Why is Optimal Product Ranking Important for E‑Commerce Businesses

Introduction

We live in very convenient times when it comes to online shopping. Whether we want to buy a new electric toothbrush or a new winter jacket, a few clicks and we can see thousands of products we can buy. The thing is, only a few online shoppers are eager to browse result lists made of hundreds or thousands of pages. If they can’t find the item they want on the first page, ideally on the top, they might search for it elsewhere.

Is there a way to ensure that all your future customers can find what they need quickly and easily, no matter what they seek? Of course, there is. You can use product rankings to present the most relevant and appealing products to users.

Read on to find out how product ranking works, how you can use product ranking in your e-commerce store to boost your future customers’ shopping experience but also meet challenges that it brings, and look into future trends.

The product ranking algorithm analyzes the information it has about given products, compares it with the search keywords, picks the products that match the search query the most, and then uses product rating criteria to rank items in order of relevance.

Just as online searchers aren’t too keen on browsing dozens of result pages on Google, only a few e-commerce store visitors are eager to look through 15 or 20 product listing pages while shopping. On average, 89% of consumers only browse through the first page of product listings—and if they can’t find anything that interests them there, they just assume the store might not have what they are looking for and leave.

That’s why helping search engines rank products better is now just as important as boosting your store’s organic search position in Google – your conversion rate and customer satisfaction depend on it.

Read also our other article, “How to Optimize Product Catalog for Maximum Search Efficiency,” which had several good tips on how you can make search engines’ jobs easier—for example, how you could use product reviews to boost the rankings.

How are the products ranked?

The ranking criteria important for product search engines differ slightly from those for websites as the searchers’ intent is also different.

Let’s say you want to buy a new vacuum cleaner but don’t know how to pick the right one. You will probably turn to Google first to find articles about how to choose the best vacuum cleaner for your needs. Once you know what kind of vacuum cleaner you want, you’ll probably go to an e-commerce store to look for products that match your requirements, compare the product ratings, and then read product reviews to help you find the ideal model.

So, basically, you use Google mostly to find general information, and once you know what type of product you are looking for, you go to e-commerce search engines to find it.

That’s why product ranking algorithms have to use a bit different criteria when analyzing and ranking the products:

• Product title and description
• Relevant keywords
• Image quality
• Price
• Description and listing completeness
• Features
• Brand name
• Customer questions
• Product video
• Specifications (size, color, dimension, material, and others)
• Average rating of a product
• Customer reviews (including negative reviews) and product score
• Number of sales

Basically, the more information the search algorithm has about a product, the easier it will be for them to match the right items with the correct search query. Therefore, it is crucial to ensure your product description and title use relevant keywords and that the description contains all the information visitors may need.

However, regular search engine tools sometimes display irrelevant results since they focus mainly on keywords in product descriptions and search terms when showing results. What’s more, the product listing order is more or less the same for every visitor, even though the visitors might be looking for a different type of the same product.

That’s where e-commerce dedicated search tools come in. Rather than just focus on the target keywords used in product titles or descriptions, those tools use more factors to rank:

• Predicted user intent (so people that typed, let’s say, a smartphone model would see the phone models first rather than see both phone models and accessories to it – so those purchase intentions are met)
• Customer’s purchase history (for example, to highlight goods from the brand the customer is often picking)
• Number of sales (to put the best-selling items to the front)
• Matching product characteristics
• Any custom ranking rules set by the store owners (e.g., answers to customer questions)

This way, e-commerce search tools can “predict” what precisely a given visitor is looking for and then show them the items they are most likely to be interested in. But what’s even better is they can automatically tailor the rankings according to the actions visitors take on the website – for example, by analyzing what product categories or items the visitors were clicking.

Consequently, the product selection that appears on the search results is fully tailored to each visitor’s expectations, so they are more likely to find and purchase the product that fits their purchase intentions – boosting your conversion rates.

How can e-commerce search engine tools boost your product rankings?

E-commerce search plays a crucial role in boosting product rankings, bringing several advantages:

Shows more relevant products to visitors

Whatever product the store visitors are looking for, they know one thing – they want to find what they are looking for as quickly as possible. Seeing things on the result list far from what they are looking for can discourage them from browsing the store and making purchases.

Say someone is looking for a new smartphone to buy – does it make sense to show them dozens of smartphone covers and other accessories in the same list? Not really – they are now looking for a phone, not for accessories yet. So, smartphone devices should be ranked higher than smartphone accessories. However, product search engines might show smartphone devices and accessories on the first page if the product title and descriptions match the keywords. The accuracy rate really matters here.

