Abandonment recovery

Sid Chaudhary

Sid Chaudhary

Founder & CEO

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Merge previous browsing behavior and a cart abandonment action into a comprehensive recovery flow that includes tailored messaging to maximize revenue recovery.

About the Growth Play

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

Step 1. Set up tracking for new user activity and define key user events

Integrate Intempt's SDK into your e-commerce website to start tracking user activities. Follow the Javascript SDK or Shopify integration guide to ensure proper setup. Track user activities such as browsing products, adding items to the cart, starting checkout, and completing a purchase (e.g., page_view, add_to_cart, checkout_start, purchase).

Good to know

Ensure that you track users' email 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.

Step 2. Create segments and Journeys based on user behavior

Create segments in Intempt:

  • 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.

Create a new journey:

Go to the Journeys section and create a new journey named "Abandonment Recovery".

Trigger:

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

Add email actions:

Email 1: Friendly Reminder

Subject: Did you forget something?

Body:

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,

Email 2: 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,

Email 3: Last Chance

Subject: Last chance to complete your purchase!

Body:

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,

Add controls:

Delay: Add delays between emails to space out the communication (e.g., 1 hour after the first email and 1 day after the second).

Condition: Use conditions to check if the user has completed the purchase. Adjust the journey flow based on these actions.

Example Journey Flow

Trigger: Users that enter the Cart Abandoners segment.

Send Email: Friendly Reminder.

Delay: 1 day.

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:

Hi [User Name],

We noticed you left some items in your cart.

As a thank you for your interest, here's a 20% discount at checkout.

[View Your Cart Link]

Happy shopping,

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.

Here's a 10% discount at checkout just for you.

[View Your Cart Link]

Happy shopping,

Delay: 1 day.

Condition: Has the user completed the purchase?

Yes: End journey.

No: Send Email – Last Chance.

Step 3: Set up an advanced journey with lifecycle agent

Create the lifecycle agent:

Navigate to the Agents section in Intempt and create a new Lifecycle agent.

Select "Purchase" as the goal event.

Under User inclusion, select only users that performed the add_to_cart event to train data and create a purchase likelihood prediction.

Create a new journey:

Go to the Journeys section and create a new journey named "Advanced Abandonment Recovery".

Add the trigger:

Trigger: Users that enter the Cart Abandoners segment.

Add condition based on likelihood prediction:

Use Intempt's Lifecycle agent to score purchase likelihood. Create conditions to segment users into high, medium, and low likelihood to purchase.

Add email actions for each likelihood segment:

  • High Likelihood: Friendly Reminder → Last Chance.
  • Medium Likelihood: Special Offer (10% discount) → Follow-Up Email.
  • Low Likelihood: Last Chance with Bigger Discount (20% discount) → Follow-Up Email.

Add controls (delays, conditions to check for purchase completion).

Step 4: Set goals and exit rules

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.

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.

Set goals and exit rules

Step 5: Monitor and optimize the journey

Start the journey:

Once configured, start the journey in Intempt.

Monitor performance:

Use Intempt's Journey Analytics to track metrics like triggered journeys, conversions, conversion rate, days to convert, and engagement breakdowns.

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.

Delivered metric

Adjust and optimize:

Refine email content, test timing, personalize messages, and monitor engagement to improve performance.

Frequently asked questions. Answered.

At minimum, track page_view, add_to_cart, checkout_start, and purchase. These let you identify who added items but didn't complete checkout. Make sure you're also capturing the user's email attribute, either through newsletter signup or by requiring email before checkout. Without an email, you can't send recovery messages.

Create a segment for users who triggered add_to_cart but didn't complete a purchase within a set timeframe, typically 1 hour. This gives them enough time to finish naturally but catches them while the intent is still fresh. You can adjust the window based on your typical checkout behavior.

A typical flow has 3 emails: a friendly reminder first, then a special offer if they don't convert, then a last-chance urgency message. You can add more if needed, but don't overdo it. Each email should have a clear purpose and an escalating incentive to give users a reason to act.

Yes, and this is where Intempt gets powerful. You can give bigger discounts to users who are less likely to convert (they need more incentive) and smaller discounts or no discount at all to high-intent users (they might complete without one). Use conditions to check if someone is a frequent browser or use the lifecycle agent's purchase prediction to segment by likelihood.

The lifecycle agent predicts how likely each user is to complete a purchase based on their behavior. You can then branch your journey based on high, medium, or low likelihood. High-likelihood users might just need a reminder. Medium-likelihood users get a moderate discount. Low-likelihood users get your biggest offer. This way, you're not giving away margin unnecessarily.

Add conditions throughout your journey to check if the user has completed the purchase event. If yes, end the journey immediately. Also set "Purchase" as your exit criteria so users are automatically removed from the flow the moment they convert. Nobody wants recovery emails after they've already bought.

Focus on triggered count (how many entered the flow), conversion rate (how many completed a purchase), and revenue recovered. Also, monitor days to convert to understand pacing, in-progress counts to see where people get stuck, and delivered rates to catch technical issues. Compare performance across your likelihood segments to see which approach works best.

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