6 Tips to Enhance Your Product Catalog Data

6 Tips to Enhance Your Product Catalog Data

One of the most important keys to succeeding in online retail is to know your audience. Today’s buyers – mainly Millennials and Gen Zs – have a pretty short attention span. If they can’t find the product they are seeking on your website within seconds, they will quickly move on to a different website. You need to capture your browser’s attention immediately and lead them to the exact product they are seeking as quickly as possible.

How can you enhance your product catalog data?

1. Study your audiences and their locations

Your catalog’s data should be suitable for all your sales channels and worded attractively to engage your target audiences. Start by defining your potential customers. Once you have done so, adjust your content, style and graphic presentation to suit their tastes. Where do they spend their time? On the Internet or perhaps on a form of social media? Attract their interest wherever they are located with marketing campaigns and Facebook ads.   

2. Provide detailed and consistent data

Most online purchasing is based on comparisons. Buyers compare products and prices before deciding where to make their purchase. Potential customers dislike comparing “apples to oranges”. In order to make accurate comparisons of the same products, buyers need to be able to view easily available, consistent and detailed product data.

3. Use product tagging

Make searches simple on your website by using product tagging. When you assign keywords to products, the system automatically brings up viable associated options that can help facilitate sales. By making all your products easily findable, you provide a productive and smooth customer journey.

4. Keep SEO and customer logic in mind

Your catalog’s structure must be adapted to your target audience’s search habits. In other words, think like your customer. Go from the broadest level to the narrowest one, but keep your main potential buyer in mind. For example, if you sell running shoes for athletes, you might start at “shoes”, move on to “athletic or sports shoes” and then narrow down to “running shoes.” The structure and related keywords should reflect the way your customers go about their search.

5. Automate inventory and product updates

Consider the following scenario: A potential buyer has conducted a search on your website and found the product he or she is seeking, only to discover that it is no longer available. The consumer will leave your website, most probably never to return. In order to offer an updated online catalog, you must dynamically refresh product data and inventory modifications. An automated AI-based catalog system prevents human error and updates data constantly.

6. Use creative design to snag buyers

While engaging copy and updated data are crucial, product presentation is no less important. Exciting design can greatly enhance your catalog’s data. Videos, product demos, interactive lookbooks and 3D simulations are likely to leave a memorable impression, and bring customers back for more.

Interested in learning more about how you can enhance your product catalog data? Click here.

5 Reasons Why Category Level Insights Are Crucial for Your Online Business

5 Reasons Why Category Level Insights Are Crucial for Your Online Business

When planning your online catalog, you need to take several central factors into consideration: Firstly, your online catalog is your showplace, and as such it must captivate your visitors as soon as they enter your website. Secondly, you must provide the information potential customers are seeking accurately and clearly. Thirdly, the data about products must be easily accessible. And finally, in contrast to physical stores, there is no sales staff to explain the pros and cons of various products or demonstrate how they are used. So your catalog must provide easily understood specifications and descriptions.

Our 5 insights you stand to gain from an optimized Product List Page

1. Learn how to attract your target audience

One of the most important ways to attract your audience is through the use of the right keywords. For example, if you sell rings, make sure to place them all on a single page rather than spread them out. Optimize the category by using different keywords for each type of ring – for example, diamond rings, ruby rings, antique rings, etc. This way, you will bring in the right traffic through search engines. This type of category structure enables you to gain insights regarding the popularity of various items and better ways to promote others. 

2. Gather information from your customer

You can acquire valuable insights by consulting with your customers regarding how they feel about your catalog. Ask them for ratings and comments under each product listing. Find out if they would recommend your website/product to a friend, and if not, why. Enable them to share your pages on social media, and take note which media they prefer for future engagement. The category structure enables you to drill down to gain insights about specific products. 

3. Manage your inventory wisely

Insights on the category level contribute to intelligent inventory planning. By gathering data about sales volumes in each category and sub-category, you can make accurate predictions about future sales and order stock accordingly. This information prevents costly overstocking and also eliminates the kind of understocking that frustrates potential customers. 

4. Test your visual presentation

According to some marketing experts, 93% of consumers consider visual appearance to be the key deciding factor in a purchasing decision. Due to the fact that end customers are unable to feel or try on online products, it is crucial to provide high-quality, enticing visuals that will captivate your buyers. Provide as many views of the product as possible so that potential customers can get a real feel of the item. Some automated catalog platforms provide tools to automatically detect which images are optimal, based on the standards of each retailer or brand. You can check if a certain category is performing poorly because of low-quality images and make the presentation more exciting.

