Increase sales with product recommendations: Personalise. How to buy customers.

"The website is beautiful ... but why do customers not buy more?" The problem of online store owners

Have you ever been ... that you are confident that the products in your online store "Dee" and "quality" and the webpage is beautifully designed. But had to face a headache situation like this:

• Customers come to see many products. But in the end, just click to buy "one piece", although we have many more interesting things
• Under the product details page, there is a "Related Products", but it looks "unrelated" with what the customer is interested.
• Aov (AOV) does not move up at all. Customers have never bought more than 1-2 items.
• The worst is Customers have already clted on the basket. But when seeing the recommended products that are not interesting May be hesitant and "press and close"!

If you are nodding ... You are not faced by this problem alone. This is the "blind spot" that many online stores overlook. That is the recommended product that "lack of heart" and "do not truly understand customers".

Prompt for illustrations: Online store owners are sitting in front of the computer screen that opens their own stores. On the screen there is a recommended product that doesn't match the main products that customers are watching at all. Conveys the irritability and the opportunity that is lost

Why "related products" become "non -selected products"?

This problem is not caused by your product is not good, but caused by the "thinking method" of the old product introduction system. That most stores use Which is usually a simple logic that is "too hard" such as:

• Based on categories (Category-based): If the customer looks at the camera The system will recommend other cameras. In the same category Regardless of whether the customer may be looking for "lens" or "tripod"
• Based on what others bought (People ALSO BOUGHT): "People who buy products A often buy B" This logic looks good at first. But if the current customer has "Specific demand" that is not the same as most people? That suggestion will be "worthless" immediately.
• Manual Selection: The owner of the shop must sit and choose the recommended products one by one. Which wasted a lot of time And cannot be adjusted to match each customer in real time

Simply put, these systems look at all customers. "The same person" lacks something called "Personalization" or customization to each person Which is the heart of modern marketing Understanding Personalization ideas for e-Commerce will help you see how we can create superior experiences.

Prompt for illustrations: simple infographic images Demonstrates the Flow's operation of the old product introduction system. Compare 3 types: 1. Point out from products A to the same category. 2. Show a large group of people buying the same item. 3. Show the hands of people who are dragging the product by themselves. Convey the absence of dynamic and frozen

Leave ... may not lose just "sales" but lose "customers" forever

Having a product recommendations That is not effective Is no different from having a salesman who does not know the product and does not understand customers The consequences are not small at all:

• Low conversion rate: When customers do not find things that "yes" the opportunity that he will buy more will decrease immediately.
• AOV (AOV) AOV (AOV) does not grow: you will miss the opportunity to make upsell (selling more expensive) and Cross-Sell (selling related items) unfortunately.
• Customer experience (User Experience) worse: encountering advice that is not repeated. Makes customers feel that your brand "doesn't care" and "don't know" they
• Customers fled to competitors: in the era of all the shops competing Personalization If your website also provides experience "One-Size-Fits -all" is not strange that customers will choose to find a brand that "knows more".
• Lose the opportunity to collect in -depth data: You will miss the opportunity to learn the behavior and preference of customers. Which is a precious treasure for future marketing planning. The Zero-Party Data data will become difficult when customers do not want to interact with.

In the end, the problem seems to be a little. May bite your business until shocking, making the cost of finding new customers higher But could not keep the old customers

Prompt for illustrations: 2 line graph images are graphs. "Sales" that are still completely, not going anywhere. And the other line is a graph "Customer ratio from (Churn Rate) that rises The back is a picture of customers who are not waving goodbye to your website.

Turn the game! Change "Visitors" to "avid shoppers" with Personalized recommendations.

The good news is ... We can completely solve this problem! The solution is a change from "Original" products that come to be "recommended products ... for you, especially" (Personalized Product Recommendations) based on the power of Data and AI to help.

Its principle is to analyze the behavior of each customer in Real-Time. Whether:

• Click to see
• Products that have been purchased in the past
• Products added to the basket
• Search terms on the web
• The duration of each product

After that, Recommendation Engine, who is smart, will process these enormous information. In order to guess and present the product that that customer "There is a tendency to be most interested" at that time precisely.

And where will it start?

1. Understand the type of Recommendations: Not every suggestion will be the same. Try to get to know strategies such as "products that are often bought together" (Frequently Bought Together), "Products that you may like" (Recommended for You), "Trending Now products).
2. Choose the right tool: Currently, there are many tools and applications that allow Personalized recommendations. It's easy, such as recommendations AI from Google Cloud or various apps on a shopify platform.
3. Position correctly. At: Show advice on strategic points that customers tend to make a purchase, such as the product page, the basket page, and even in the follow -up email.

Starting to understand UPSELL and Cross-Sell strategies are the first stairs that are excellent in bringing Personalized recommendations. To be used to maximize benefits

Prompt for illustrations: beautiful infographic images Show the process of Personalized Recommendations Engine, starting with the icon of people with various behavioral information (click, search, buy) flow into the "AI brain" and come out as a recommended product that appears on the computer screen and mobile phone of the customer.

Examples from the real thing: from ordinary clothing stores to the brand that "know the heart"

Imagine a "STYLEME" online clothing store that has encountered a problem with only one T -shirt and disappeared despite the pants, skirts and many other jewelry.

Before the change: Styleme's page only "products in the same category", if customers come to see the white T -shirt He will only see other t -shirts, all the opportunity, legs, jeans that meet together, so they are zero.

