The Ultimate Guide to AI and PIM: Boosting Your Business Performance

AI has been around for a while, but it's recently started to have a major impact on retail businesses, where one of the highest adoption rates can be seen. Driven by factors like the rise of smart devices and internet users, growing awareness of AI's potential, and government pushes for digitalization, companies are increasingly leveraging operational tracking to achieve corporate goals, improve results, and connect with customers online. This trend is fueling the expansion of AI in the retail market. In fact, by 2028, the retail industry alone is expected to spend $24.1 billion on AI, and that number is growing quickly.

This is good news because many companies struggle to be efficient, get products to market fast enough, and understand stores, customers, and items for better inventory management. According to Capgemini’s, the top most relevant and useful AI platforms used among organizations are related to: chatbots to automate customer service (83%), tools to design, collect, and summarize data (75%), and text (71%). The last two are of interest as we explore the key AI features reshaping product data to help retailers increase their bottom line.

What is AI and PIM?

Simply put, AI (or Artificial Intelligence) is like a superhuman data analyst. It can crunch massive amounts of information, turning it into insights businesses can use to make smarter decisions. Imagine sifting through mountains of data to find hidden patterns — that's AI's specialty. 

Moreover, AI serves as the cornerstone of customer-centricity, empowering companies to deeply understand their customers, foresee their requirements, and deliver personalized experiences. However, AI's impact extends beyond customer relations; it automates tasks, predicts market trends, bolsters security measures, and the list goes on…

What’s certain is that embracing AI is no longer discretionary, it’s a winning formula providing several benefits for companies across industries.

“AI should definitely be part of your overall strategy and technology stack moving forward. But it’s important to understand that AI will play different roles for different functions throughout your operations. The AI tool you’ll be using to optimize shipping and delivery management in your logistics system will be different from the one that’ll help you recommend the most relevant products to visitors on your e-commerce site. Because AI works at its best when you have large data volumes to leverage, the PIM solution is a good use case for AI to support operations and improve speed to market. Plus, you’ll get more effect from AI when used to boost processes close to your business core.”

Ulrik Lilius, Senior Business Advisor at Avensia

On the other hand, Product Information Management (PIM) is a solution that helps businesses manage and centralize their product data. It serves as a single source of truth for all your product information — from descriptions to categories, classifications and more. As a result, this enriched data is then easily distributed to sales channels, ensuring consistent and informative presentation of your products to the end customer.

The Fusion of AI and PIM: A Winning Combination

Wherever there’s large amounts of data, there is a case for AI. In this scenario, the long awaited adoption of AI features in PIM solutions can enable retailers to unlock the possibilities of product data even further to the extent we have not seen before. We can refer to it as ‘PIM on steroids’ - this powerful duo can create a springboard for smarter product decisions. Together, they can optimize several processes, automate tasks and workflows, and as a result reduce return rates or headcounts required to manage product data, and help companies scale their operations globally. 

Key Challenges Managing Product Data

Whether you are using spreadsheets or have a robust PIM solution in place, managing product data presents a lot of challenges within retail, but similarly within distribution and manufacturing industries. 

Some of them include:

• Reliance on human resources to perform the majority of tasks manually by creating, distributing and validating it, while ensuring the data is up to date;

• Setting up key processes and automation within PIM solution, e.g creating product categories;

• Maintaining and further refining product data to ensure consistency;

• Understanding of how product taxonomies work in practice and how to make them effective for your customers.

Considering the above, it seems that AI can further enhance several aspects of the PIM solution, in order to automate and enrich product data, resulting in significant improvements.

Several of them are described below and can help retailers (but also other companies handling vast amounts of data or SKU’s) to significantly boost their business performance.

#1 Generating Product Descriptions

If you happen to work with product data within e-commerce, you must experience the struggle of dealing with large amounts of products, which require manually crafting descriptions and attributes for each new item added. Assuming it takes roughly 10 minutes per product, multiply that by the number of products, and you'll find yourself dedicating an entire week solely to managing product data. AI fundamentally alters this scenario, by inputting basic product information and technical specifications, you can generate compelling product descriptions tailored to your product taxonomy within seconds.

AI can assist with tasks that involve not only repetitive work but also those requiring specialized knowledge and comprehension of the product. For instance, if you operate a store specializing in aftermarket building materials, you'll need to associate products with specific building categories they are compatible with. In a traditional PIM system, you would either require an expert with comprehensive knowledge or invest significant time in researching official product specifications and other information sources. While AI cannot replace the expertise and experience of a specialist, it can efficiently search for relevant information within the documents provided, thereby saving you a considerable amount of time.

