Automated vs Manual: Battling Approaches to Related Products

Boris Kwemo

31 Oct 23
Reading Time: 7 min

In the ever-evolving eCommerce landscape, the importance of a well-optimized product detail page cannot be overstated. As the heart of any online shopping site, these pages not only offer information but also influence buying decisions. Shopify brands, in particular, have been exploring various ways to maximize the potential of their product detail pages. One of the main debates is whether to adopt automated or manual approaches when it comes to displaying related products.

At ConvertMate, we have been helping Shopify brands navigate this intriguing dilemma while optimizing their product descriptions using advanced data analysis and Artificial Intelligence. In this blog post, we delve into the intricate world of related products, exploring the pros and cons of both automated and manual methods. Our goal is to shed light on the most effective strategies to boost your Conversion Rate Optimization (CRO), ultimately enhancing your eCommerce performance.

Understanding Related Products

Defining Related Products

In the world of eCommerce, related products play a crucial role in enhancing the shopping experience, boosting sales, and increasing the average order value. Related products are essentially those items that complement the main product that the customer is viewing or purchasing. For instance, if a customer is looking at a book on an online store, the related products could be similar books by the same author, or other books in the same genre. This not only offers the customer more choices but also encourages additional purchases, thus boosting the conversion rate.

There are two primary approaches to defining related products: manual and automated. The manual approach involves manually selecting and assigning related products for each item. This method provides a high level of control and precision but can be labor-intensive and time-consuming, especially for large eCommerce stores with a wide range of products. Conversely, the automated approach uses algorithms to automatically identify and suggest related products based on factors such as customer browsing history, purchase history, and product characteristics. Though it may lack the precision of manual selection, it offers increased efficiency and scalability.

In the battle between automated vs manual approaches to related products, the ideal choice depends on the specific needs and resources of your eCommerce business. A smaller online store with a limited product range might find the manual approach more feasible and beneficial, whereas a large online retailer with an extensive product catalog might lean towards the automated approach for its convenience and time-saving benefits. However, a blend of both approaches, where automated suggestions are refined with manual oversight, may provide the best balance between efficiency and accuracy.

Importance of Related Products in eCommerce

In the thriving world of eCommerce, the concept of related products is a vital marketing strategy that can significantly impact conversion rates. By understanding and effectively utilizing related products, online retailers can provide a more personalized shopping experience, boost average order value, and cultivate customer loyalty.

Related products are essentially items that complement, supplement, or are similar to the product currently being viewed by a customer. For instance, a customer shopping for a laptop might be presented with related products like a laptop bag, a wireless mouse, or even a different model of laptop. The goal is to tempt the customer with additional purchases or alternatives that they might find interesting or useful.

The key to implementing a successful related products strategy lies in the battle between automated and manual approaches. While an automated system uses algorithms and data analysis to generate related product suggestions, a manual approach requires retailers to handpick each related product. Both methods have their advantages and pitfalls, and finding the right balance for your eCommerce store can be a game-changer.

Automated Approach to Related Products

What is Automated Related Products

Automated related products is a feature often used in ecommerce to boost sales and improve the customer experience. This feature usually works by analyzing customer browsing and purchasing habits, using algorithms to suggest items that other customers viewed or purchased alongside the one a customer is currently viewing. The idea is to present customers with products they may not have thought to look for, increasing the chances of cross-selling or upselling.

Automating this process can have several advantages over a manual approach. For one, it saves time and effort - rather than painstakingly selecting related products for each item in your inventory, the software does the job for you. More importantly, it can provide more personalized recommendations. Because the suggestions are based on customer behavior, they are likely to be more relevant and appealing to the individual customer, which can lead to higher conversion rates.

However, it’s important to note that the quality of automated related products largely depends on the sophistication of the software. Basic algorithms might simply suggest the most popular products, while more advanced ones could take into account factors such as the customer’s past purchases, browsing history, and even demographic information. As an ecommerce store owner or marketer, it’s crucial to choose a system that suits your needs and delivers the most value to your customers.

