How a Product Recommendations Engine Improves Customer Experience

By ​Karlie Morien

July 12, 2018

Product recommendations engines are a great way to deliver customers with an improved user experience. Through machine learning, manual curation, and specific algorithms, a product recommendations engine can help bring customers the relevant products they want or need.

Take a closer look for more on what a product recommendations engine is, the benefits it offers, how to use it to meet customer experience expectations, and best practices.

What is a Product Recommendations Engine?

A product recommendations engine is a solution that allows marketers to provide customers with relevant product recommendations in real time. As a component of an ecommerce personalization strategy, product recommendations dynamically populate products onto websites, apps, call centers, or emails, enhancing the customer experience. These omnichannel recommendations are made based on data such as customer attributes, longitudinal behavior, or situational context.

Using specialized algorithms, product recommendations engines are able to support even the largest of product catalogs. The engine is driven by an orchestration layer that is able to intelligently select which algorithms and filters to apply in any given situation, for any given individual shopper. This means that marketers can maximize conversions and average order value.

The Benefits of Using a Product Recommendations Engine

Using a product recommendations engine can provide several benefits to help drive your business forward. Here a few of the top advantages to consider:

Increase Sales and Average Order Value

Product recommendations allow you to drive higher conversions and increase average order value. With a recommendations engine, marketers are able to bring multiple data sets (historical data, third-party insights, and real-time visitor behavior) into a recommendation algorithm. These algorithms can then deliver relevant recommendations in real time as customers engage with your brand.

This level of relevancy gives a boost to sales and average order value by exposing customers to a greater volume of items that are likely to pique their interest. By leveraging inferences about what is likely to resonate with the customer based on what they are already planning to purchase or what has been purchased by similar customers, the recommendations engine can encourage additional spending while providing a more engaging user experience.

Create a Consistent Brand Experience

A consistent brand experience can begin with product recommendations. By drawing data from multiple channels to inform your recommendations, you can optimize your omnichannel customer experience so that your customers don’t feel as if they’re starting fresh with each interaction. Instead, by serving them more personalized recommendations across every channel on which they interact with you (web, email, in-store, app) you can ensure that your customers feel known by your brand and create a strong and loyal connection.

Avoid Customer Frustration

Customers quickly lose patience when they experience frustrations like being served a recommendation for a sold out product. Such experiences can and should be avoided; by using a recommendations engine that filters out items guaranteed to create this kind of disappointment, you can ensure that the content you deliver is relevant to the consumer an also leads to sales and revenue.  

Meet CX Expectations with a Product Recommendations Engine

Customers have higher expectations than ever before, and product recommendations are playing an integral part. When users engage with your brand, they are looking to be led on a smooth and easy buying journey. Anticipating products they may need along the way helps them find items that will delight them and fulfill their needs. Remember: one good experience will likely bring a customer to the next, so keep that in mind as you develop and adapt your personalization strategy.

Personalized Interactions

The majority (73 percent) of consumers say they would increase their purchases if they had a superior customer experience. A product recommendations engine is one of several tools at your disposal that can deliver the level of personalization that will impress consumers with individualized options.

Consistent Experience Across Channels

Today, offering a consistent customer experience begins with omnichannel personalization: brands need to engage with customers in the same way across all channels. If a customer recently searched for a product on one channel, a recommendations engine should be able to personalize email communication with relevant products or send a push alert via a mobile app when a product the customer considered is selling out. The job of the engine is to recognize the individual across the board, which will deliver a personalized omnichannel experience.

More than half (58 percent) of consumers say they would recommend a company that delivers a relevant customer experience. If you’re providing a relevant experience across multiple platforms, you could have a better shot at meeting customer expectations, earning sales and driving revenue.

Customized and Relevant Content

Building customized and relevant content is one of the most efficient ways to meet customer expectations. With 65 percent of consumers saying an online experience has changed their opinion on a brand or its products, you may only have one shot at making a good impression.

Product recommendations engines help brands make a positive impression by presenting customers with items that will make them feel as though they were hand-picked for them.

Best Practices for Using a Product Recommendations Engine

As with any solution, there are a few tried and true best practices for using a product recommendations engine:

  1. Make intelligent recommendations. Leverage all the data (both internal and third-party) that enables the product recommendations engine to deliver contextual recommendations, ones that recognize them as an individual.
  2. Design an appealing and easy to navigate experience. Crowding a page with products may frustrate customers; instead, create a dedicated space for a few well-chosen product recommendations.
  3. Keep recommendations fresh. Remember to update the products you’re recommending regularly and as needed. If customer data changes, you must immediately adjust your recommendations to reflect the change. Letting stale product live forever at the bottom of a page not only decreases consumer relevance as time wears on, but could also become noticeable, diminishing the positive impression of a fresh, personalized experience.

If you would like to learn more about Monetate or how to get started with our Monetate Intelligent Recommendations Engine, contact us today. Sign up for our blog if you want the content to keep coming your way.

Karlie Morien is the Director of Market Development at Monetate. She joined the company in October of 2016, and comes from a background of software sales and business development. She lives in Phoenixville, PA and you can likely find her cooking for her two daughters, ages 8 and 10.

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