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Sahl Thursday,13 Nov 2025

With the expansion of e-commerce in Saudi Arabia, customers now expect a personalized shopping experience similar to in-store shopping. They want to see products that suit their taste without having to search extensively. This is where the smart recommendation system comes in, relying on analyzing customer behavior within the store.

This system isn't just an online shelf displaying random products; it's a powerful tool that boosts sales and increases customer time on the site in a smooth and intelligent way.

1️⃣ First step: Gathering the right data that identifies customer interests 🧠 The smart recommendation system starts with data.

You need to collect and understand customer behavior within the store, such as:
- Products viewed
- Products added to cart
- Pages spent the most time on
- Keywords searched for
- Categories visited multiple times
These indicators are the foundation upon which the system accurately builds its suggestions.

2️⃣ Analyzing behavior and transforming it into clear patterns 🔍 Analysis is the brain that connects the dots.

For example, if a customer is browsing bedding products and adds a duvet to their cart, the system will infer that they are interested in bedroom items and begin displaying:
- Pillows
- Sheets
- Bedroom lighting
The more data available, the more accurate and intelligent the prediction becomes.

3️⃣ “Similar Customers” Technology Increases Recommendation Accuracy 👥
Here, the system says:

“This customer is similar to another customer who purchased certain products.”

Based on this, it displays the same products or products similar to those purchased by the previous customer.

This technology is excellent in large markets like Saudi Arabia because it relies on the responses of many customers, not just one behavior.

4️⃣ Focusing on Time… Not every visit has the same interest ⏱️
Customer behavior changes depending on the time of day.

For example:
- At the beginning of the week, they might look for office supplies.
- At the end of the week, they might buy going-out clothes. A smart recommendation system must distinguish between “ongoing interest” and “momentary interest.”

So, don't show the customer outdated products they're no longer interested in, but rather products relevant to their current visit.

5️⃣ Display recommendations in the right places within the store 📍 The most crucial factor for a recommendation system's success is its placement.

The ideal locations are:
– Product page
– End of product description
– Shopping cart page
– Home page
– "Previously viewed products" page
Each of these locations has a significant impact on increasing cart additions and purchases.

6️⃣ A mobile-friendly recommendation experience is very important for the Saudi customer 📱 Most shopping in Saudi Arabia is done via mobile.

Therefore, the recommendation system must be clear and easy to navigate, with a simple horizontal layout that customers can easily scroll through without feeling overwhelmed by the design or cluttered page.

7️⃣ How does the "Sahl" platform help you build a smart recommendation system? 🤖⚙️ Sahl provides a recommendation system built on automatically analyzing customer behavior.

Its features include:
- Tracking user behavior on every page
- Displaying products relevant to each customer
- Suggesting similar or complementary products
- Improving recommendations with each new visit
- Easily customizing the recommendations section

This means your store benefits from artificial intelligence without the need for complex programming or lengthy configurations.

The smart recommendation system isn't just an added feature…

It's a tool to boost sales, increase customer loyalty, and make the shopping experience in your Saudi store more comfortable and professional.

Implementing it with “Sahl” allows you to leverage the power of data analytics effortlessly and build a personalized shopping experience for each customer, moment by moment.