5. Facilitate the customer journey

What are the steps that your potential buyer takes before making a purchase? Whether the customer starts browsing on a smartphone, a tablet or on your online website, you should maintain consistency across channels, enabling you to offer a strong and enjoyable omnichannel experience. Follow your customers’ footsteps across channels and determine which categories were visited at each location. Based on this data, create special personalized offers on products in categories that are the most popular, and provide incentives in categories that are less popular in certain channels.

Want to learn more about how category level insights can boost your sales? Click here.

How to Boost Product Classification With AI

How to Boost Product Classification With AI

Here’s the golden rule for every online enterprise or marketplace: Your online catalog must always be up-to-date and search friendly, despite the rapid influx of inventory and fluctuation in product availability. That is easier said than done, especially if you handle a wide variety and large volume of products from different countries. 

Well-organized product categorization and classification are key to your website’s traffic and customer search engine, but also contribute significantly to your logistics and operations behind the scenes. In order to prevent costly errors due to faulty product classification, you need an AI-based platform that automatically and accurately categorizes merchandise. 

What is Product Classification

Product classification is a crucial process for any eCommerce business. It involves categorizing products based on their attributes, such as size, color, and material. However, manually classifying products can be time-consuming and prone to errors, which is where AI comes in. In this blog post, we’ll explore how AI can boost product classification and help eCommerce businesses save time and improve accuracy.

Use machine learning algorithms

One of the most effective ways to boost product classification with AI is to use machine learning algorithms. These algorithms can learn from existing product data and use that knowledge to classify new products automatically. For example, an algorithm could learn that a certain set of attributes is associated with a particular product category, such as shoes, and then use that knowledge to automatically classify new shoes based on their attributes.

Train your AI models

To get the most out of AI for product classification, it’s important to train your AI models on a large and diverse set of data. This can include product images, descriptions, and other attributes. The more data your AI models have to learn from, the more accurate they will be at classifying products.

Incorporate natural language processing

Natural language processing (NLP) is a branch of AI that can help improve product classification by analyzing and understanding text-based product descriptions. By using NLP, AI can automatically extract relevant product attributes from product descriptions and use them to classify products more accurately.

Use image recognition

Image recognition is another powerful AI technology that can be used to boost product classification. By analyzing product images, AI can automatically identify product attributes such as color, shape, and pattern. This can help improve the accuracy of product classification and reduce the need for manual intervention.

Integrate with your eCommerce platform

To get the most out of AI for product classification, it’s important to integrate it with your eCommerce platform. This can help automate the classification process and reduce the need for manual intervention. For example, an AI-powered product classification system could automatically categorize new products as they are added to your eCommerce platform, saving time and improving accuracy.

What are the benefits of AI-powered product classification? 

Empower accurate product mapping

In order to ensure accurate product mapping, you must first create organized product groups. This means forming macro-categories (dresses, for example) and micro categories that logically fall underneath the main category (casual dresses, summer dresses, etc). AI-powered product taxonomy enables accurate macro and micro categorization predictions based on category ID and taxonomy tags. Product classification using machine learning prevents costly manual mistakes.   

Optimize tariff classification and customs compliance

When dealing with a large volume of products from numerous countries and various retailers there is much room for error. An AI-based system has the ability to use data such as manufacturer, product description and other input to automatically ensure customized classification and accurate tariff codes. The machine-learning classification module can be modified based on each country’s code in the Harmonized Commodity and Coding System, facilitating faultless shipments to customers worldwide.  

Recommend products based on past customer experiences

AI-based classification can be used to recommend new products based on a customer’s past browsing and purchase history. Today’s customers desire personalized content and special offers based on their individual preferences. AI-categorization, which provides actionable insights, enables the delivery of individualized messages. This machine learning tool is used by large businesses like Netflix and Spotify. 

Correlate crucial data of different classes

Aside from the ability to match data within a given class, AI-based techniques also enable the correlation of data from different classes that share association. Machine learning integrates meta-data analysis to achieve a deeper understanding of data. This input enables more discerning automatic cataloging for easy discovery through search. By combining in-depth classification and correlation capabilities, AI provides enterprises with the tools to locate, inventory and map crucial data.

The days of manual categorization for online catalogs are long gone. With inventories counting tens of thousands or even millions of products, most large enterprises are transitioning to automated AI-based platforms to ensure consistency, prevent duplications, and increase customer traffic. 

4 Tips for Online Marketplace Architecture With Extensive Catalog Data

4 Tips for Online Marketplace Architecture With Extensive Catalog Data

Establishing a successful marketplace model can be challenging. You will obviously need to generate buyer interest in your platform, but a successful marketplace platform also necessitates interconnection between your vendors and users, as well as engagement with the products and content presented within.

