The human eye can distinguish as many as 10 million different colors. From fashion and beauty to furniture retail and tile manufacturing, the impact of color is immense. Businesses often hinge their identity and product appeal on precise shades and tones, ranging from standard colors like Azure and Ruby Red to unique hues like Fern, Charcoal, Byzantium, Celadon, and Smaragdine (yes, that’s a real color). Some companies even venture into creating proprietary colors (the term ‘Tiffany Blue’ will always evoke imagery of that robin eggshell hue), underscoring how essential and influential color is to consumer preferences across diverse sectors. The lesson is clear: getting color right is crucial and something businesses cannot afford to overlook. Just as colors can be complex, the struggle for companies to manage them can be complex too. Across an entire enterprise, there could be multiple teams involved in managing color, from design and engineering to eCommerce and procurement. With multiple teams and users comes competing business objectives, a higher risk of human error, and lots of room for interpretation. For 100 instances of ‘Burgundy’ in a product line, you could expect to get some variation of the following: As you can see there are a lot of ways of interpreting (and spelling) the same thing. These types of discrepancies are a lot more common than many people realize. They certainly detract from the product experience your customers have, but they also cause problems with Site Search and SEO, and can wreak havoc with attempts at applying analytics to products and buying trends. Fortunately, these types of issues with colors are what Product Information Management (PIM) systems were designed to eliminate.  

Benefits of Streamlining Color Variations

Streamlining the color naming process for a business when listing their products across different marketplaces and geographic locations offers several benefits: Consistent branding: Standardizing color names ensures that a brand is represented consistently no matter where its products are sold, aiding in maintaining a uniform brand identity and reinforcing brand recognition among consumers regardless of where they’re shopping. Improved customer experience: Consistent and clear color naming reduces confusion for customers, making it easier for them to find and select products, which can enhance customer satisfaction and potentially increase the likelihood of repeat purchases. Enhanced searchability and SEO: Using standardized color names improves searchability across platforms. Customers often search for products by color, and consistent naming helps in aligning with common search terms, which can boost SEO and visibility. Easier inventory and catalog management: When colors are named consistently, managing inventory across multiple channels becomes more straightforward. It simplifies tracking and reduces errors in stocking and distribution, leading to better inventory accuracy. Streamlined communications: A standardized color naming system simplifies communication within the company and with external partners, such as manufacturers, distributors, suppliers, and retailers, reducing the risk of errors and miscommunications. Cross-market appeal: Having a uniform color naming system helps in adapting and translating products for multiple markets without needing to customize the descriptions for each region too extensively, leading to more efficient expansions and launches in new markets. Reduced costs: Streamlining the color naming process can lead to lower marketing and operational costs, and simplified product descriptions and catalogs mean less time and resources are spent on creating and managing product listings across various platforms. Improved data analytics and reporting: Standardized color names make it easier to collect and analyze data on color trends and preferences across different markets. This can inform future product development and marketing strategies, allowing businesses to be more responsive to consumer needs. By adopting a streamlined approach to color naming, businesses can enhance their operational efficiency and market adaptability, leading to better customer engagement and potentially higher sales.  

Akeneo PIM & The Color Conundrum

In Akeneo PIM, this headache would be solved by creating a field (attribute) of the simple or multi-select type. These fields allow the business to decide on exactly how they want to present each color (is it ‘Burgundy’ or is it ‘Maroon’?) and then enforce governance for all of their users so that they are applied consistently. Just as important in today’s global markets, the translation of these colors can also be standardized. Here’s what this approach looks like in Akeneo PIM: Another common problem with managing color is that an individual color may need several different iterations depending on what system or team is working with it. For example, it’s not uncommon for a new SKU to be onboarded by a purchasing manager who inputs it as a generic “Blue” to fit the basic (and boring) requirements of the ERP system. Next, this same color is recreated as “Sapphire” by a content specialist looking to provide a proper marketing name. And on yet another path along the color carousel could involve an eCommerce Manager accounting for a website filter or search engine and going with ‘Navy Blue’. In Akeneo PIM, users could account for this by making separate attributes like ERP Color, Color, SEO Tags, or Site Color. This allows you to manage the unique requirements of each component of color with data governance in the same product record. Or, you could utilize Reference Entities, which help you to maintain all of colors and color variations in a single centralized entity as shown below: Reference Entities also allow you to store and manage additional color information like Hex Codes and Swatches. All of this information can also be adapted and translated to different Sales Channels and Locales. Finally, (and arguably this is where the real power lies!) if I want to change a color’s name or description information, Reference Entities allow me to update ALL of the products referenced to that record in a few clicks without having to update each record individually.  Managing colors is a complex and important part of product information management that is a struggle for companies of all sizes. High quality images may present what a product looks like to consumers, but it’s not enough. To optimize website filters, SEO, internal operations, and the tastes of discerning consumers who expect an exceptional product experience, color must be correct and contextualized across languages and business applications. Don’t whitewash color as I used to by treating it as just another data point to be managed in a back-end system. Instead, treat color like Picasso or Van Gogh did: as a powerful tool of great depth and intricacy that can attract attention and help curate the customer’s experience.

