How AI Recommendation Systems Are Driving Business Value

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Artificial intelligence has the potential to revolutionize the way that companies market and sell their products. AI recommendation systems, in particular, have the potential to drive significant business value to brands.

While we’ve all heard of product and service recommendation engines by the likes of Amazon, Spotify, Tinder, Google, and so on, these are just one category of recommender systems.

Another powerful type of recommender systems are merchandising recommendations, which are AI-powered recommendations for web and in-store merchandising strategies.

Let’s dive into these two types of recommendation systems to see how they can drive value for your business.

Product Recommendation Systems

AI-powered product recommendation systems help brands to automate one of their most time-consuming and expensive processes.

Traditional product recommendation systems rely on data scientists who manually review and integrate data into the product recommendation process.

AI-powered product recommendation systems can help brands to increase both product sales and brand awareness. It’s said that Amazon’s AI-powered recommendation engine is responsible for over one-third of its sales, making it one of the most valuable AI systems on the planet.

Recommendation systems can also help drive brand awareness. By surfacing the most relevant products on social media, recommendation systems can help brands to reach new customers, and provide new product recommendations to existing customers.

Recommendation systems can also help brands to provide a better customer experience. For example, online shopping is often a frustrating experience for customers who have to sift through irrelevant products to find the right one.

Moreover, recommendation systems can even help brands to improve the product design process. For example, recommendation systems can help brands to make design decisions by surfacing the most relevant products to a given problem.

Finally, recommendation systems can also help brands to identify customer pain points and create products to solve those pain points. For example, if two products are commonly purchased together, the brand might offer a package offering, or even an improved product that features the best of each product.

Merchandising Recommendation Systems

Beyond the product recommendation systems that drive many of the businesses we use today, from Google to YouTube to Amazon, there’s another type of recommendation system driving massive business value: Merchandising recommendation systems.

Merchandising strategies are key to a retailer’s success, but creating successful strategies is far from easy. These strategies should vary by category and objective, and should rely on the data, instead of gut feeling.

Using Commerce.AI, businesses can create merchandising recommendation systems to uncover the best web and in-store merchandising strategies. Popular strategies include traffic building, transaction building, profit generating, turf defending, excitement generating, and image enhancing.

With this wide-range of potential strategies, trying to execute on all of them is a recipe for disaster, as you’ll stretch your resources thin. Selecting a strategy at random isn’t the answer either, especially as competitors are using data-driven approaches to fuel their merchandising strategies.

With Commerce.AI, businesses can find the best merchandising strategies for their needs, powered by a data engine trained on millions of products and services across thousands of categories.

Why Merchants Need Intelligent Merchandising Strategies

As Harvard Business Review reports, around three-quarters of new consumer packaged goods and retail products fail. Other reports indicate failure rates as high as 85% among fast-moving-consumer-good (FMCG) launches. 

With such an incredibly high failure-rate, merchants can dramatically improve with AI-powered recommendations systems that highlight the best strategies.

Conclusion

Artificial intelligence recommendation systems will continue to revolutionize the way that businesses design and sell their products. By automating the product recommendation process, improving product sales and brand awareness, and the customer experience, AI recommendation systems will be key to business success.

There’s a lot of hype surrounding artificial intelligence, but it’s already driving real business value for companies around the world.

In this article, we’ve explored how two main types of AI recommender systems have the power to add massive value to your business.