Key business value: A significant time saved in managing product data

#2 SKU Matching

Another application of AI/ML in PIM systems involves automatically identifying and matching SKU’s of duplicate products. Through intelligent identification and matching of similar SKUs, organizations achieve a more streamlined and precise database within their PIM solution, all while ensuring real-time detection of outliers to maintain data integrity. This functionality proves particularly valuable in marketplace e-commerce platforms, where multiple sellers may offer identical products at significantly different prices and recommend them for a review.

Utilizing AI to match SKUs offers several customer-centric enhancements, For instance, customers can compare various listings of the same product and receive recommendations based on their priorities, such as price, shipping speed, or return policies, enhancing their overall shopping experience.

Key business values: Improved CX while providing better purchasing options for consideration.

#3 AI Translation of Product Data

If you desire to sell globally and cannot bear the costs of professional translation services, with an AI-Translate feature, you can generate product descriptions into other languages with a single press of a button. What’s more, by performing a bulk action, AI is able to translate the whole categories of product data within seconds. 

For example, a company selling electronics can use AI translation in its PIM to localize product details into various languages, making them accessible to customers worldwide. This enhances customer experience, expands market reach, and accelerates international sales. Moreover, AI ensures consistency and accuracy across translations, maintaining brand integrity and reducing the risk of miscommunication. 

This feature brings a lot of controversy around putting yet another industry out of business — translation services, however while AI translation is getting better, it still has some limitations with cultural nuances, idioms and industry-specific jargons. Instead of fearing the unknown, it’s better to have a more opportunistic approach — AI may open doors for new services like real-time conversation translation or highly specialized translation tools. 

Key business values: 

• Costs savings in professional translation services

• Improved workflows with the final human oversight

• The ability to expand into new markets

• Delivering localized product experiences to customers around the world

#4 Content Enrichment

The challenging endeavor of gathering and enhancing data from various origins poses a significant hurdle in product data management. Historically, this undertaking relied heavily on manual effort, leading to inefficiencies and error-prone processes. However, organizations can now capitalize on AI to automate the extraction and enrichment of data, consequently diminishing the need for manual intervention and streamlining workflows significantly.

AI can assist in crafting engaging narratives about your products. Whether investigating the product's history, AI can generate stories that enthrall your audience. For example, the product description can adopt a tone and language tailored for a teenage audience. By using AI, you can get product content suggestions to enhance the description of your products. For example, referring to a customer rating or even a review of the product, such as: “These jeans are exceptionally comfortable, stylish, and durable, making them the perfect choice for casual outings” will create a more informative and engaging experience for the customer.

Additionally, AI algorithms can enhance product data by aggregating additional information from diverse sources. For instance, AI-powered PIM solutions can scour the web to gather product photos, user-generated content, and relevant product recommendations. With access to a wide range of data, businesses can obtain a comprehensive understanding of their products, enabling them to offer consumers more engaging and personalized experiences.

Key business values: An automated data enrichment enables companies to:

• Expand to new markets

• Add new brands into the portfolio offering

• Increase the number of product listings
  
  

“With all product data available in the PIM solution, you can leverage AI to generate texts, descriptions, images and translations for usage in all sales channels instead of placing an AI generator in each publication tool such as the CMS. As such, you’ll benefit from consistent product marketing messages as well as accelerated time to market for new products.”

Ulrik Lilius, Senior Business Advisor at Avensia

#5 Product Categorisation and Classification

This process entails training a machine learning model on an extensive dataset comprising products and their corresponding categories. It leverages the dataset to grasp the associations between products and categories, facilitating precise categorization of new products based on their attributes.

The initial phase of automated product categorization involves defining a comprehensive array of categories and subcategories for organizing products. These categories may be delineated by diverse attributes like product type, brand, material, size, and color. Once the categories are established, the PIM system commences gathering data on products, encompassing attributes, descriptions, images, and other pertinent information. For instance, if you have a diverse catalog of clothing, AI can classify items into categories like "Tops," "Bottoms," "Outerwear," and "Accessories" based on features such as material, style, and color. Another way of categorizing products is by using product hierarchy, for example, having a category of “Furniture” and subcategory of “Kitchen & Supplies”. Based on the product characteristics, it is AI that decides under which subcategories products belong to. 