The history of invention is scattered with accidental magic; creations that undergo a transformation in how we use and apply them. Bubble wrap was originally invented and sold as a type of wallpaper. That failed. Yet it eventually found success as an excellent packing material – and who can resist popping those bubbles?  Play-Doh was first marketed as a wallpaper cleaner before realizing its creative potential as a modeling compound for children’s arts and crafts. The rapid rise and proliferation of Artificial Intelligence (AI) has us all scrambling to look for the best ways of integrating it into everything, from business products and services to workflows and personal self-development. As it evolves, so will our use of it. Product Information Management (PIM) is also evolving. And as the technology advances, the role of PIM in shaping engaging customer experiences will continue to grow. PIM is already helping brands and retailers centralize their product data to better manage and update product information across channels (physical stores, apps, websites, email marketing).  Some of the core benefits of PIM for businesses include:

• Reach markets faster by streamlining processes of updating existing products as well as adding new ones. With this added agility, businesses can respond much faster to meet new customer demands and market trends.
• Uphold consistency and accuracy by ensuring product information is the same across all touchpoints. By centralizing data into a single source of truth, customers receive a seamless experience regardless of where they interact with a brand.
• Improve personalization by using data management to better understand customer behaviors, preferences, and needs. This can then be used to recommend products and create more tailored shopping experiences.

 

What’s Next for PIM?

When Tryzens analyzes PIM solutions, we have an eye for how the platforms are evolving and integrating other technologies to future-proof business needs. There are many areas to explore, but let’s zero in on five key areas that PIM is helping to shape.

1. Artificial Intelligence (AI)

PIM platforms are already using artificial intelligence to improve the product experience. For example, last year Akeneo acquired the AI platform Unifai, which is helping to improve data collection, cleansing, categorization, and enrichment. It has also created a dedicated Center of Excellence to optimize AI for the product experience. AI-powered PIM systems will be able to automate data categorization to further refine navigation and search for customers. They could also automate enrichment tasks to provide customers with richer product details, helping them make more informed purchasing decisions, as well as enhancing product discoverability.

2. Real-Time Personalization

Through AI enablement and automation, PIM platforms will be a key enabler for deeper personalization in real time. For example, recommendation engines will leverage rich semantic product information data that has been created by artificial intelligence. With more effective ways of centralizing customer data, segmenting it, and automating certain efforts, personalization is becoming more sophisticated. PIM platforms may deliver hyper-personalized experiences that consider individual preferences, intent, and context, involving tailored pricing, bundling, and specific product promotions. This could also include customers receiving different product media being showcased to them on a PLP or PDP – like how Netflix curates personalized thumbnail images to each viewer.

3.  Virtual Reality (VR) and Augmented Reality (AR)

Brands and retailers are already experimenting with AR and VR. From virtual fitting rooms for clothing to virtual try-ons for jewelry, customers are getting a more immersive shopping experience. And it’s just the start. Sales of VR headsets have accelerated in recent years. Around 5.5 million were sold globally in 2019; 7.9 million in 2020; 14.3 million in 2021; 19.1 million in 2022; and 21.8 million last year.  What does that mean for retailers and brands? Businesses will be able to integrate PIM data with AR and VR platforms, allowing customers to explore and interact with products in a lifelike environment. This not only improves customer engagement and satisfaction but also reduces product returns by enabling customers to make more informed purchasing decisions based on realistic product representations.

4.  Voice and Livestream Commerce

Voice assistants like Google Assistant and Alexa increasingly sit on kitchen counters, living room coffee tables, and bedroom drawers. PIM platforms can help businesses adapt their products for voice-driven product searches, purchases, and recommendations, giving customers a convenient and intuitive way to shop online. With the growth of eCommerce, social media, and influencers, livestream commerce is a rising global trend. It involves a host showcasing products in a real-time broadcast and interacting with viewers, who can make a purchase during or after a show.  And the biggest benefit is that livestream sales have impressive conversion rates: they’re 10 times higher than traditional eCommerce rates, with 60% of livestream viewers making a purchase during or after an event. Connecting PIM data with livestreaming platforms presents exciting opportunities for brands to engage customers with more interactive and immersive shopping experiences, such as analyzing viewer interactions in real time to optimize content based on their preferences and behavior.  

5.  Sustainability

As environmental sustainability becomes an increasingly important consideration for both businesses and customers, there is a growing emphasis on tracking and managing the environmental impact of products. Future PIM will likely focus on further integrating sustainability metrics and environmental data that underscore responsible product management. By showing the carbon footprint, recyclability, and sourcing practices, it allows brands to communicate their level of eco-friendliness in a more transparent and user-friendly way.  

The Future of Customer Experiences

If the history of innovation has taught us anything, it’s that the most unexpected transformations often yield the most innovative uses, and PIM and AI are no different. The future of PIM is not only about enhancing product information management and customer experience but also about advancing sustainability and driving substantial business growth.  As businesses continue to leverage these innovations, PIM will undoubtedly play a pivotal role in meeting the dynamic demands and setting new benchmarks for customer engagement and operational efficiency. This article was provided by Akeneo, Tryzens.

