [User Name],

We noticed you left some items in your cart.

As a thank you for shopping with us, here's a special offer just for you.

Use code SAVE10 at checkout to get 10% off your purchase.

[View Your Cart Link]

Happy shopping,

The [Your Store] Team

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5. Delay: 1 day.
6. Condition: Has the user completed the purchase?
   • Yes: End journey.
   • No: Send Email - Last Chance.

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Step 5: Set up an advanced journey with likelihood prediction

Create the likelihood model

1. Create a Purchase Prediction Model:
   • Navigate to the Likelihood section in Intempt and create a new "Likelihood Prediction" model.

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• • Select the "Real-time" prediction model to generate predictions within the same session.
  • Select "Purchase" as the goal event.
  • "Under "User inclusion," select only users that performed the event added_to_cart to train data and create a prediction.
  • Wait until the model is trained to predict the likelihood of users completing a purchase.

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2. Create a new journey:
   • Go to the Journeys section and create a new journey named "Advanced Abandonment Recovery".
3. Add the trigger:
   • Trigger: Users that enter the Cart abandoners segment.
4. Add condition based on likelihood prediction:
   • Use Intempt's Likelihood Prediction model to create a "Purchase Prediction" score. Create conditions to segment users into high, medium, and low likelihood to purchase.
5. Add email actions for high likelihood segment:
   • Email: Friendly Reminder
     • Subject: Did you forget something?
     • Body:

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Hi [User Name],

We noticed that you left some items in your cart.

Don't miss out on these great products!

[View Your Cart Link]

Best,

The [Your Store] Team

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6. Add email actions for medium likelihood segment:
   • Email: Special Offer
     • Subject: Here's a special offer for you!
     • Body:

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Hi [User Name],

We noticed you left some items in your cart.

As a thank you for shopping with us, here's a special offer just for you.

Use code SAVE10 at checkout to get 10% off your purchase.

[View Your Cart Link]

Happy shopping,

The [Your Store] Team

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• Follow-Up Email:
  • Subject: Don't miss your discount!
  • Body:

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Hi [User Name],

We noticed you still have items in your cart.

Use code SAVE10 at checkout to get 10% off your purchase before it's too late!

[View Your Cart Link]

Best,

The [Your Store] Team

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7. Add email actions for low likelihood segment:
   • Email: Last Chance with Bigger Discount
     • Subject: Don't Miss Out on Your Items!
     • Body:

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Hi [User Name],

This is your last chance to complete your purchase.

The items in your cart are going fast, so don't wait too long!

Use code SAVE20 at checkout to get 20% off your purchase.

[View Your Cart Link]

Best,

The [Your Store] Team

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• Follow-Up Email:
  • Subject: Your 20% discount is expiring soon!
  • Body:

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Hi [User Name],

Don't miss out on your 20% discount!

Use code SAVE20 at checkout to get 20% off your purchase.

Offer expires in 24 hours.

[View Your Cart Link]

Best,

The [Your Store] Team

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8. Add controls:
   • Delay: Add delays between emails to space out the communication. For example, delay 1 hour after the first email, then delay 1 day after the second email.
   • Condition: Use conditions to check if the user has completed the purchase. Adjust the journey flow based on these actions.

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Advanced Journey Flow Example

1. Trigger: Cart abandonment (add_to_cart event without a corresponding purchase event within 1 hour).
2. Condition: Likelihood to purchase (High, Medium, Low)
   • High Likelihood:
     1. Send Email: Friendly Reminder.
     2. Delay: 1 day.
     3. Condition: Has the user completed the purchase?
        • Yes: End journey.
        • No: Send Email - Last Chance.
   • Medium Likelihood:
     1. Send Email: Special Offer (10% discount).
     2. Delay: 1 day.
     3. Condition: Has the user completed the purchase?
        • Yes: End journey.
        • No: Send Follow-Up Email.
   • Low Likelihood:
     1. Send Email: Last Chance with Bigger Discount (20% discount).
     2. Delay: 1 day.
     3. Condition: Has the user completed the purchase?
        • Yes: End journey.
        • No: Send Follow-Up Email.

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Step 6: Set goals and exit rules

1. Set a conversion goal:
   • Before starting the journey, set a conversion goal to measure its effectiveness. We recommend selecting the "Purchase" (or "Placed an order" if named differently) event to track your conversions.
2. Define exit criteria:
   • Decide whether users should exit the campaign once they achieve the goal. This ensures that users who have completed the purchase do not continue to receive recovery emails. You can select the same "Purchase" event as an exit criteria.

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Step 7: Monitor and optimize the journey

1. Start the journey:
   • Once the journey is set up and configured, start the journey in Intempt.
2. Monitor performance:
   • Use Intempt's Journey Analytics to track the performance of each email and the overall journey. Key metrics to monitor include:
     • Triggered journey: This metric indicates the initial engagement level, showing how many users have started the journey. A high number suggests that the journey trigger is relevant and appealing to users, highlighting the effectiveness of the cart abandonment trigger.
     • Converted: This metric shows the number of users who completed the conversion event set for the journey, which in this case is completing a purchase. It measures the effectiveness of the journey in achieving its goal. A higher number of conversions indicates a successful recovery effort.
     • Conversion rate: This percentage indicates how effective the journey is at converting users. A higher conversion rate suggests that the journey steps and content are well-aligned with user needs and motivations, effectively encouraging users to complete their purchases.
     • Days to convert (Avg): This metric shows the average time it takes for users to convert after entering the journey. It helps in understanding the timing and pacing of the journey. If the average days to convert is too long, consider shortening the wait times or streamlining the steps to accelerate conversion.
     • Entered: The number of users who started the journey. This helps in understanding the reach of the journey and the initial engagement level.
     • In Progress: The number of users currently in a journey block but haven't moved to the next step. This helps identify where users might be getting stuck or losing interest, allowing for targeted improvements.
     • Completed: The number of users who completed the journey. A high completion rate indicates that the journey is engaging and effective, successfully guiding users through the recovery process.
     • Failed: Instances where a journey action failed (e.g., an email not being sent successfully). This helps in identifying technical issues or poorly performing actions within the journey, allowing for troubleshooting and optimization.
     • Delivered: The number of successful deliveries of communications like emails or notifications as part of the journey. This metric helps gauge the reach of your communications and the effectiveness of the delivery process.

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3. Adjust and optimize:
   • Based on the analytics data, make necessary adjustments to the journey to improve performance. For example:
     • Refine Email Content: If open rates are low, consider updating the subject lines to be more engaging. If click-through rates are low, enhance the email content with more compelling calls to action.
     • Test Different Timings: Experiment with different wait times between emails to find the optimal timing that maximizes engagement.
     • Personalize Messages: Use personalization tokens to address users by their names and tailor the content based on their actions and preferences.
     • Analyze User Feedback: Collect feedback from users about the recovery emails to understand their effectiveness and identify areas for improvement.
     • Monitor Engagement: Track additional engagement metrics such as time spent on the linked pages and the number of items recovered after receiving the emails to gauge the overall impact of the journey.