Your marketplace’s operation is dependent on a growing user base and a continuously updated catalog. A thriving platform relies on well-designed online marketplace architecture. Actionable data is key to your architecture’s effectiveness. 

How rich catalog data boosts the success of your marketplace architecture: 

Real-time data to enable growth

For an online marketplace framework to succeed, it must possess the ability to onboard vendors and products continuously while maintaining accuracy and customer trust. You need to provide consistent and complete data about products sold by each of your vendors, even though they fluctuate regularly.

How to go about it: 

AI-based marketplace APIs enable you to acquire complete product intelligence on each and every item in real-time. In addition, a Product Identification API gathers a list of products that match a search term, allowing grouping of identical and similar items as well as sorting by demand.    

Prevent mismatching and disgruntled customers

Sometimes different vendors provide incomplete data about their items, leading to customer frustration and abandonment. It is crucial to provide all of the most relevant product information consistently in order to enable accurate product identification and easy comparisons.

How to go about it:

Neural network modelling automatically captures both similarities and differences, enabling effective e commerce marketplace management. Regardless of the type of data provided by the vendor, you are able to feature a complete set of information about each product, boosting sales and customer loyalty.

Ensure prices are within range

At times, vendors set product prices outside of the current price range. This kind of overpricing must be avoided as it can put off customers permanently. However, keeping up with fluctuating prices is a difficult task considering the huge inventories handled by marketplaces.  

How to go about it:

Smart outlier detection techniques enable the identification of vendor set prices that are outside the current range. Using AI-based price modelling tools, automated pricing can be applied to products as they are being uploaded by vendors. 

Display products based on demand

Sometimes, the customer may not have the precise name of the product they are looking for. As a result, they may just search for the name of the brand rather than the exact item they want. In order to boost sales and increase customer satisfaction, items in demand must be displayed prominently on the product page. But how can you tell which products are most relevant at any given time?

How to go about it: 

Using specific search criteria, machine learning algorithms enable the ongoing ranking of products based on demand and attractiveness. The items that have the greatest appeal for the buyer will be displayed prominently based on a confidence score. According to research, accurate product assortment leads to a 5% increase in the add-to-cart ratio.   

To learn about additional ways extensive catalog data can enhance your online marketplace architecture, schedule a demo now.  

How to Facilitate Seller Onboarding on Your Marketplace

How to Facilitate Seller Onboarding on Your Marketplace

Attracting new sellers to your marketplace is a huge challenge, but onboarding is what clinches the deal. In order to effectively incorporate new sellers and ensure ongoing satisfaction, it is crucial to ensure a seamless seller onboarding process, ongoing user support and easy website management. 

When building your marketplace, you must first identify your target audience and then locate the best channels to reach them. A deep understanding of your potential vendors, as well as their concerns and interests, will enable you to formulate the right messaging to bring them aboard. 

How can you facilitate marketplace onboarding?

Convince vendors that it’s worthwhile

Your first task is to convince online sellers that your marketplace will make life easier for them. Describe how your platform promotes operational control through integration with their existing solutions as well as built-in features such as easy inventory management, order management and an array of payment possibilities. Meet the needs of a variety of vendor types by offering specialized plugins and extensions.

You can also partner with 3rd party product intelligence solutions to quantify the sellers’ opportunity of selling their specific inventory on your marketplace.

Automate your processes

In order to ensure fast scaling of your marketplace, automate as many of your processes as possible. Support should not be dependent only on a manual team. Provide precise explanations for each stage as well as short FAQs to prevent dependency on auxiliary manpower. 

Facilitate the seller registration process

When it comes to onboarding, set up a designated, user-friendly page that includes all the required registration steps and specifies the types of documentation needed. Add a link to the page on your website and in the navigation menu to enable easy access. 

Provide concise training modules 

Rather than grinding out long training guides, prepare short training videos for each of the onboarding stages. You can also prepare an interactive walkthrough, accompanying sellers step-by-step through the process. This makes the training process more palatable and easier to grasp. Short instructional videos can be prepared for each of the back office tasks. 

Offer user-friendly templates and DIY tools

While smooth initial registration is important, that is only the first step. Provide your vendors with user-friendly tools to easily upload special offers, ads, images and information. In addition, enable them to easily integrate with your built-in features such as payment and billing systems.

Enable automatic enrichment of catalog data

The prospect of manually uploading hundreds of thousands of products is daunting and susceptible to human error – especially if you require complete item data. An AI-based product intelligence/marketing analysis platform enables automated cataloging of new products, product data enhancement, and accurate product identification in real-time. The ability to provide consistent data about the vendor’s fluctuating range of products is not only crucial during onboarding but also on a daily basis.