Managing product data is critical for selling any type of product in the 21st century. The importance of high-quality content and data has gone from only being needed for eCommerce, to a minimum requirement for competing in an omnichannel world.  The data standards required to compete today, especially in the automotive industry, require a unique approach that leverages many different types of data. This article will cover an overview of the data required for automotive products, the importance of a microservices approach to managing this data within your commerce system, and the importance of leveraging enriched product data for a compelling experience.

Automotive Industry Standards

The Autocare Association represents the automotive industry and sets the standards. These standards are commonly referred to as ACES and PIES, but there are several layers of database provided as part of the Autocare VIP service.  ACES stands for Aftermarket Catalog Exchange Standard, and PIES stands for Product Information Exchange Standard. The below chart details the relationship between the various databases and the higher level standards, but most industry professionals use ACES and PIES to discuss the requirements for automotive data.    

PIES

PIES data covers the core attribution, assets, product makeup, and classification. From a product experience perspective, this data is no different in structure from other products in other industries.  All products need a title, brand, description, price, and some sort of hierarchy. While the specifics of PIES data structures are highly specific and tailored to the automotive industry, they very closely align with what we recognize as core PIM functionality. Completeness, data quality analysis, data validation, and assets are critical pieces of the enrichment of this data. According to the 2023 NRF report on Consumer Returns in the Retail Industry, 17.6% of online sales were returned in 2023, significantly higher than the 10.02% return rate for brick-and-mortar store purchases. This discrepancy is often due to improper fit, which is a leading cause of high return rates. In the US, returns across the retail sector totaled $743 billion for the year.  Anything short of a best-of-breed PIM to empower teams to enrich this data will result in a subpar experience for any shopper and result in lower sales and increased returns.   

ACES

ACES data covers application data, qualifier data, and other structures that power fitment. Fitment isn’t a unique challenge to automotive, but the Year Make Model (YMM) standard found in the VCDb is critical to automotive parts sales.  Take for example a common use case: A customer needs new windshield wipers for their 2016(year) Subaru (Make) Crosstrek (Model). There are millions of unique combinations of YMM, but this customer doesn’t care about the other vehicles on the road, they only need to answer 1 question: Does it fit?  Managing YMM is simplified by subscribing to the Autocare VCdb updates, but the assignment of valid fitment configuration (also known as application) is essential to converting sales in the market. Microservices Architecture has dominated the eCommerce space over recent years for good reason. Leveraging the ‘Best of Breed’ solutions for specific problems results in a more flexible system that can be improved in specific areas without needing to replace the entire system all at once. In addition, these targeted systems allow for companies to leverage the best tools for specific problems without compromising on other critical areas.  Akeneo excels at Product data including attributes, quality, attribute validation, and assets. All that was needed was a targeted add-on to manage the Fitment component, which we developed and released as the Sitation Automotive Fitment App.  Similar to the ACES and PIES standards created and championed by the Autocare Association, the separation of Fitment and PIM enrichment, validation, and distribution is the ideal solution for a company following a microservices architecture for their commerce solutions.  Competition in the automotive industry is forcing companies to evolve or be left behind when it comes to competing in this space. Traditional powerhouses in space such as Advanced Auto and AutoZone now compete with Amazon and Ebay for the aforementioned Subaru driver looking to replace their windshield wipers, and those shoppers expect high-quality product data combined with confidence the product will fit their vehicle.

As artificial intelligence (AI) becomes increasingly integral to how we do business, one thing has become abundantly clear: AI is only as good as the data it works with. AI systems, particularly those based on machine learning, rely on vast amounts of data to learn, make decisions, and provide insights by extracting patterns and knowledge from the data they are fed. If the input data is flawed—be it incomplete, biased, inaccurate, or poorly structured—the output will inevitably suffer. This can ultimately manifest in AI models that perform inconsistently, deliver erroneous predictions, or fail to provide actionable insights, ultimately compromising decision-making processes and business outcomes. But how do you know if your data is ready for AI? Let’s take a look at 6 crucial factors that can be used to determine how strong your foundation is to support AI implementation.  

1. Stability of Data Structure

AI algorithms develop their understanding and make predictions based on the patterns they detect in the data they are trained on. Consistent data formats across time ensure that once an AI system is trained, it can continue to apply its learned patterns to new data without errors or the need for reconfiguration.  Changes in data formats—such as altering column names, changing data types, or reorganizing the database schema—can confuse AI models. This may lead to incorrect outputs or require additional time and resources to retrain the model with the new structure. In order to maintain a stable data structure conducive to effective AI analysis, it’s important to remember to:

• Plan with the future in mind: When designing your data architecture, anticipate future needs and potential expansions. Design a scalable and adaptable structure that can accommodate foreseeable changes without fundamental overhauls.
• Implement version control and documentation: Version control systems for your databases and comprehensive documentation of any changes ensure smooth transitions and support the integrity and traceability of data modifications.
• Establish change management protocols: Create a protocol for assessing and implementing changes in the data structure. This should include steps for impact assessment, testing the changes for compatibility with existing AI systems, and provisions for updating the AI models if necessary.
• Create a system for auditing: Conduct regular audits to ensure that the data remains consistent with the expected formats and to verify that no unauthorized or unintended changes have occurred.