The mission "Turn the website to know the heart": Styleme decided to invest in Personalized recommendations. Driven by AI

1. Product Page: Under the white T -shirt Instead of showing other T -shirts, the system shows the section "Complete The Look" that recommends jeans that models that are paired together. With necklaces and sneakers
2. Cart Page: When customers add a T-shirt to the basket, there will be a small pop-up showing that "People who buy this product tend to buy ... (socks or belts) ... add as well."
3. Homepage (Homepage): For customers who have already entered the website The system will remember what kind of product he used to see. And show the banner "New products ... for you, especially" that select only that product style

The amazing result: only 3 months after using the new Styleme system, it was found that AOVER AORD VALUE (AOV) increased by 25% and Conversion Rate from the recommended section 3 times higher than the average of the web! Customers feel like having a personal stylist to give advice. Causing them to come back to buy repeatedly and become regular customers This is the power of changing from "guessing random" to "use data" to create the best experience.

Prompt for illustrations: The Before & After online store image "Styleme", the first picture (before showing a T -shirt and has a recommended product as a boring other T -shirt (AFTER) shows the original T -shirt. But the recommended products are "Complete The Look" that includes pants, shoes and jewelry with numbers, % more sales.

Want to follow, right? Checklist starts to create a product recommendations that "can actually sell"

Read here You probably see the power of Personalized Recommendations. Then right? The good news is that you can start immediately! Try using this checklist as a guideline:

Phase 1: Foundation (foundation)

• [] Installing the tracking pixel correctly: Make sure you install the measurement tools such as Google Analytics 4 or Facebook Pixel. To collect basic behavior of customers, having GA4 manual for E-Commerce will help you to start confidence.
• [] Start collecting customer data seriously: whether it is purchasing information, admission history, or even Quiz for customers to tell the zero-party data).

Phase 2: Choose tools and strategies (Tools & Strategy)

• [] Explore the tools/app: If you use a platform like Shopify, Magento, or Woocommerce, try to find the app "Product Recommendations" or "Personalization" that has a good review and suitable for your budget.
• [] Set Placement: Plan to display results. Recommendations At any point, such as the first page, product page, the basket, confirmation page, or even page 404 not found
• [] Select the type of recommendations to use: In the beginning, it may start with the "Frequently Bought Together" and "Recommended for You" first and then gradually expand to a more complex model.

Phase 3: Measure & Optimize

• [] Set goals at measurement: How many percent do you want to add AOV? Or want to add a conversion rate from the product recommendation?
• [] Do A/B Testing: Don't stop, just install! Try the test between "algorithms" different or "different display design" to find the best for your customers.
• [] Analyze and learn: Go to see the report regularly which products are recommended and the best selling. In order to continue to plan the stock and market

To follow these steps Will change your website from just "shops" to become a "personal shopping assistant" that customers will fall in love with

Prompt for illustrations: Beautiful checklist images, modern style, divided into 3 parts, according to Phase, each has an easy -to -understand icon, such as graph icon for measuring, tools for tools, and icons for customer information. Looks like it is easy to follow.

Questions that E-Commerce people often doubt (Q&A)

Q1: There must be a large shop. Or have a lot of information Before? Can you start Personalized recommendations?
A: Not necessary! Many modern tools are designed to start working, although there are not many information. Which the system will start by using "Wisdom of the Crowd" (such as products that most people click often Or the bestseller). Go first and when there are more customers' information The system will gradually Adjust Personalization More automatically, so "the faster The more advantage "

Q2: Is these systems difficult to install? Do you have to hire a programmer program?
A: For popular platforms such as Shopify or WooCommerce, there are many applications that can be installed in a few clicks without writing even a single line. Most of them have Dashboard pages for you to easily set up and see reports. But if you want a more complex and deeper system for the official website, having an e-commerce expert team to give advice and care, it will help everything to be smooth and the best results.

Q3: How is it different from general UPSELL / CROSS-SELL?
A: UPSELL/CROSS-SELL General models are usually manual settings and the same for all customers (such as buying a phone model A to recommend the B B), but Personalized Recommendations will be "smarter". "Real behavior" of that customer, for example, if this customer has watched a pink case before The system will choose the "Pink" case automatically. Which has the opportunity to close the sales much higher

Q4: Is it worth investing?
A: According to statistics and case studies around the world, the answer is "very worthwhile". Investment in this system is like hiring the best salespeople and working for you 24 hours without holidays. Return returns in the form of higher AOV, improved conversion rate and increased customer loyalty. Usually many times higher than the cost of a long -term

Prompt for illustrations: Specialist cartoon characters (Maybe the brand's mascot) is standing answering questions eloquently. There is a question mark (?) And the lamp mark (!) Float around to convey the solution.

Conclusion: Do not just "sell" but "create a heart -know experience"

At this point, I believe that you can see that the Product RecommenDations is not just a "supplementary feature", but it is one of the most powerful "marketing tools" for the E-Commerce stores. In this era, the change from the offering of "sowing" is a "knowing" and "true".

It is a conversation from "This is what we have" to be ". This is what we think you are looking for." Care of these little details is what is separated between "Ordinary stores" and "brands in the hearts of customers"

Do not wait for the opportunity to increase sales and impressions of customers. Start exploring and acting from today To change every visit to a greater sales!

It's time to upgrade your online store! If you need an expert who understands both the design and marketing of e-commerce, it helps to set strategies and create a product recommendations. To change every click to be a sales of the Vision X Brain team today! We are ready to be a partner to your success.

Prompt for illustrations: Powerful and inspiring final images Is a picture of a product that is full of products that customers are happy Along with the sales graph that rises to the sky Conveys the final result of success from Personalized Recommendations.

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