Want to effectively facilitate your onboarding process? Contact us today.

Top Product Data APIs eCommerce Marketplaces Can Offer Their Partners

Top Product Data APIs Ecommerce Marketplaces Can Offer Their Partners

The ability to acquire, manage and utilize product data is crucial to the success of your marketplace. Marketplace operators are currently being offered a wide range of eCommerce APIs. What do the best eCommerce platform APIs have to offer and which of these are most suited to your needs?

Leading enterprises such as Amazon, Walmart and eBay have developed outstanding eCommerce APIs. Let’s take a look at their features and understand how your marketplace can benefit from them.

What are product data APIs?

Product data APIs are a powerful tool for eCommerce businesses that allow them to access product information and other relevant data from a variety of sources. Essentially, an API (Application Programming Interface) is a set of protocols that enable different software applications to communicate with each other. In the context of eCommerce, product data APIs allow businesses to easily access product information, including price, availability, and other relevant data, from a variety of sources, such as suppliers or other eCommerce platforms.

Benefits of product data APIs for eCommerce marketplaces

Improved efficiency

One of the primary benefits of using product data APIs is improved efficiency. By automating the process of accessing and updating product information, businesses can save time and reduce the risk of errors. For example, instead of manually entering product data into your eCommerce platform, you can use a product data API to automatically import product information from a supplier’s database. This can save a significant amount of time and resources, allowing you to focus on other areas of your business.

Enhanced customer experience

In addition to improving efficiency, product data APIs can also help enhance the customer experience. By providing accurate and up-to-date product information, businesses can improve the customer’s online shopping experience, leading to higher conversion rates and increased customer loyalty. For example, if a customer sees that a product is out of stock or has an incorrect price, they may become frustrated and abandon their purchase. By using a product data API, you can ensure that your customers always have access to accurate and up-to-date product information, improving their overall experience with your brand.

Increased profitability

Product data APIs can also help increase profitability by providing businesses with valuable insights into product performance and trends. By analyzing data from a variety of sources, businesses can identify which products are selling well, which products are underperforming, and make data-driven decisions to optimize their product offerings. Additionally, by automating the process of accessing and updating product data, businesses can save time and resources, allowing them to focus on other areas of their business, such as marketing and customer service.

Amazon’s Product Advertising and MWS API 

With 310 million monthly users, Amazon has massive appeal for sellers and buyers alike. Free Amazon MWS data can be used to create listings, fetch orders, get payments, produce reports, and more. MWS API data enables sellers to increase selling efficiency, reduce manpower expenses, and improve response time. By studying eCommerce data attributes, applications can be developed to list products for sale, set product prices, retrieve information for order fulfillment, generate reports, and more. 

The Amazon Advertising API automates scales for affiliates, and optimizes advertising results. This API yields campaign and performance data for sponsored products, brands, and display, with programmatic access for campaign management. Advertisers have the ability to manage ads or ad groups based on predefined conditions.

Walmart’s Open API

The Walmart Open API provides access to the marketplace’s extensive product catalog, thereby enabling digital distribution partners to earn affiliate revenues from customer referrals. Walmart is very restrictive in providing access to that API and it’s nothing but open.

Developers can utilize a variety of APIs to acquire crucial Walmart API data, promote sales, and improve the user experience:

Lookup API –  This product price API features the price and availability of each item. 

Search API  – This product lookup API enables a text search to be conducted on the Walmart.com catalogue, which returns matching products on sale. 

Taxonomy API – This API reveals Walmart.com’s category taxonomy which is used to categorize items.

Trending API – This eCommerce API features trending items on Walmart.com.

Reviews API – This API provides user reviews of products.

eBay’s Buy and Sell APIs

eBay currently has 177 million active monthly users. Its free Sell APIs provide sellers and third-party developers with all the capabilities needed to manage the vendor’s end-to-end eBay business. Sell APIs are focused on product catalogs (structured data), inventory on-boarding, and management capabilities. It employs a SKU-driven approach to manage purchase orders, fulfillment and returns. 

eBay’s Buy APIs enable vendors to create buying experiences outside of the eBay.com site. Users can search for, select, and buy eBay items based on eBay API data. Sellers can mirror and display the contents of the items in an eBay category, provide marketing data to drive conversions, and track orders, all from within the seller’s own website. eBay’s Buy APIs offer shoppers the option to buy eBay sellers’ items at any location including social sites.

Optimal Data Synergy with the Cluster Platform

Our AI-based marketing analysis platform enables online vendors to achieve superlative marketplace performance by integrating seamlessly with a wide range of product data APIs. The platform constantly draws crucial data related to products, prices and competitive markets, enabling sellers to dynamically build automated product catalogs and display their wares to the best advantage. 