 

2. Diversity and Accuracy of Data Sources

AI algorithms benefit from a broad spectrum of data inputs as diverse data sources aid in minimizing biases and improving the accuracy of insights.  Data can come from a variety of sources, including different suppliers, customer demographics, sales channels, eCommerce sites, and third-party marketplaces. This diversity is vital for a few key reasons:

• Reduction of bias: AI systems can develop biases based on the data they are trained on. By integrating data from a wide array of sources, you can mitigate the risk of these biases, as the AI solution will have a more balanced view that reflects varied perspectives and conditions.
• Enhanced robustness: Diverse data sources make AI models less sensitive to anomalies in any single source, which is crucial in dynamic market environments.
• Improved predictive power: With data coming from a comprehensive mix of inputs, AI algorithms can better predict behaviors and outcomes across different customer segments and market conditions.

It’s important to note here that data accuracy is just as crucial as data variety. Before integrating a new data source, verify its credibility and track record and ensure that your suppliers and data providers adhere to industry standards and best practices in data collection and management.  

3. Volume of Data

The volume of data is critical for the effectiveness of AI algorithms. More data points allow AI systems to train more comprehensively, leading to more accurate and reliable outputs.  A large dataset is fundamental for training AI models because it provides a comprehensive basis from which the system can learn and recognize patterns. More data points increase the likelihood of capturing all variations and nuances of the behavior or trends being analyzed, which is crucial for accurate pattern recognition. Plus, with limited data, there’s a higher risk that an AI model will overfit, meaning it performs well on training data but poorly on unseen data. A substantial volume of data not only mitigates this risk as the model can be validated and tested across a more diverse set of data points, but also increases the statistical power of the analyses, meaning findings and predictions are more likely to be valid and not due to random chance.

4. Data Structuring for AI Comprehension

AI algorithms require data in formats that they can readily process. This typically means structured data that refers to any data that adheres to a strict format, enabling easy access, search, and analysis, and would typically include:

• Defined data models: Structured data operates within a defined schema—like tables with rows and columns—where each data element is clearly delineated.
• Uniform data entry: Each entry follows the same format. For example, in a CSV file, every row represents a record and each column a specific attribute of that record.
• Direct usability in AI models: Structured data can be directly fed into most AI models without requiring preliminary processing steps, facilitating smoother and more efficient data analysis.

Unstructured data, such as text documents, images, videos, or even emails, often requires extensive cleaning and transformation processes (like natural language processing for text or image tagging for visuals) to convert it into a structured form suitable for AI analysis. If your data requires extensive human intervention to decode or reformat, it may not be ready for efficient AI integration.  Ensuring that your data is AI-friendly from the outset saves time and resources and reduces the likelihood of errors during data processing.  

5. Richness of Data Fields

The content of your data fields plays a significant role in the effectiveness of AI analysis. When data fields are populated with comprehensive, detailed information, AI systems can perform deeper and more nuanced analysis and more personalized recommendations. Data fields should go beyond basic identifiers like name or price to include detailed product descriptions, comprehensive titles, and extensive categorizations to enrich the dataset.  Why? It’s simple; a product description that includes specifications, materials used, intended use cases, and unique features provides a robust dataset for AI to analyze, providing a better foundation for these solutions to accurately classify products, recommend similar items, and even identify market trends. Pro-tip: Your data fields should be in rich text format to get the most out of AI. Rich text formats allow for the inclusion of formatting and structural elements such as headings, lists, and bold or italicized text, which can not only help highlight important features within the data, but also allow the AI solution to leverage these elements to better understand the emphasis and hierarchy of information, improving its ability to extract relevant features and insights from textual data.  

6. Structuring of Input Files

The physical structure of your data files impacts the ease with which AI can process them. Tabular data formats, like CSV or excel files, provide a clear and organized way to present data where each row typically represents a single record (such as a product) and each column represents a specific attribute of that record (like price, SKU, description). This arrangement offers several advantages, including ease of access, data consistency, and increased efficiency when it comes to larger datasets. Unstructured formats such as Word documents or PDFs often contain a mix of text, images, and other elements that do not follow a predictable structure. To maximize the effectiveness of AI applications, consider these best practices for structuring data files:

• Standardize data collection: Implement standardized procedures for data collection to ensure that all data is captured in a consistent format from the outset. 
• Utilize data centralization technologies: Employing technologies such as a PIM for centralizing your product record can help organize and manage large chunks of information, and create a structured dataset for AI.
• Implement regular data structuring audits: Regularly review and update the structure of your data files to ensure compatibility with evolving AI technologies, including revising data schemas, updating table formats, and ensuring that all data fields are accurately and consistently captured.
• Invest in training and tools: Invest in training for your team on best practices in data management and provide them with tools that facilitate the maintenance of structured data formats.