E-commerce search tools are far more innovative here, though. They can monitor and analyze the visitor’s actions at the store, finding out what exactly the store visitor is looking for and then tailoring the product rankings to visitors’ expectations. That way, the search results page will show exactly the products future customers want to see at the top, making it easier for them to decide.

Saves customers time

In a Feed Advisor report, 54% of Amazon users admitted they often buy the first product on Amazon’s search results page. Why? They know how the Amazon product ranking algorithm works and trust that the item that is ranked first is the one that will meet their needs the most. Therefore, they don’t need to search any further or compare online reviews – they trust that the search algorithm has already picked the best product for them.

AI-powered search tools can help you deliver the best possible customer experience by saving time and displaying relevant products thanks to the ability of AI and machine learning to:

• Personalize: AI and ML algorithms can analyze vast amounts of data about user behavior, preferences, and past interactions to personalize product recommendations. By understanding individual user preferences, these algorithms can tailor search results and product rankings to match each user’s specific needs and interests, thereby improving the overall user experience.
• Dynamic ranking: Traditional algorithms often use static rules or features to determine product rankings. AI and ML algorithms, on the other hand, can continuously learn from user interactions and feedback to adjust rankings in real-time dynamically. This adaptability allows the algorithm to respond to changing user preferences and market dynamics, ensuring that the most relevant and popular products are consistently ranked higher.
• Contextual understanding: AI and ML algorithms can analyze contextual factors such as user location, device type, time of day, and browsing history to provide more relevant and contextualized product rankings. For example, a user searching for “coffee shops” on a mobile device in the morning may receive different rankings than a user searching on a desktop computer in the evening, reflecting their respective contexts and preferences.

For the shoppers, that means they won’t have to explore your entire store catalog far and wide and compare the average rating of ten different products – the products that match their needs are right at the top. The faster they can find a product that meets their requirements, the more likely they will purchase it.

Shortens shopping path (and risk customers will abandon the store)

Baymard Institute recently found that the average cart abandonment in e-commerce is nearly 70% (precisely, 69.9%). In another survey, this time from Barilliance, it was found that the abandonment rate for mobile and tablet abandonment is even more worrying – 85% for mobiles and 80% for tablets. What are the reasons? Slow pages, long and complicated checkouts, extra costs visible only at checkouts – and needing help finding the product they want among thousands of others.

You can improve your abandonment rates a bit, though, by enhancing how your product rankings work. With personalized rankings for your visitors, you can show them the items they are most likely to click on and keep updating those based on what actions the visitors take. For example, suppose you have three different visitors looking at winter coats. In that case, each can get a separate search results page depending on what product categories or items they clicked on earlier. Accuracy rate, again! The less time it takes them to spot items matching their requirements, the more you can count on them clicking the “Buy” button.

This could be especially useful for luring impulse buyers to your store since the less time it takes to find something they want and go through the checkout, the more likely they will complete the purchase.

Increases your revenue

Lastly, tweaking how the search engine ranks products in the store can boost your revenue in several ways.

The first is personalized search results for each visitor, which can make a massive difference in the user experience and sales. Rather than have to browse multiple pages or change their search terms to find the right products, visitors can see “best for me” items at the very top of the results list. That makes the visitors feel like you understand their needs perfectly, making them more likely to buy from you. Happier customers = more likely to return to your store = more sales.

But there are also a few other ways in which you can boost your store’s revenue through product rankings:

• Promoting specific product categories or brands inside relevant results pages (for example, seasonal products) to boost sales of those.
• Giving customers a great shopping experience and thus convincing them to return to your store – helps them get to their desired products more efficiently without the need for endless scrolling through several pages and placing the right products right at the front.
• Using the information from the search engines to create personalized product recommendation boxes to raise the average order value

As the product search and Google SEO criteria overlap in many places, improving your product descriptions and keywords can also improve your position in Google search rankings. This can boost your visibility in organic search results, giving you more external traffic and possibly more organic sales.

Challenges of implementing product ranking systems and solutions

Implementing product ranking systems in e-commerce stores can be challenging due to various factors:

Data quality and quantity

E-commerce stores often have vast amounts of data, including product information, customer behavior, and transaction history. However, ensuring the quality and relevance of this data can be challenging. Incomplete or inaccurate data can lead to poor ranking decisions.

Solution:

Implement data cleansing and normalization processes to ensure data accuracy and completeness. Utilize data validation techniques and invest in data enrichment services to enhance the quality of your data. Additionally, consider leveraging user feedback mechanisms to improve data quality continuously.

