With 23% of retail purchases expected to take place online by 2027, furniture retailers have an opportunity to maximize their ecommerce sales potential.
Implementing effective product recommendations can help drive more conversions, increase product line awareness, and streamline operations. But which type of product recommendation is best for your furniture retail ecommerce?
Below, we’ll discuss AI-driven vs. manually curated product suggestions.
Understanding AI-driven and Manually Curated Product Recommendations
When it comes to boosting sales and enhancing the customer experience on your furniture retail ecommerce site, product recommendations play a pivotal role.
There are two primary types of product recommendations: AI-driven and manually curated. Understanding the differences between these can help you choose the right approach for your business.
Manually Curated Product Recommendations
Furniture merchandising teams can curate product recommendations based on predefined criteria that reflect current trends and seasonal offerings. This does not always factor in the browsing behavior of shoppers on your website, but it gives you total control over what products are recommended and displayed to your shoppers.
These types of product suggestions are often the first choice for growing furniture retailers as they are more accessible.
Advantages of Curated Recommendations:
Manually curated recommendations let you:
- Leverage industry knowledge, seasonal trends, and expert insights to choose products that may resonate well with customers.
- Maintain full control over which products are recommended, allowing for strategic promotion of specific items or categories.
- Showcase products that might not otherwise be promoted, such as overstock items, high-margin products, or new arrivals.
Drawbacks:
- Manually curating and displaying products requires a significant time investment.
- Ensuring that recommendations remain relevant involves continued maintenance.
- Curated selections might not always align with the immediate interests or needs of your target customers.
AI-driven Dynamic Product Recommendations
Instead of relying on manually curated suggestions, dynamic product recommendations can be based on rules and driven by AI. The combination of rules and machine learning considers shopper behavior to coordinate the best display of products through the clickstream.
Rule-based recommendations — such as best sellers, new items, also purchased products, or recently viewed items — offer streamlined ways to show additional or complementary products to your customers while machine learning algorithms continually refine what's displayed. Instead of simply viewing a “similar” product, your shoppers will see recommendations for highly considered products related to their searches and shopping behavior.
Advantages of AI Product Recommendations:
AI product suggestions offer the benefits of manually curated product suggestions and can:
- Generate suggestions based on specific actions and preferences, leading to a more personalized shopping experience.
- Adapt to changes in user behavior, ensuring the most relevant products are always displayed.
- Require less maintenance and upkeep, making it a more efficient choice.
Drawbacks
- Can give you less control over what you display and at what time.
- May limit the exposure of users to a wider range of products, potentially reducing the discovery of new items.
Blueport’s Product Recommendations
Blueport offers both manually curated and AI-focused product recommendations so that your teams can leverage both options depending on when and where you choose to display recommendations.
By understanding each customer’s unique shopping journey, Blueport’s recommendation engine, powered by Netcore Unbxd, ensures that the right product is always presented to the shopper, significantly improving product discovery and driving sales for furniture retailers.
Which One Would Help Your Business Right Now?
We highly recommend incorporating AI-driven, dynamic recommendations to improve your customer experience.
By showcasing products that closely align with what customers are looking for, AI product recommendations increase the likelihood of shoppers clicking on items and continuing their exploration. This not only enhances the shopping journey but also encourages higher engagement and conversion rates.
Powering Your Online Furniture Retail Store With Blueport’s AI
Blueport's product recommendation system is integrated into its overall omnichannel approach, which aims to create a seamless shopping experience across digital and physical channels. The platform uses geolocation to personalize online experiences based on shoppers' local stores and synchronizes with store systems to ensure unified end-to-end experiences.
If your furniture retail business is ready to enhance the online shopping experience, contact us today to learn more about the top furniture retail ecommerce platform.
