Purchase propensity & abandonment

Sid Chaudhary

Sid Chaudhary

Founder & CEO

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Accurately predict purchase propensity in real-time and automate interventions with on-page experiences and messaging actions in journeys.

About the Growth Play

Converting browsers into buyers is crucial for balancing your acquisition funnel. This use case addresses the challenge of predicting the likelihood of user purchases and intervening when there is a high risk of cart abandonment.

Benefits

  • Increase sales: Predict and target potential buyers effectively to convert more browsers into customers.
  • Reduce cart abandonment: Implement timely interventions to prevent users from abandoning their carts.
  • Enhance customer experience: Personalize user interactions based on their behavior and preferences.
  • Data-driven insights: Utilize advanced analytics to understand user behavior and optimize marketing strategies.
  • Integration capabilities: Seamlessly integrate with various data sources to create comprehensive user profiles.

How it works

Step 1: Track key events

Identify purchase behaviors:

Common purchase indicators include frequent product views, adding items to the cart, and long browsing time.

Implement tracking for these events using the Javascript SDK or iOS SDK

Step 2: Create the lifecycle agent

Create lifecycle agent:

Navigate to the Agents section in Intempt

Initiate Agent Creation:

Select the conversion as the goal event - such as "Purchase."

Initiate Agent Creation

Filter Training Data:

Filter out users you don't want to include in the model training data. This might involve excluding inactive users or users with incomplete data profiles.

Filter Training Data

Real-Time Scoring:

Deploy the model to start scoring users in real time. Intempt ensures that the likelihood model operates in real time, constantly updating as new data is collected.

Once the model is trained and deployed, it will output an attribute with values indicating purchase propensity (low, medium, high).

Step 3: Create user segments

Create user segments:

Based on the lifecycle agent, create Segments such as "High Purchase Propensity" and "At Risk of Abandonment."

"High Purchase Propensity" should have a "High" value for the "Purchase likelihood" model.

High Purchase Propensity segment

"At Risk of Abandonment" will have a "Low" value for the "Purchase likelihood" model

At Risk of Abandonment segment

Step 4: Design personalized journeys

Create a journey for high purchase propensity:

Go to the "Journeys" section and click "Create Journey."

Define triggers such as "Product Viewed" or "Added to Cart."

Add conditions to target users in the "High Purchase Propensity" segment.

Configure actions like sending personalized emails with product recommendations or exclusive discounts. Example email:

Subject: "Special Offer Just for You! 10% Off on Your Next Purchase"

Body: "Hi [First Name], we noticed you were looking at [Product Name]. As a thank you, we're offering you a 10% discount on your next purchase. Use code SAVE10 at checkout. Don't miss out on this exclusive offer!"

High purchase propensity email

Create a journey for at-risk users:

Define triggers such as "Cart Abandoned."

Add conditions to target users in the "At Risk of Abandonment" segment.

Configure actions like sending reminder emails or offering limited-time discounts. Example email:

Subject: "You Left Something Behind!"

Body: "Hi [First Name], it looks like you left [Product Name] in your cart. Complete your purchase now and get an extra 5% off! Use code CART5 at checkout. Hurry, this offer is for a limited time only!"

At-risk user email

Step 5: Implement personalizations

Set up personalized experiences for high purchase propensity:

Go to the "Experiences" section and click "Create Experience"

Choose the target audience based on the "High Purchase Propensity" segment.

Design experiences such as tailored product suggestions or special promotions.

Example personalization:

On Home Page: Display a banner with a personalized message like, "Welcome back, [First Name]! Check out our new arrivals just for you!"

On Product Page: Show a sidebar with related products and a message, "Based on your interest in [Product Name], you might like these items too!"

Product page personalization

Set up personalized experiences for at-risk users:

Go to the "Personalizations" section and click "Create Personalization."

Choose the target audience based on the "At Risk of Abandonment" segment.

Design experiences such as tailored reminders and special incentives to complete the purchase.

Example personalization:

On Cart Page: Display a pop-up with a personalized message like, "Don't leave yet, [First Name]! Complete your purchase now and enjoy an extra 5% off with code CART5."

On Checkout Page: Show a message encouraging users to finalize their purchase, "Almost there, [First Name]! Your items are waiting. Complete your purchase and get 5% off with code CART5."

Checkout page personalization

Configure display rules:

Set rules to display personalized content on specific pages, such as the home page, product page, cart page, or checkout page.

Ensure the personalized content is visible to users in the relevant segments

Configure display rules

Step 6: Monitor and optimize

Analyze performance:

Use Intempt's analytics dashboard to monitor the effectiveness of your journeys and personalizations.

Track key metrics such as conversion rates, cart abandonment rates, and overall sales.

Optimize strategies:

Based on the performance data, make adjustments to your journeys and personalizations.

Continuously test and refine your strategies to maximize effectiveness.

Frequently asked questions. Answered.

It tracks things like frequent product views, adding items to cart, and longer browsing sessions, the signals that indicate someone is seriously considering a purchase. You implement tracking for these events using the JavaScript SDK or iOS SDK, and the model takes it from there.

Yes. When setting up the agent, you can filter out users you don't want included, like inactive users or those with incomplete profiles. This keeps the model focused on the audience that actually matters for your purchase predictions.

Set up a journey triggered by "Cart Abandoned" that targets your at-risk segment. Send reminder emails letting them know they left something behind, and sweeten the deal with a limited-time discount. Urgency plus incentive is a solid combo for recovering abandoned carts.

Absolutely. For high-propensity users, you might show a homepage banner like "Welcome back! Check out our new arrivals just for you" or a product page sidebar with related items. For at-risk users, display a cart page pop-up reminding them to complete their purchase with a discount code. Same site, different experience based on who's browsing.

You set display rules to show personalized content on specific pages, the home page, the product page, the cart page, the checkout page, wherever makes sense. The content only appears to users in the relevant segments, so high-propensity shoppers and abandonment risks each see what's most likely to convert them.

Real-time. The model updates constantly as new data comes in, so if someone suddenly starts adding items to their cart, their score reflects that immediately. You're not waiting for batch processing; you can act on current behavior.

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