Cluster is a platform for eCommerce marketplaces, brands, retailers, and sellers. We leverage ML & AI technology that provides the Retail/eCommerce community with demand forecasting, competitive market share information across multiple platforms, improved product matching capabilities, catalog data enhancement, optimized catalog rankings based on demand analysis and data-driven pricing.

The core competency of our technology is the ability to identify every product available online based on user-generated content (for example, users on Facebook Marketplace listing their used products), build a complete and structured product entity with up to 300 attributes as well as its regional GTINs, identify the product offerings in various websites across countries and channels and extract market price, estimate and predict sales volume per channel and even provide accurate sales-related costs such as shipping, marketing, tax and VAT, etc.  

To learn more about marketplace optimization through seamless integration with Data APIs, book a demo now

Who Needs Market Price Benchmarking?

Who Needs Market Price Benchmarking?

Before we discuss WHO needs market price benchmarking, let’s first address WHY it is so pivotal. No retail business, whether online or in-store, is an island. In order to gain the traction to succeed, it is crucial to understand where your products’ prices stand in relationship to your competitors’. 

Market price benchmarking provides invaluable insight into several key issues: Where do your prices fall – are they above or below the average market price? What are your customers looking for and what kind of experience do they undergo in your shop? What makes your direct and indirect competitors’ offering appealing? Where can you fill in gaps that your competitors are missing?

Now that we understand why price benchmarking is vital, let’s see who can best profit from using this type of analysis:

Price Benchmarking for Online Enterprises

Online enterprises must constantly gauge the competition in order to gain an edge and boost sales. This process sounds easier than it actually is. Product prices are constantly fluctuating. New products are introduced to your inventory and other products are removed. Special sales are offered on competitive items. If you handle a large volume of products, keeping up with changing prices across the web is a formidable task. 

While this type of task may have been handled manually in the past, businesses can now use dynamic AI-based marketing analysis platforms to gain dynamic insights into product prices across the web in real time. Online retailers can instantly add or withdraw products, or make special offers on certain items, thereby outperforming the competition and attracting customers. 

Price Benchmarking for Brands

The main objective of most brands is to build a name and reputation for themselves. In order to do so, they need to offer a memorable and seamless customer experience that makes them stand out. Some brands operate their own websites, while others join a marketplace sales model. 

Market price benchmarking provides insights into direct and indirect competitors, i.e, companies that sell identical or very similar products to a brand. After carefully analyzing your target audience, make your brand conspicuous by launching special offers to certain buyers on products they have purchased in the past. Use market price benchmarking to personalize your offerings and create a lasting connection with your brand. 

Price Benchmarking for Marketplaces

Many marketplace owners use the commission model to claim fees from the businesses they work with. The fee may depend on whether the provider distributes products only through the marketplace or through other channels as well. Marketplaces do not want to price themselves out of the market, so in exchange for a sales spot, they should either offer lower fees or greater value to enterprises. Marketplaces also need to consider the different types of providers they host and if fees should be identical for all. 

Market price benchmarking provides clear insight into all of these dilemmas: Actionable data analysis enables marketplaces to compare prices across the board, gauge the competition’s offerings, and offer top value to providers. Through price benchmarking, marketplaces can create a sustainable business model with affordable fees and mutually acceptable profit margins.

The Ultimate Winner – The Customer 

Whether you are an enterprise, a brand or a marketplace, your primary goal is to engage new and veteran customers, and generate loyalty. Market price benchmarking can be combined with online catalog optimization to significantly increase traffic and streamline customer experiences. 

Interested in learning more about how market price benchmarking can work for you? Book a demo.

What Are the Benefits of Retail Segmentation?

What Are the Benefits of Retail Segmentation?

We live in a different world compared to only a few decades ago. Consumer research has become more complex and efficient, and clients have higher expectations than ever when interacting with their favorite retailers. 

No matter how big your store is, keeping up with current purchasing trends is essential to staying competitive in a rapidly-evolving marketplace.

In the past, retail stores used a “one-size-fits-all” approach that adapted slowly to changing demand. Thanks to new ways of collecting data through online usage statistics and buyer personas, we can now achieve more personalized ways to interact with our clients.

How Does Customer Segmentation in Retail Work?

Customer segmentation in retail often involves using point-of-sale systems to gather this information and divide customers into groups. First, broad categories are created that incorporate a large number of customers before they are split into smaller groups for more detailed analysis.

Some overlap among the groups is inevitable, but most businesses try to minimize it to ensure more useful data.

What Kind of Information Is Collected?

Retail tracking incorporates several types of data points that can help build a detailed buyer persona.

