Shopping from brands has come a long way from the old in-store days. Today, modern-day customers interact with companies and brands across the world in several ways, like social media, search ads, organic searches, email, and word-of-mouth referrals.
However, one thing that has remained the same is the customers’ expectation of a personalized experience. A business that takes action based on intricate customer data is likely to resonate better with a larger audience and generate higher revenue.
That puts forward a difficult conundrum – how do you effectively address the needs of each customer or website visitor on a one-to-one level, especially with a small in-house team?
Spending several hours on each website visitor is impractical for any business. Hence, automating the process of customer data acquisition, interpreting customer insights, and curating website content for each individual in real-time is the golden duck for online businesses!
Differences Between Manual Recommendations and Automatic Product Recommendations
Manual Product Recommendations
Several eCommerce platforms like WordPress WooCommerce, Shopify, and OpenCart have built-in product recommendation systems that allow the store owner or administrator to manually add recommended products to product pages and checkout pages.
Manual recommendations certainly have their fair share of uses and benefits, but the pros of automatic product recommendations are far greater.
For example, some eCommerce stores in the custom fashion or fine jewelry niche, like Pure Pearls, have a highly segmented and smaller audience base. This group of customers can benefit from manual recommendations by the administrator.
Nevertheless, the owner or administrator of the online store should be well-versed with audience targeting and segmentation principles to successfully carry out manual product recommendations.
Automatic Product Recommendations
Automatic product recommendations, on the other hand, are driven by artificial intelligence and machine learning (ML) algorithms that intelligently analyze user input in real-time to come up with hyper-personalized product recommendations. Such individual recommendation greatly boost the total order value of each customer over time.
AI-driven automated recommendations are suitable not just for small businesses but even for medium and large-scale businesses that feature thousands of products across hundreds of categories in their eCommerce stores.
Above all, unlike manual recommendation engines, automated recommendation systems do not require the website administrator to be an expert in audience segmentation or behavioral analysis. The algorithm takes care of all that!
Advantages of AI Personalization and Individual Recommendation
1. Real-Time Analysis
Personalized or individual recommendation require mountains of data on users. Since humans cannot analyze user behaviors from the backend of the screen without breaching privacy, it takes several weeks or even months before actionable data sets could be gathered. This challenge is so widespread that it even has a name – the cold start problem.
Thanks to AI-based solutions, it is possible to securely gather real-time shopper insights to cross-sell products more effectively. This advantage can boost sales in any online store!
2. Saves A Lot of Time
When the recommendation engines are run on ML algorithms, they no longer require periodic maintenance and constant tweaking to perform effectively.
Business owners do not have to invest several hours creating the perfect buyer/shopper persona. The automated recommendations system captures live data to accurately and instantly enable individual recommendation products to website visitors.
3. Maximizes Engagement and Reduces Bounce Rate
Since individual recommendation are hyper-personalized, the content that the user sees would be incredibly relatable. Therefore, shoppers are more likely to interact with the website for longer, which shoots up user engagement metrics and lowers bounce rates.
4. Highly Scalable
Manual recommenders can only do so much. If your online store is growing or shrinking rapidly, it cannot do a good job of adapting due to the rapid fluctuation of data sets.
But automated recommendation systems can carry out tasks based on real-time data. Thus, your online eCommerce business can scale at any pace while maintaining high conversions.
5. Unmatched Accuracy
Here’s an interesting fact: approximately 8 out of 10 products sold online buy a business make up for only about one-fifth of the product catalog. This is known as the 80:20 rule or the Pareto principle.
As a result, what you recommend to your customers is more important than ever!
With AI personalization and Individual recommendation, you can consistently boost sales by showing your customers the best-selling and highest-rated products without any discrepancy.
Examples and Use Cases of AI Personalization
Below are some popular eCommerce stores that actively leverage the power of AI to maintain high conversions.
Often, going for an AI-driven recommendation system is more beneficial to a business than a manual engine. However, this is not a golden rule. Some businesses are better off with manual systems, at least in the early stages.
If the business owner makes an informed decision on the size of investment and ROI, then going for an AI-Powered automated recommender is advisable.
With an AI-first approach and strong expertise in AI frameworks, RecoSense is a one-stop partner for end-to-end Data Intelligence Solutions. Our industry-unique cognitive computing platform based on Natural Language Processing and Machine Learning frameworks offers Intelligent contextual interpretation of the Content & Users.
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