Benefits of Automated Related Products Approach

The benefits of an automated approach to related products are numerous, especially when considered in comparison to the manual method. One of the most significant advantages is the efficiency it brings to the process. Unlike the manual method, which requires regular updates and adjustments, an automated system can consistently suggest related products based on the customer’s search or purchase history, ensuring a smooth and continuous shopping experience.

Furthermore, an automated related product approach is powered by algorithms that can analyze vast amounts of data in real-time. This allows for more accurate and personalized recommendations, improving the conversion rate significantly. As an ecommerce store owner or marketer, you might find the time and resources saved through automation to be invaluable, allowing you to focus on other crucial aspects of business growth.

Finally, the scalability automated systems offer cannot be overstated. As your ecommerce business grows, managing related product recommendations manually might become overwhelming and unmanageable. On the other hand, automated systems can effortlessly handle increasing amounts of data, ensuring your store’s performance remains optimal despite the growth. Thus, investing in an automated related product approach not only enhances your store’s present performance but also prepares it for future expansion.

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Manual Approach to Related Products

What is Manual Related Product Selection

The manual approach to related products is a hands-on method used by ecommerce store owners to categorize and display products that complement each other. In this approach, the store owner or marketer personally chooses which products should be shown as related items. While this might seem time-consuming, it offers a level of precision and personal touch that can be appealing to some customers. The ability to personally curate and group products based on an intimate understanding of your inventory is a key strength of the manual method.

However, manual related product selection has its drawbacks. The process can be labor-intensive and time-consuming, especially for larger inventories. Additionally, it lacks the ability to adapt to changes in customer behavior and preferences in real time, which can affect the relevancy of the suggested products. This method also runs the risk of human error and bias, which could lead to missed opportunities for upselling and cross-selling.

In the battle between automated vs manual approaches to related product selection, each has its strengths and weaknesses. Ultimately, the choice between the two methods should be based on the unique needs and capabilities of your ecommerce business. Consider factors such as the size of your inventory, the resources you can devote to product selection, and the complexity of your customers’ buying patterns.

Advantages of Manual Related Products Approach

The manual approach to related products may seem outdated in the digital age, but it holds many advantages that can drastically increase your conversion rate. One of the most significant is the level of control this method offers. Unlike automated systems, which rely on algorithms to suggest related products, the manual method allows you to personally select and adjust the recommendations displayed to each customer. This means you can take factors like current market trends, seasonal relevance, or the customer’s past purchases into account to provide highly personalized suggestions.

Another key advantage is the potential for nuanced decision-making. Algorithms can’t inherently understand the subtle connections between products that humans can. They might miss the opportunity to cross-sell a product that doesn’t seem ’related’ in the strictest sense but would nevertheless appeal to the customer based on their expressed interests or needs. In the manual approach to related products, you as the ecommerce store owner or marketer can leverage your understanding of your products and your customer base to curate a more appealing selection.

Finally, the manual method is less likely to make errors in product suggestion, which could cost you a potential sale. Automated systems, although generally accurate, can sometimes make inappropriate or irrelevant recommendations due to glitches or incorrect data. In contrast, the manual approach to related products offers you the opportunity to review and refine your suggestions, reducing the risk of any mishaps. While it may require more work, the increase in conversion rates may well be worth the effort.

Comparing Automated and Manual Approaches

Differences between Automated and Manual Approaches

When it comes to managing related products on your ecommerce platform, two main approaches are often considered: automated and manual. The automated approach leverages algorithms to analyze shopping behaviors, product relationships, and customer preferences to suggest related items. On the other hand, the manual approach relies on human input where related products are personally chosen and added to each product. This approach gives more control over what products are displayed as related, but it can be extremely time-consuming.