  • First interaction with your brand. How did the buyer discover your store (through social media, word of mouth, or otherwise?), and when did they become a customer? What was the first purchase, and what future products are they likely to buy? This information helps you build your onboarding strategy.
  • Method of browsing. Some customers just walk in and look through the store. Others use a variety of devices from desktops with web browsers to mobile devices. Find new ways to engage clients and see what you can do to make interacting with your business smooth and easy.
  • Location. Connect individual purchases with the clients’ postal codes to figure out regional shopping trends. It’s also an easy way to track the distance between you and your customers compared to your competition.
  • Income level. An inevitable factor in purchasing decisions, income level determines what products appeal the most to your buyers. Find out which specific items to advertise to what groups based on client budgets.
  • Demographic information like gender and age, which significantly impact purchasing activity. Men and women tend to have different shopping patterns, and younger customers are impacted more by online marketing than older ones.
  • Buying activity. On average for each group of customers, how many transactions do they make? How frequently do they visit? Can you consider them recurring shoppers?

There are other factors to consider as well. Find different metrics that can help you find exactly who shops at your store and what you can do to cater to them.

The Benefits of Segmentation for Retail

What’s the reasoning behind all this effort? Retail customer segmentation gives you actionable insights into what you can do to boost revenue for certain types of buyers.

  • By identifying trends in purchasing activity, you can pinpoint the seasonal buyers and target your sales and advertising to certain parts of the year.
  • Finding your most popular demographics gives you a chance to build more successful marketing initiatives by aiming for specific groups of customers and providing more relevant customer service.
  • Showing which types of clients pay full price vs. wait for a discount, which tells you when to time your sales for maximum effectiveness.

Customers are all different people. Addressing their individual, unique needs is the key to higher satisfaction rates.

What Better Metrics Can Do for You

Customer segmentation involves learning a lot about your clientele. Collecting transactional data, which is easier than ever with many cloud-based services, has several benefits:

  • Giving you a head start when it comes to scheduling sales and incentive programs.
  • Deciding on what products to feature depending on how well they sell for certain people.
  • Finding out what you can do for groups who aren’t buying as much.

Collecting metrics also lets you determine how successful you are. You might study the sales/profits per customer or how much your clientele demographics have changed over time. Are your efforts to appeal to more specific groups giving you a deeper understanding of why your customers choose your store?

All this happens regardless of whether you’re a brick-and-mortar shop or an online store that practices eCommerce segmentation.

The Takeaway: Retail Segmentation Creates Personalized Customer Experiences

Retail segmentation is the practice of collecting information on your customers and categorizing them into groups. Using factors like age, location, income level, and others, these groups have their own buying habits and preferences.

By focusing your sales and marketing on specific segments, you do a better job offering customized customer experiences. The result is more brand loyalty, better engagement rates, and more effective sales and rewards programs.

Retail segmentation is practiced by almost all stores and businesses, from small shops to large franchises and from physical stores to online ones. Get started today with a marketing team to get these benefits.

Interested in learning more about how retail segmentation can work for you? Click here.

5 Common Challenges of eCommerce Catalog Management

5 Common Challenges of eCommerce Catalog Management

It’s no secret that eCommerce is growing in profitability now that more and more buyers are shopping online. Stores must adopt eCommerce if they want to increase visibility and accessibility for their products. Today, an online presence isn’t optional—it’s essential.

But eCommerce doesn’t come without its own challenges. Companies must deal with large catalogs of hundreds or even thousands of products (SKUs). Every product must be identified and shipped quickly, and sometimes requires a bit of customization before it reaches the hands of the buyer. Businesses in this sector usually sell in multiple sales channels and marketplaces as well, further complicating the process.

This complexity ensures the importance of a consistent and efficient cataloging system. Without one, you risk incorrect or incomplete information leaking into your listings, frustrating customers and wasting company time that’s used to reorganize it. It’s time to look for a product identification solution, but what are some potential challenges you might face in doing so?

What Is Catalog Management in eCommerce and Why Does It Matter?

Catalog management occurs when suppliers must generate quality product data to describe accurately what a company is selling. This information must not only be accurate but also in the correct format for the target marketplace.

Having excellent catalog management results in:

  • More positive customer experiences since they can more easily find the items they want or search for what they need easily. The company can also make more accurate product recommendations this way.
  • Search engine optimization, as it helps streamline site navigation and product searching. More potential buyers will find your website this way.
  • Better product suggestions for cross-selling and upselling
  • Faster time-to-market since your business can update and expand the catalog more quickly. Reaching the customer in a timely fashion means more attention to your brand.
  • More accurate financial reporting, which also includes better inventory management and better timing for ordering new stock

Catalog management might be a feature of your business’s current enterprise resource planning (ERP) platform. But let’s talk about some challenges of catalog management first.