 

Preparing Your Data for AI Integration

Ensuring your data is ready for AI integration involves meticulous planning and management across multiple dimensions.  From maintaining a stable data structure and accumulating a sufficient volume of data to ensuring data source diversity and structuring data for optimal AI comprehension, each factor contributes significantly to the success of AI applications.  By adhering to best practices in data management—such as standardizing data collection, verifying source accuracy, and enriching data fields—you can build a robust foundation for AI to not only function effectively but also drive insightful, data-driven decisions that propel your business forward.  This preparation not only streamlines the integration process but also maximizes the potential benefits of AI, ensuring that your investment in this cutting-edge technology yields tangible, valuable results. Do you know if your organization has the right framework in place to support AI technology integration? Take our AI Readiness Assessment today to get your personalized readiness score, and receive actionable tips and tricks on how to get started!

Ever clicked that “Buy Now” button on your favorite online store and marveled at how effortlessly the product arrives at your doorstep just a few days later? From a customer’s perspective, the ordering process seems pretty straightforward: select, pay, confirm, wait for delivery. Yet that seemingly simple click triggers a domino effect of tasks, checks, and movements that span multiple technologies and organizations.  

What is eCommerce Order Management?

eCommerce order management is exactly what it sounds like – the process of managing, fulfilling, and shipping all orders completed on eCommerce channels, whether that’s through your own website or a third-party marketplace, such as Amazon. The average order fulfillment process looks a little something like this:

1. 1. Order placement: The customer places an order on an eCommerce platform, and kicks off the order management process.
   2. Order confirmation: Once the order is place, an order confirmation is sent to the customer to acknowledge receipt of the order and should include important details such as items purchased, prices, order number, and expected delivery details.
   3. Order processing: The order is then processed internally by the company, and includes verifying payment, checking the availability of items purchased, and routing the order information to the nearest warehouse or fulfillment center.
   4. Order picking, packing, and shipping: The ordered items are picked and packed for shipping in the warehouse or fulfillment center, and a shipping label will be printed and attached to the packaging before it is dispatched from the facility.
   5. Order tracking: Once the order has left the warehouse or fulfillment center, the customer should be provided with a tracking number that allows them to monitor the shipment’s progress.
   6. Delivery: The package has arrived! A delivery confirmation should be sent to the customer.
   7. Returns Management: The order fulfillment process should also account for reverse logistics, including receiving the returned items, inspecting them for compliance with return policies, processing refunds or exchanges, and restocking items when appropriate.

This process can be complex for even a small business, and can quickly become overwhelming and unmanageable when you start to manage thousands of orders across multiple channels and distribution centers. Traditionally, and still in many cases today, order management involves a combination of manual and automated processes designed to streamline operations from the point of sale to delivery to the customer. In the early days of eCommerce, processes such as order entry, inventory checks, and communication with customers were all manually handled in spreadsheets or basic software and database solutions. These tools helped businesses to organize and visualize data, but still required a lot of manual input and lacked in-depth integrations with other systems. So, the technology market responded – specialized Order Management Systems (OMS) emerged to offer more sophisticated features for handling complex order processes, including omnichannel selling, backorder management, and returns processing.   

What is an Order Management System (OMS)?

An Order Management System (OMS) is simply a platform that helps businesses manage this complex order process, from start to finish.  Here’s a breakdown of core functionality for an OMS:

• Order entry and processing: An OMS provides a centralized platform for entering and processing orders from various channels, ensuring accuracy in capturing order details and customer information.
• Inventory management: An OMS should monitor stock levels across multiple locations in real-time and send alerts when stock levels are low, enabling businesses to forecast demand and manage their inventory efficiently.
• Warehouse management: Within the broader order fulfillment process, an OMS can offer insights into the most efficient ways to pick and pack orders.
• Shipping and logistics: An OMS tracks orders through the delivery process,often integrating with shipping carriers and logistics services to offer real-time tracking information to both the business and the customer.
• Customer service: An OMS enhances customer service by providing a complete view of an order’s status, history, and any issues that may arise, enabling support representatives to offer informed support and solutions to customers.
• Returns and exchanges management: The reverse logistics process should also be handled by your OMS, as it should update inventory levels, and ensure customer refunds or replacements are processed efficiently.
• Cross-channel integration: An OMS integrates with various sales channels, including eCommerce platforms, brick-and-mortar operations, and marketplaces, to provide a seamless shopping experience for customers and a unified view for the business.
• Analytics and reporting: An OMS should offer analytics and reporting capabilities, providing insights into sales trends, order volume, customer behavior, and operational efficiency.

 

How an OMS Can Improve Operations

An OMS provides a single location to centralize the entire order management process, which enables:

• Efficiency across order processing, fulfillment, and shipping: Automation and data centralization reduces manual intervention and speeds up the entire order-to-delivery cycle.
• Higher data accuracy: Data is the lifeblood of decision-making in today’s business environment; an OMS ensures that the data across sales channels and touchpoints is synchronized and updated in real-time, supporting better inventory management, forecasting, and planning to minimize stockouts or excess inventory.
• More scalability: As businesses grow, their order management requirements become more complex. An OMS provides the scalability needed to handle increasing order volumes without a corresponding increase in chaos or overhead costs, ensuring that businesses can grow without being hamstrung by their operational capacities.
• Expansion to new markets and geographies: Entering new markets or expanding geographically can be daunting due to the complexities involved in managing orders across different regions, but an OMS can simplify this process by managing orders from multiple markets in one system, enabling businesses to adapt their operations to local requirements and preferences.
• Enhanced supplier and vendor relationships: By providing real-time data on inventory levels, order statuses, and forecasts, an OMS can improve collaboration, leading to better relationships with vendors and suppliers.
• Better employee experience: The automation and efficiency provided by an OMS reduce the burden on employees, freeing them from repetitive and error-prone tasks which only improves productivity but also enhances overall work experience.
• Improved customer service: With faster order processing, accurate fulfillment, and timely shipping, customers receive their orders when expected, leading to higher satisfaction levels. Plus, the ability to provide accurate and timely information to customers about their orders enhances the overall experience.

