MoEngage launches Smart Recommendations to help consumer brands build personalized and memorable experiences for their customers.
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Did you know that 35% of Amazon’s E-commerce revenue is generated thanks to its advanced product recommendation engine? Did you also know that 80% of the stream time on Netflix can be attributed to its industry-grade content recommendation engine?
The modern consumer wants more personalized and contextually relevant communication. 27% of consumers find irrelevant content and product recommendations to be their most frustrating experience with brands, while 26% of consumers want brands to personalize experiences based on previous shopping history.
Customers no longer question the need to collect data because they expect you to use it to create delightful experiences for them. This includes delivering personalized recommendations to them. Although consumer brands understand the need for personalized recommendations, most are not well-equipped to create memorable customer experiences.
We’ve built Smart Recommendations to help you build personalized micro-moments for your customers. In real-time, you can send suitable recommendations to each customer based on their preferences, past interactions, and engagement patterns, easing product discovery and increasing conversion.
AI powers the all-new MoEngage Smart Recommendations to enable you to send real-time recommendations across any channel without any technical expertise.
This helps your customers discover new products and increase their probability of completing a purchase. You can create a seamless buying journey personalized to each individual’s unique needs by recommending the right products and items.
Smart Recommendations has six distinct built-in recommendation models, enabling you to serve your customers the most appropriate product recommendations.
You can use this model to recommend products based on specific item (product) attributes.
This model is best used when you want to showcase products for specific thematic events, occasions, requirements, and more.
Some examples of item attributes-based recommendations are recommending skirts that are “blue” in color and “large” in size or suggesting mutual funds that have “low SIP installments,” “high-interest rates,” and a “1 yr maturity period.”
You can recommend products based on your customer’s past interactions and actions.
Customer action-based recommendations play a critical role in driving purchases for items your customers want.
Some examples include recommending products added to the cart but not purchased or suggesting TV shows customers have added to the wish list.
Leverage our proprietary AI Engine, Sherpa, to recommend products most suitable for your customers.
This model filters items based on customer preferences, customer interactions over time, and other engagement patterns.
This recommendation model is best used to maximize engagement, drive more purchases, and deliver personalized experiences.
An example of recommended items is showing a pair of shoes to a customer based on their preferences.
Let Sherpa AI recommend products similar to those a customer has last interacted with.
This model picks items based on product attributes and the historical co-occurrence of events.
The similar items recommendation model will help you avoid and reduce drop-offs in the buyer journey.
An example includes recommending dresses based on attributes such as price, brand, title, or category, often viewed together, added to a cart together, and more to a customer who has viewed a winter dress.
Leverage Sherpa AI to recommend products that customers frequently view together. This will depend on the latest product viewed by a customer.
This model is critical when you want to avoid and reduce drop-offs and showcase catalog versatility.
An example of this model being used is when a customer has viewed a phone, you can recommend other products, such as phone cases or accessories frequently viewed together.
Use Sherpa AI to recommend products frequently bought with the latest producing listing a customer has interacted with.
This model is a great way to boost cross-sell opportunities.
An example of this model is recommending accessories other customers have frequently purchased to a customer who purchases a Television unit.
Personalized recommendations have become necessary for brands to engage with customers, boost sales, and deepen engagement. 49% of customers had purchased a product because of a personalized recommendation they received from the brand.
We built Smart Recommendations to help brands send personalized, contextually relevant recommendations to customers.
This new feature enables you to send real-time, contextually relevant suggestions from millions of catalog products to each customer. The new Smart Recommendations will help you:
Smart Recommendations make it easier for your customers to discover new and relevant products. Here are reasons why our MoEngage is the solution to your current challenges:
MoEngage Smart Recommendations is built using AWS Personalize, the same recommendation engine that powers Amazon’s robust e-commerce website.
You can be assured that you get the most accurate and relevant recommendations powered by industry-leading and battle-tested algorithms.
Your customers’ needs are varied, and so are the use cases for your brand.
Marketers can choose the right recommendation model to implement the most appropriate strategy and delight customers with relevant recommendations – Item attributes-based, Customer actions-based, or AI-recommended.
Leverage the power of AI to recommend products that would be most relevant for the customer.
Our recommendation engine keeps track of all customer interactions, preferences, and engagement patterns in real time. This information is then used to decode your customer’s purchase intent and deliver the most relevant recommendations.
MoEngage’s recommendation engine feeds customer behavior to our proprietary algorithm as it happens, adapts to the new data, and refreshes quickly to provide relevant recommendations in real time.
Delight your customers with relevant product recommendations across the website and the channels your customers prefer, such as Email, Push Notifications, SMS, In-App Messages, On-Site Messages, and Cards.
Marketers don’t need data science or coding expertise to go live with Smart Recommendations.
You can integrate data, select recommendation models, and start serving relevant product recommendations quickly, all from an intuitive and easy-to-use interface.
MoEngage Smart Recommendations lets you send personalized recommendations to your customers across different touchpoints in your customer’s omnichannel journey, such as Push Notifications, Emails, WhatsApp, Facebook, Mobile In-app Messages, and Website Banners. You can personalize the recommendations for each customer journey stage and enable your customers to find what they want quickly. Your customers no longer need to click or search multiple times to find their favorite product on your website. This will help you:
Suggest the most relevant recommendations to each customer based on their preferences, helping them discover products and services faster. By helping your customers fulfill their needs more quickly, you can improve the overall experience and increase revenue.
Recommend popular, relevant, and trending products to your customers when they’re about to complete a purchase and encourage them to increase their order value. Over time, this also helps you improve customer LTV.
Customers are more likely to purchase products they resonate with. So if your campaigns recommend products aligned with their preferences, they are more likely to convert and give you better conversion rates overall.
Suppose your customers are hovering around the exit button or performing other actions that indicate they’re uninterested in completing a purchase. In that case, you can slip in a relevant recommendation to pique their interest. This helps reduce cart abandonment and improve conversions.
With MoEngage Smart Recommendations, you can show your customers exactly what they’re looking for before they even start searching. Surprise your customers at every step with a relevant, personalized recommendation and create better experiences for every customer.
Recommend the newest shows or songs from a customer’s favorite artist. Recommend precisely what customers want before they search for it and improve their trust in your brand. These recommendations will also help you create happy customer experiences that keep them coming back for more.
If you’re an existing customer, contact your favorite MoEngage account manager to get started with Smart Recommendations. If you’re new to MoEngage, you can request a demo here.