The Most Common eCommerce Product Catalog Management Challenges

What causes some managers to become frustrated with eCommerce product catalog management?

Updating Product Listings

Poor product catalog management makes updating your catalog a pain. The time you waste working with a badly organized catalog means a less efficient workflow. How do you tweak your management protocol to accept product or price changes in a timely manner?

Handling Multiple Sales Channels

Catalog management must efficiently support multiple online stores, such as Amazon and eBay. Each channel likely has a different system for accepting product specifications and categories. Tailoring your catalog data to each can take a long time, especially if the information is incomplete or messy.

Incorporating Third-Party Data

Your business often doesn’t write its own product data. It’s occasionally provided by a third-party supplier and thus may be in a different format or be missing certain attributes. Catalog management must involve cleaning up this data for your own use.

Expanding Your Offerings

When it comes to adding new products to your store, it’s more difficult to do so with a badly organized catalog. Developing businesses will find this issue especially worrying, as it caps how quickly the company can grow.

Complicated Structures of Products

Not all items “function” the same way. For instance, serialized items require an individual identifier for each unit. Company vehicles are an example.

You also may deal with different variations of the same product, such as offering multiple colors and sizes. Ensure your management can deal with special catalog items.

Addressing the Problem

How well a business handles eCommerce content management hinges on how it manages its data centrally. Smaller stores may use Excel, but this solution fails when dealing with larger catalogs. It also relies on human input, opening up the possibility for error.

There are eCommerce platforms available that offer either basic or advanced SKU management. Enterprise resource planning (ERP) platforms are popular amongst larger companies, as they work closely with your financial reporting sector. Such a solution handles updating prices, publishing to new markets, and working with inventory.

Another solution for eCommerce product catalogs is the PIM, or product information management platform. These services are specifically for handling product data, including uploading and publishing it to multiple sales channels. However, PIM can be expensive for enterprises, so it’s up to you to decide whether it’s worth the investment.

Regardless of what solution you choose, make sure it serves your needs. For instance, can you import and publish the data to all the marketplaces you use? Can the tool be used for inventory fulfillment? And does it automate the process effectively. Using artificial intelligence to streamline catalog management is one of the leading trends in eCommerce.

Are you trying to identify and enhance your product catalog, but only have basic information from your supplier? Algopix helps online brands validate and enhance their catalog data to fill in the gaps. 

Learn more about how eCommerce catalog management can improve your catalog data and improve your conversion rates. Boom a demo now.

Uncovering Insights: How to Get the Most Out of Your Amazon Data

Uncovering Insights: How to Get the Most Out of Your Amazon Data

Amazon is a powerhouse in the online retail world. With its vast array of products and services, it is no surprise that Amazon is the go-to platform for many businesses to get their products or services in front of the right customers. However, it can be challenging to understand how to effectively use Amazon to its fullest potential when it comes to leveraging data and gaining insights about customer behavior.

At Cluster, we understand that as a business owner, you want to make the most of your online presence. In order to do so, it’s important to have a deep understanding of how your competitors are performing on platforms like Amazon. That’s where our Amazon Insights tool comes in.

Why Analyzing Amazon Data is Important

Analyzing Amazon data provides valuable insights that can be used to optimize your Amazon business. It can help identify areas of opportunity, uncover customer preferences, and inform strategic decisions. By understanding your data, you can make informed decisions on how to best grow and optimize your business.

For example, analyzing your Amazon data can help you identify products that are underperforming, as well as identify which products are most popular with customers. This knowledge can help you make decisions on which products to prioritize, as well as which products to discontinue or improve.

Analyzing Amazon data can also help you understand customer behavior, such as which products customers are searching for, how often they are returning to your store, and how long they are staying on your website. This information can help you tailor your marketing and promotional campaigns to best suit the needs of your target audience.

In addition, analyzing Amazon data can help you identify trends in customer behavior, such as which products are most popular in different demographic groups or in different locations. This information can help you target the right segments of customers and better cater to their needs.

Best Practices for Analyzing Amazon Data

Now that we’ve discussed why analyzing Amazon data is important, let’s go over some best practices for data analysis.

1. Start with the Basics

Before diving deep into your data, it’s important to start with the basics. Begin by gathering data on key metrics and trends, such as sales, revenue, customer engagement, and customer reviews. This will give you a good starting point and provide you with an overview of your performance and customer behavior.

2. Identify Your Goals

Once you have an understanding of your data, it’s important to identify your goals. What do you want to achieve with your data analysis? What insight do you hope to gain? Knowing your goals will help ensure you are focusing your analysis on the right areas.