 

PIM & OMS in the Ecosystem

A Product Information Management (PIM) system houses crucial information such as product descriptions, titles, specifications, images and pricing that the OMS relies on, and the OMS tends to hold important order information such as order status, tracking information, and inventory adjustments that the PIM may need, so it’s crucial to ensure these systems are integrated and communicating efficiently.   Integrating a PIM system with an OMS ensures real-time data exchange, where the PIM provides up-to-date product information to the OMS for accurate order processing, while inventory levels and order status updates from the OMS keep product availability current across all sales channels.  Plus, this integration facilitates more personalized shopping experiences, offering product recommendations tailored to individual customer preferences and purchase history. Overall, the integration of an OMS with a PIM not only optimizes operational efficiencies but also plays a crucial role in building and maintaining positive customer relationships through a superior shopping experience.  

How to Choose the Right OMS For You

Choosing the right Order Management System (OMS) for your organization involves a thorough evaluation of your business needs, technical requirements, and growth plans.  Here are key considerations to help you select the right OMS:

1. Understand your business needs

Order volume and complexity: Consider the volume of orders you process and the complexity of your order management needs, including multi-channel sales, international orders, and custom product configurations. Customer experience goals: Identify the aspects of the customer experience you want to improve, such as delivery times, order accuracy, or return processes.  

2. Evaluate the system capabilities

Integration with existing systems: Look for an OMS that can easily integrate with your existing eCommerce platform, CRM, PIM, and ERP systems to ensure seamless data flow and minimize disruptions. Automation features: Check for automation capabilities that can streamline order processing, fulfillment, and returns, reducing manual errors and operational costs. Inventory management and forecasting: Ensure the OMS offers robust inventory management features, including real-time inventory tracking across multiple locations and channels. Analytics and reporting: Access to detailed analytics and reporting can help you make informed decisions about inventory management, sales strategies, and customer service improvements.  

3. Consider the technical aspects

Cloud-based vs. on-premise: Decide whether a cloud-based OMS, which offers flexibility and lower upfront costs, or an on-premise solution, which may offer more control and customization, is right for your business. User interface and ease of use: The system should be intuitive for your team to use, with minimal training required. A good user interface can improve efficiency and reduce errors. Security and compliance: Ensure the OMS meets industry standards for data security and privacy, especially if you handle sensitive customer information.  

4. Assess the vendor

Support and training: Evaluate the level of support and training the vendor provides, including the availability of resources, response times for support requests, and ongoing training opportunities. Vendor reputation and reliability: Research the vendor’s reputation in the market. Look for reviews, case studies, and testimonials from businesses similar to yours. Cost: Consider not only the initial cost but also the total cost of ownership, including any ongoing fees for support, updates, and additional features.  

5. Plan for the future

Flexibility and customization: Choose an OMS that offers flexibility and customization options to adapt to future business needs, such as launching new products or entering new markets. Innovation and updates: Consider whether the vendor regularly updates the software with new features and stays on top of industry trends to support your business’s growth over time.  

OMS for eCommerce

Selecting the right OMS requires careful consideration of how the system will fit with your current operations and support your future goals. It’s beneficial to request demos, free trials, and to discuss your specific needs with vendors to ensure you find a solution that aligns with your organizational objectives and enhances your operational efficiency. As the digital marketplace continues to evolve, the selection and integration of an OMS become crucial for businesses aiming to streamline their operations, enhance customer experiences, and scale in a competitive landscape.  Ultimately, the success of eCommerce hinges not just on what the customer sees on the screen, but on the sophisticated, behind-the-scenes orchestration of technology, logistics, and strategy that transforms a simple click into a seamless delivery experience.

Historically, B2B transactions have been characterized by complex, relationship-driven processes that often require extensive negotiation and personalized service from sales representatives.  But the digital era has ushered in a new generation of efficiency-oriented, tech-savvy buyers who expect many of the same luxuries and seamless buying experiences in a B2B commerce setting as they do with B2C. Think about it – B2B may stand for “business to business”, but who is actually clicking that “buy” button for the business? A human being, who expects to find comprehensive product information, transparent pricing, and straightforward ordering processes wherever they’re purchasing. This level of efficiency and personalization in B2B has become a standard, not an exception.  