Subsequently, the model scrutinizes the product data and allocates products to the suitable categories. Over time, the model discerns patterns and correlations between products and categories. It employs these patterns to anticipate the categories to which new products belong to. This epitomizes the essence of AI — its capacity to learn and execute tasks autonomously, devoid of routine dependence. To uphold accuracy, it is crucial to periodically update and retrain the model with fresh data. 

Key business values:

Enhanced Customer Experience (CX) and costs savings by providing

• An improved search and navigation allowing customers to find products faster;

• Faster product onboarding;

• Streamlined data management.
  
  

#6 Image Recognition and Enhancement features

AI enhances image quality in product information management, refining visuals to maximize consumer engagement. Employing deep learning techniques, it enhances product images by accentuating vibrant details. For example, within the fashion sector, AI improves color accuracy and texture details, offering an authentic representation of garments. This integration of image enhancement and product information not only captivates consumers visually but also ensures a precise and enticing depiction of items, thereby enriching the online shopping experience as a whole.

Image recognition with AI enables us to analyze product images and generate a list of attributes and descriptors. It transforms unstructured data in PIM or DAM solutions into structured product descriptions, enhancing accuracy and efficiency. This feature eliminates inherent biases that humans may have in describing products, broadening the product's reach from an SEO perspective. 

Key business values: 

• Improved customer experience through similar product recommendations;

• Auto-categorizing and creating streamlined product taxonomies.

How is AI Boosting Overall Business Performance Around Product Data

While AI adoption among Product Information Management has been discussed thoroughly above with specific business values, what’s yet to be discovered is AI’s ability to bring long-term strategic advantages to businesses adopting the AI early on, such as:

1. Allowing companies to fully embrace data-driven decisions

 According to Gartner, by 2025, 95% of decisions that currently use data will be at least partially automated. This extends to product data, while empowering companies to optimize product offerings, pricing strategic and marketing campaigns.

2. Unlocking the Competitive Advantage 

By leveraging AI for categorization, businesses can stay ahead of the competition. They can identify emerging trends, tailor product offerings to customer needs faster, and ultimately gain a competitive advantage.

3. Enabling Future Growth

AI can handle massive amounts of data effortlessly, making it ideal for businesses with large and ever-growing product catalogs and reducing human errors while ensuring consistency and accuracy in product classification.

4. Specialized Knowledge Assistance

AI aids in tasks requiring specialized product comprehension, such as associating products with specific building parts. While AI does not replace specialist expertise, it efficiently extracts relevant information from documents and databases, saving time and effort.

Step Up your eCommerce Game with the AI Features of Bluestone PIM

Bluestone PIM is a MACH-based PIM solution, supporting global brands to name a few: Sainsbury’s, Dolby Laboratories and St. Gobain in managing product data. The modular nature of MACH-based solutions facilitates easier maintenance and reduces dependency on single vendors, reducing risks associated with system failures or disruptions. Ultimately, the combination of agility, interoperability, and reduced operational overhead inherent in MACH architectures translates into a higher ROI for businesses seeking to optimize their PIM solutions for the modern digital landscape. 

The launch of a wide range of AI features in Bluestone PIM solution, enables companies to automate the creation of product descriptions, attributes, and classifications. This ensures accuracy and consistency across vast product catalogs, saving valuable time and resources. 

Users can now fully leverage AI with our new built-in feature to ensure top-notch product information: 

• AI Enrich  - generate fresh content like product descriptions, analyze existing content quality, and receive improvement suggestions – all powered by AI;

• AI Linguist - take control of language with features like translation, spell checking, and text refinement. Ensure clear and error-free communication across all touchpoints.
  
  

Or go beyond content with the AI Analyst, our data optimization expert.  This advanced feature, currently on the roadmap, will bring significant business benefits by identifying:

• Misplaced or missing categories while ensuring accurate categorization, leading to improved product discoverability and customer satisfaction;

• Incorrect attribute values or definitions and rectifying issues and optimizing product data for success.

Imagine creating content that resonates deeply with your audience, while also optimizing your operations for maximum efficiency. That's the power of combining AI-powered content creation with advanced data analysis. This potent duo can unlock significant business value by streamlining workflows, boosting customer satisfaction, and driving targeted marketing efforts.  

Ready to see how it works for your business? Let's talk!