3. Clean and Organize Your Data

Once you have identified your goals, the next step is to clean and organize your data. Data can be messy and difficult to interpret, so it’s important to make sure it is organized and easy to understand.

4. Analyze Your Data

Once your data is organized, it’s time to start analyzing it. Begin by looking for patterns and trends that can help you understand customer behavior and identify opportunities for improvement.

5. Visualize Your Data

Data visualization is an important step in data analysis. Visualizing your data can help you identify patterns and trends more quickly and easily. There are many tools available to help you visualize your data, such as Tableau, Microsoft Power BI, and Google Data Studio.

6. Take Action

Once you have identified insights from your data, it’s time to take action. Use the insights you’ve gained to inform your decisions and optimize your Amazon business.

How to Use Insights Gained From Your Amazon Data

Now that we’ve discussed best practices for analyzing Amazon data, let’s talk about how to use the insights gained from your data.

1. Optimize Your Product Listing

Analyzing your Amazon data can help you optimize your product listings. You can use the insights gained from your data to determine which products are most popular with customers and which products are underperforming. This information can help you make decisions on which products to prioritize and which products to discontinue or improve.

2. Tailor Your Marketing and Promotional Campaigns

Analyzing your Amazon data can also help you tailor your marketing and promotional campaigns. You can use the insights gained from your data to understand customer behavior and target the right segments of customers. For example, you can use the data to identify which products are most popular with different demographic groups or in different locations.

3. Improve Your Customer Service

Analyzing your Amazon data can also help you improve your customer service. You can use the insights gained from your data to understand customer preferences and identify areas of improvement. For example, you can use the data to determine which products customers are searching for and how often they are returning to your store.

4. Sales Performance Analysis

One of the most important factors in your Amazon strategy is sales performance. With an Amazon Insights tool, you can gain a deep understanding of how your competitors are performing in terms of sales volume and revenue. This information can help you identify areas where you can improve your own sales strategy, and stay ahead of the competition.

5. Product Pricing Analysis

A variety of Amazon Insights tools can provide you with detailed data on product pricing for your competitors’ products. This information can help you identify areas where you can improve your own pricing strategy, and stay ahead of the competition.

6. Competitor Analysis

Analyzing your competitors’ data can also provide valuable insights. By analyzing their sales data, pricing, and customer reviews, you can identify gaps in the market and opportunities to differentiate your products from theirs.

For example, you might discover that your competitors are offering a similar product at a lower price, which could prompt you to adjust your pricing strategy. Alternatively, you might notice that your competitors are receiving consistently negative reviews for a certain feature or aspect of their product. This can help you identify areas where you can differentiate your product and offer a better customer experience.

In addition to analyzing your direct competitors, you can also look at broader market trends and patterns. For example, you might notice that certain product categories or trends are gaining popularity among customers. This can help you identify new product opportunities or adjust your existing product line to meet changing customer needs.

7. Advertising Campaign Analysis

Amazon offers various advertising options to sellers, including Sponsored Products, Sponsored Brands, and Sponsored Display. By analyzing the performance of your advertising campaigns, you can determine which campaigns are generating the most sales and adjust your strategy accordingly.

For example, you might discover that your Sponsored Products campaigns are generating more sales than your Sponsored Brands campaigns, which could prompt you to allocate more of your advertising budget to Sponsored Products. Alternatively, you might notice that certain keywords or ad placements are generating more sales than others. This can help you optimize your ad targeting and improve the ROI of your advertising campaigns. In addition to analyzing the performance of individual advertising campaigns, you can also look at broader trends and patterns.

8. Inventory Management

Analyzing your inventory data can help you make informed decisions about inventory management. By analyzing your inventory levels and sales data, you can identify which products are selling quickly and which ones are not. This information can help you adjust your inventory levels and prevent stockouts.

For example, you might notice that a particular product is selling faster than expected. This can prompt you to order more inventory to avoid running out of stock. Alternatively, you might notice that a certain product is not selling as well as expected. This can prompt you to adjust your pricing or marketing strategy to boost sales.

You can also use data to forecast future demand. By analyzing historical sales data and trends, you can predict how much inventory you’ll need to order in the coming months. This can help you avoid overstocking or understocking, which can lead to lost sales or excess inventory costs.

How Cluster Can Help

To get the most out of your Amazon data, it’s important to have the right tools and resources in place. This might include data analytics software, customer feedback platforms, or inventory management systems. By investing in tools like Cluster, you can ensure that you’re able to collect and analyze data effectively and make informed decisions that drive business growth. Book a demo now.