The automated approach is favored for its scalability, efficiency, and advanced technology. It can analyze large amounts of data, understand patterns, and make recommendations accordingly, which is a massive advantage for larger stores with a high volume of products. It also allows for a personalized shopping experience as the recommendations are based on the customer’s browsing history and buying patterns. However, the downside is that you relinquish control over what products are suggested, which could lead to irrelevant recommendations if the algorithm isn’t fine-tuned.

Opting for the manual approach means choosing precision over efficiency. Ecommerce store owners can handpick the products they want to upsell and cross-sell, ensuring that the recommendations are always relevant. This method is particularly useful for smaller stores that have a more focused range of products. However, it can be a labor-intensive process, especially when changes need to be made to the catalog. Moreover, the static nature of manual recommendations may not provide the dynamic, personalized experience that today’s online shoppers expect.

Which Approach Works Best for Your Business

Deciding between automated and manual approaches to related products is a crucial decision for ecommerce store owners and marketers. Both methods have their unique benefits and drawbacks, and understanding these can help in choosing the right approach for your business.

Automated systems use algorithms to suggest related products based on customer behavior and purchase history. They can handle large amounts of data and provide results in real time. However, these systems can sometimes miss subtle connections between products that humans might easily pick up on. They may also fail to adapt quickly to changes in trends or customer behavior.

On the other hand, manual curation allows for a high level of control and customization. It lets you draw connections between products that an algorithm might miss. However, it can be time-consuming and may not scale well for larger ecommerce sites. Furthermore, the success of this approach heavily relies on the curator’s understanding of the products and the target market.

Ultimately, the choice between automated and manual approaches to related products depends on the specifics of your business. If your ecommerce store has a large inventory and a diverse customer base, an automated system might be more suitable. However, if your store focuses on a niche market and has a smaller inventory, a manual approach could yield better results. It’s also worth considering a hybrid approach, which combines the strengths of both methods and may provide a balanced solution to the issue.

Optimizing Related Products with ConvertMate

How ConvertMate Can Enhance Your Related Products Strategy

When it comes to optimizing your related products strategy, choosing between automated and manual approaches can be daunting. This is where ConvertMate can enhance your overall strategy. ConvertMate offers a streamlined and efficient way to manage and manipulate related product recommendations, giving you full control over what items are shown to your customers.

One of the key advantages of using ConvertMate is that it allows you to manually select related products, rather than relying on an automated system. This means you can select items that are more likely to lead to conversions, based on your understanding of your customers and their buying behavior. This manual approach might be time-intensive, but it provides a greater level of customization and accuracy, ensuring the most relevant products are shown to your clients.

On the other hand, if you’re running a large ecommerce store and requires a more automated approach, ConvertMate can help too. With its robust algorithm, it can intelligently select related products that are likely to be of interest to your customers, based on their browsing history and previous purchases. This saves you time while still providing a personalized shopping experience for your customers. In conclusion, ConvertMate offers the best of both worlds and can significantly enhance your related products strategy.

The Role of AI and Data Analysis in Optimizing Product Descriptions

The role of Artificial Intelligence (AI) and data analysis in optimizing product descriptions cannot be overstated. The process of manually writing and optimizing product descriptions can be tedious and time-consuming. However, with AI and data analysis tools such as ConvertMate, this process can be automated, saving you time, reducing the margin for error, and driving a more consistent and effective approach.

AI-powered tools assess your product information and generate optimized descriptions that are unique, SEO-friendly, and engaging. They can analyze vast amounts of data to determine what type of language, keywords, and structure work best for your target audience, leading to better visibility of your products and ultimately, higher conversions.

ConvertMate takes it a step further by also optimizing related products. The system analyzes the purchasing patterns and preferences of your customers to recommend related products in a more personalized and intelligent manner. This way, each customer sees products that are most likely to interest them, boosting your chances of cross-selling and upselling. It's a key advantage in the battle between automated and manual approaches to related products, providing a more efficient, targeted, and profitable strategy.

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