The Shift in B2B Buying Dynamics

From adopting advanced technologies for streamlined processes to leveraging data analytics for informed decision-making, B2B brands embracing the digital transformation will experience heightened agility, enhanced operational efficiency, and increased market relevance, as well as be able to engage with customers in new and innovative ways. In an era where convenience is king, B2B buyers expect the purchasing process to be as smooth and effortless as possible, including intuitive navigation and filtering on digital platforms, and access to up-to-date and accurate product information.  Transparency is another cornerstone of the expectations of the modern B2B buyer. This includes clear communication about product details and compatibility, along with upfront pricing models, shipping and stock availability, and environmental policies or relevant supply chain information. Lastly, the B2B buyers of today value streamlined operations and processes that save them time, resources, and effort, whether that’s through faster website performance, quick response times to inquiries, or efficient problem and query resolution.   

Managing the Evolution of the B2B Buying Experience

So how do B2B businesses keep up with these new demands and expectations? That’s where eCommerce platforms come into play. eCommerce platforms for B2B are specialized digital solutions designed to cater to the unique needs of these businesses, such as accommodating complex sales cycles, bulk orders, customized pricing agreements, and intricate product configurations.  The hallmark of a robust B2B eCommerce platform is its ability to provide a seamless, intuitive interface for both buyers and sellers.  For buyers, it should offer a convenient, straightforward shopping experience that mimics the experience of B2C platforms, with features like personalized product recommendations and detailed product information. For sellers, it should provide powerful tools for customer management, data analytics, and inventory control, and should integrate seamlessly with other business systems, such as CRM, ERP, or PIM solutions, allowing for a high degree of automation and customization.   

Salesforce B2B Commerce: A Leading Solution

Salesforce B2B Commerce is designed with the unique needs of business buyers in mind, and offers a low-maintenance but high-impact solution that revolutionizes how B2B businesses engage in online sales.  At the core of Salesforce B2B Commerce is the capability to craft personalized eCommerce experiences tailored to support large-volume and bulk purchases, with an easy interface and quick setup time that lends itself well to supporting a seamless, self-managing customer experience. As it’s part of the expansive Salesforce suite, Salesforce for B2B automatically integrates with Salesforce CRM, creating a cohesive, 360-degree view of the customer experience. Learn more about Salesforce B2B Commerce.  

Product Information Management and Salesforce B2B Commerce

Salesforce B2B Commerce also integrates seamlessly with other pieces in your tech stack. This is particularly important for systems that handle crucial product data, like your PIM.

What is Product Information Management (PIM)? 

Product Information Management (PIM) is both a systematic approach and a toolset that centralizes, organizes, and enriches product data, making it accessible to all stakeholders and distribution channels. A PIM solution itself serves as the backbone for managing the entire product record, including detailed product descriptions, titles, pricing, imagery, ingredients, sustainability information, multimedia content, and more.  The true importance of a PIM solution lies in its ability to:

• Enhance efficiency and collaboration: By centralizing product information, companies can avoid the pitfalls of data silos and inconsistent information as a PIM facilitates better collaboration among teams.
• Improve accuracy: PIM systems ensure that all product information is accurate, up-to-date, and consistent, reducing errors and enhancing customer trust.
• Speed time-to-market: Streamlined processes for managing product data can significantly accelerate the introduction of new products and updates to existing ones.
• Boost sales and customer satisfaction: Accurate, detailed, and easily accessible product information helps customers make informed buying decisions, leading to improved satisfaction and increased sales.
• Create a consistent experience across channels: A centralized product record  ensures that all sales and marketing channels are aligned with consistent and accurate product information, crucial for maintaining brand integrity and coherence.
• Provide scalability: As businesses grow and their product ranges expand, a PIM system can scale to accommodate increased data complexity and volume, ensuring that the management of product information remains seamless and efficient.
• Enrich data quality: Beyond mere storage, PIM systems often come equipped with AI-powered tools for data quality management and enrichment, allowing businesses to enhance their product data with additional information, translations, and optimized content for different markets and channels.

 

Integrating a PIM with Salesforce B2B Commerce

Integrating a PIM with Salesforce B2B Commerce as a B2B organization creates the required foundation for providing those high-quality, consistent, and omnichannel experiences that modern-day B2B buyers demand.  By acting as a central source of truth for all product data, the PIM solution ensures that all information displayed in the Salesforce B2B Commerce platform is accurate and up-to-date. Any changes or updates made in the PIM are then automatically reflected in the Salesforce platform. What does this mean in practice? New products can be introduced more swiftly and efficiently, as new product information is centralized, standardized, and enriched in the PIM before disseminating through Salesforce B2B Commerce. This also helps to establish clear data governance processes over product information, ensuring compliance with industry standards and cross-channel consistency.  This integration of a PIM system and Salesforce B2B Commerce has a measurable impact on B2B businesses primarily through:

• Seamless product discovery: Enhanced product information and easy navigation facilitate smoother discovery processes for B2B customers.
• Enhanced customer trust: Detailed, accurate product data enables customers to make well-informed purchase decisions that help create a sense of loyalty and trust, reducing the likelihood of returns and dissatisfaction.
• Reduced data errors: With automated data syncing and centralized management, the chances of errors in product information are drastically lowered.
• Improved operational efficiency: The streamlined processes for managing product information reduces manual efforts and operational costs while also enabling quicker responses to market demands.