Algorithm selection and tuning

Choosing the right ranking algorithm and fine-tuning its parameters to optimize performance can be complex. Different algorithms may be suitable for different types of products or user behaviors, and finding the optimal combination requires careful experimentation and analysis.

Solution: 

Conduct thorough algorithm evaluation and benchmarking to identify the most suitable algorithms for your specific requirements. Utilize A/B testing and machine learning techniques to iteratively refine and optimize your ranking algorithms based on real-world performance data.

Real-time processing and scalability

E-commerce stores often need to process large volumes of data in real-time to provide timely and relevant product recommendations. Ensuring the ranking system can scale efficiently to handle increasing traffic and data volumes is crucial.

Solution: 

Invest in scalable infrastructure and cloud-based services that can handle the computational demands of real-time data processing. Utilize distributed computing frameworks and caching mechanisms to improve system performance and responsiveness. Additionally, consider implementing load balancing and auto-scaling techniques to adapt to fluctuating demand.

Future trends and innovations in product ranking

The landscape of product ranking is continuously evolving, influenced by technological advancements, consumer behavior, and market dynamics. E-commerce platforms can develop more intelligent, personalized, and trustworthy product ranking systems that enhance the user experience and drive business success. Here are some of them:

Visual search

Visual search technologies allow users to search for products using images rather than text. Advanced image recognition algorithms will analyze visual content and match it to relevant products in the inventory, providing a seamless and intuitive search experience.

Voice commerce

With the increasing adoption of voice-enabled devices and virtual assistants, voice commerce is poised to become a significant trend in e-commerce. Ranking algorithms must adapt to voice-driven search queries and provide concise and relevant product recommendations tailored to spoken language patterns.

Multi-modal recommendations

Future product ranking systems will leverage multiple data modalities, including text, images, audio, and video, to provide more comprehensive and engaging recommendations. Multi-modal algorithms will analyze diverse data types to understand user preferences better and deliver more diverse and personalized product rankings.

Contextual ranking

Future ranking algorithms will consider a broader range of contextual factors, such as user location, weather, and social trends to provide more relevant and timely product recommendations. Context-aware ranking will enable e-commerce platforms to deliver personalized experiences tailored to users’ current context and needs.

What can Luigi’s Box do to enhance and personalize your product ranking?

If you want to enhance how your e-commerce search engine ranks the products at your store to help your visitors find the right products, then there are a few things you can do.

1. You can do your own research and optimize your target keywords yourself. If you look at the phrases and words that searchers often use to search for given products, that should make it easier to find the most relevant keywords for each product. Completing the product descriptions, adding better quality images, and making relevant online reviews visible under the products can also help search engines rank the products better.
2. You can also make all those tasks easier and faster with solutions like Luigi’s Box.

Luigi’s Box can help you enhance your visitors’ search experience on your page thanks to its abilities to:

• Predict visitors’ search and purchase intentions and automatically create personalized listing pages for them
• Update the rankings based on visitors’ previous purchase history and store behavior
• Recognize and correct typos to lead visitors to the right products
• Allow you to set your own ranking rules (for example, to promote seasonal products)
• Show personalized product recommendations to each visitor.

With those features, you can make it easier for your store visitors to find what they’re looking for—and in seconds. As the product ratings and search listings will be updated in real-time, you can be sure that your visitors will always find the most relevant products at the top of the results.

Luigi’s Box Analytics

In addition to that, Luigi’s Box provides an analytical tool that will give you valuable insights to grow your e-commerce store further with advanced features like:

• Tracking trending relevant keywords and products (seasonality and trends)
• A/B testing to evaluate the impact of changes to product ranking algorithms (offline and online versions)
• Tracking user interactions with the e-commerce platform to gain insights into user preferences, intent, and shopping patterns
• Identifying high-performing products that deserve higher rankings and underperforming ones that may need adjustments
• Delivering tailored recommendations by analyzing user data to understand individual preferences and behavior

and more

That way, you can find out how to optimize your store to attract more customers and raise your revenue.

Conclusion

With e-commerce stores often offering thousands of items, it is essential to help users find the right ones without forcing them to scroll through several pages if you want them to return and spend more. That’s the job of product ranking – to place the right products at the front, where visitors can easily find them. And if you combine some of the best ranking tips with Luigi’s Box, you can quickly guide your customers to the right product.

You can set up the product rankings in any way you wish, and then the Luigi’s Box search algorithm will match the right items with the right visitors and create a personalized results list for each of them. Less time spent searching = happier and more eager-to-buy customers = more sales for you. And that’s precisely what you want, right?

What is product ranking FAQ