Build a merchant-product personalization-driven engagement strategy
The future of consumer ecommerce belongs to brands who curate experiences that keep customers coming back. To improve the customers’ shopping experience, brands are using personalization to let them know they are truly valued.
But despite leveraging customer interactions to send unique content, offers, and promotions, we quickly lose context. This is because customer choices evolve rapidly – what users like today, they may not like tomorrow or for that matter, in the next hour. This leads to an increasing level of frustration among growth and retention teams looking to sustain their personalization strategy over the long term.
The gap lies in how we integrate personalization into the overall customer engagement and retention strategy. If personalization is approached on a standalone, campaign-by-campaign basis, it may not result in sustained customer loyalty, which all brands aspire to. To build a long-term personalization strategy at a realistic scale, growth we need:
- A recommendation engine that keeps up with rapidly shifting consumer choices in real-time
- Automation of campaign content to reach customers at the right time with the most relevant suggestions
This article is about how Product Recommendation capability helps fill this gap for brands. Plus, Recommendation Strategies (use cases) that will help teams drive growth and repeat business opportunities.
Accelerate product discovery and boost revenue with recommendations
The concept of recommendations has been around since Amazon first added “inspired by your shopping trends” or “top picks for you” to its website. They are so powerful that 35% of amazon.com’s revenue is generated by its recommendation engine.
Research in consumer psychology shows that convenience has a major impact on buying decisions. Customers are willing to spend more and buy more frequently when they receive a personalized and targeted experience
Here, our objective is to deliver a personalized experience that increases user retention, accelerating product/content discovery, and boosting revenue through cross-sell and upsell opportunities.
- Make real-time recommendations based on user actions tracked via Crayon SDK or APIs
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- Example: Trigger in-app notifications with product recommendations when a user adds product to cart or cancels an order
- Customize recommendations based on customer segments to upsell and optimize inventory
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- Example: Generate recommendations with only high value items or top-rated products for our most loyal users
- Enhance the customer experience with a live item catalog to customize recommendations
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- Example: Recommend the next best item if a given item becomes unavailable in the inventory
- Include/exclude items from recommendations to avoid serving repetitive or unwanted products
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- Example: If a customer has seen the top n recommendations, serve the next n items in the following communication
- Send multiple recommendations based on unique rules within a single campaign
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- Example: Recommend up to 5 items to a user who has abandoned cart in a carousel message (2 based on items purchased together; 2 based on viewed together; 1 based on product in cart)
Real-time personalized recommendations: use cases for ecommerce brands
Today’s ecommerce brands strive to meet customer needs by providing easy access to relevant products, assisting in product discovery, and wowing them with surprising product suggestions. In doing so, brands gain customer loyalty, better retention, and boost customer lifetime value. Weaving real-time recommendations into our engagement strategy allows you to accomplish the following:
1. Increase Average Order Value (AOV)
For growth and retention teams looking to increase revenue on each order, send personalized product recommendations during the most effective time!
Because our product recommendations use machine learning, they can be dynamically embedded in our campaign messages to make them highly contextual. Help customers discover more relevant products and find complementary items that match their buying trends.
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Serve related products to add to cart
Increase AOV with campaigns delivered at the moment (now) of purchase, urging users to add products to cart by featuring items frequently bought together with the item already added to cart.
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Cart abandonment campaigns powered by similar items
There are numerous ways that customers get distracted from purchasing items already in their carts. Supercharge our cart abandonment campaigns with similar items that are on discount, along with the usual reminder to purchase the abandoned items.
2. Increase Upsell and Cross-sell Opportunities
One of the prime benefits of using recommendations is increased sales through upsell and cross-sell opportunities. Our advanced recommendation algorithm makes use of high intent and low intent signals to determine the most relevant products to recommend. Sending these recommendations with intelligent campaign triggers makes them highly effective.
- Real-Time Recommendations Triggered by Customer Actions
- Search Abandonment Campaigns to Show Diversity of Product Catalog
- Complete the Look Campaign Based on Recent Purchase
- Recommendations for Selected Product Categories or Brands
- Post Purchase Engagement with Recommendations
- Premium Product Recommendations for Champion Users
Real-Time Recommendations Triggered by Customer Actions
Nudge users towards the path to purchase with in-app notifications triggered when users add products to their wishlist. Recommend similar products that are available on discount to incentivize a purchase at the moment.
Search Abandonment Campaigns to Show Diversity of Product Catalog
Users often need assistance to explore the breadth and depth of our entire catalog. Use search abandonment campaigns as an opportunity to showcase catalog diversity.
Complete the Look Campaign Based on Recent Purchase
Stitch together multiple items in one single campaign to complete a fashionable look for users. For instance: recommend multiple products such as jeans, casual shirt, jacket, and shoes – all in a single message. Guide users to purchase all or any of them with deep links for each item so users can click and be brought to the product page of an item.
Recommendations for Selected Product Categories or Brands
Boost sales for a selected few brands or product categories through targeted recommendations. If the user has seen the top 3 recommendations, avoid repetition and dynamically serve the next 3 recommendations.
Post Purchase Engagement with Recommendations
Assist users with recommendations based on the last purchase they made. For example, cross-product recommendations for users who purchased a mobile phone with products like Bluetooth headphones, phone cases, etc.
Premium Product Recommendations for Champion Users
Engage high value users or champion users with recommendations of premium products.
3. Increase Engagement and Retention
Brands that meet and exceed customer expectations enjoy high levels of engagement and retention. By delivering a personalized experience with highly relevant recommendations, brands serve customers not just seasonally but throughout their lifecycle. And taking an omnichannel approach to serve them recommendations ensures that we provide a seamless, personalized experience at every touchpoint.
- Web Campaigns Containing Recommendations Triggered on Exit-Intent
- Bring Users Back to the App via Personalized Push Notifications
Web Campaigns Containing Recommendations Triggered on Exit-Intent
Engage users with the most relevant products just before they leave our website. Grab attention at the last second to increase purchase completion by showing each user the most interesting products
Bring Users Back to the App via Personalized Push Notifications
Send product recommendations within push notifications to increase app launch. Use rich media and deep link each call-to-action to the product’s details within the app.