 

The Right PIM for Salesforce B2B eCommerce

The B2B landscape is transitioning away from a traditional, complex buying process towards an approach more focused on efficiency and personalization that mirrors the B2C experience. Today’s tech-savvy B2B buyers demand seamless, tailored buying experiences characterized by easy access to detailed product information, transparent pricing, and simple order processes.  In order to meet these demands, B2B organizations need a scalable and flexible centralized product record that can easily integrate with eCommerce platforms like Salesforce B2B.    That’s where Akeneo PIM comes in. As a MACH-Certified PIM, integration with Salesforce, along with any ERP, DAM, or MDM solutions that are already included in your tech stack is simple and intuitive,  With a single source of truth for organized and optimized product data, Akeneo PIM enables your B2B organization to provide B2C-like experiences to customers for years to come.

Hello Akeneo Community, Today, I’m excited to talk about a natural progression in our journey at Akeneo. Our SaaS offering, Serenity, has grown into our most capable and fastest-evolving product, and in order to invest our resources efficiently, we will not be releasing any new versions of our PaaS (Flexibility) and on-premise offerings. This decision is a reflection of both the evolution of our customer needs and the advancements in our technology. Let me walk you through our journey, enriched with key insights and data points.  

A Little Bit of History 

Back in 2017, with an entirely on-premise customer base, we stepped into the cloud space. Our PaaS offering, Flexibility, was a bridge connecting our legacy of customization with the emerging cloud technology. It was an exciting time, with 45% of our customer base embracing PaaS by the end of 2018. However, as we continued our journey, we noticed a shift.   As you can see above, the landscape has changed over the years By the end of 2023, SaaS adoption soared to 80% of our customer base, a clear indicator of changing preferences and needs. We listened to our customers and acted accordingly – popular custom features from PaaS such as table attributes and import/export mapping were seamlessly integrated into Serenity, and the Akeneo App Store grew into an expansive, customizable network of expert partners that reduces the need for a dedicated PaaS solution. At Akeneo, we firmly believe in the importance of adaptability and responding quickly to market changes, and so these reasons and more support our focus on delivering SaaS capabilities in the future. Plus, transitioning to a SaaS only offering will result in:

• Operational Efficiency: Migrating between PaaS versions, while straightforward, consumed resources. We observed that our clients’ time and effort could be more impactful in areas other than technical upgrades.
• Exclusive Features for SaaS Users: Our newest innovations, including Activation and emerging AI capabilities are designed for SaaS, offering cutting-edge tools that were not possible with PaaS.
• Reduced Carbon Footprint: A SaaS model is more resource-efficient, aligning with our goal to minimize environmental impact. We estimate the carbon footprint of a PaaS instance to be about twice that of a SaaS instance.
• Focus on Innovation: Freeing our resources from PaaS development allows us to expedite new features and products, fostering a culture of rapid innovation.

 

Comprehensive Support for PaaS Customers

Though we’re excited for the future, I’d like to take a second and acknowledge the importance of a seamless transition and continued support for our PaaS customers, which is why we’re investing nearly $5 million in resources designed to mitigate concerns, address potential challenges, and enhance the overall migration experience. This includes:

• Dedicated Professional Services Team: To ensure a smooth transition to SaaS, we have assembled a dedicated team of 13 individuals, comprised of both Product and Professional Services team members, at your service. This team is specifically tasked with assisting our PaaS customers in migrating to SaaS over the next 2.5 years, providing tailored support and expertise every step of the way.
• Focused Product Team: Understanding that feature parity is crucial, we have a dedicated product team identifying and addressing any major feature gaps that could hinder migration. This team is committed to ensuring that all critical functionalities available in PaaS are seamlessly transitioned or adapted to the SaaS environment.
• Extended Support Period: We’re extending support for the last PaaS version, V7, until September 2026, giving ample time for our customers to plan and execute their migration with our full support.
• Investment in App Engine: We’re also enhancing our App Engine to offer more SDK-like capabilities, providing more flexibility and customization options in the SaaS environment.

 

A Migration to Serenity 

This shift towards SaaS is a logical step in our growth trajectory, driven by data, customer feedback, and our commitment to innovation and sustainability. It’s a testament to our adaptability and dedication to providing the best solutions for our community.  If you have any questions or concerns about this migration, please do not hesitate to reach out to your point of contact at Akeneo. We’re excited about this new phase and grateful for your continued support!

Akeneo was highlighted as a leader in optimizing omnichannel product experiences and featured among the top 15 technology companies in the latest equity funding round. 

 

 

About Viva Technology

VivaTech accelerates innovation by connecting startups, tech leaders, major companies, and investors responding to our world’s biggest challenges. Each year, over four exciting days in Paris, VivaTech creates Europe’s biggest technology and startup event, exploring the most disruptive topics in tech with world-premiere demos, launches, and conferences in a collaborative ecosystem. This is where business meets innovation. Join us for the eighth edition of VivaTech 22-25 May 2024. For more information go to our website at https://vivatechnology.com/media and follow us on social media @VivaTech. 

 

About GP Bullhound

GP Bullhound is a leading technology advisory and investment firm, providing transaction advice and capital to the world’s best entrepreneurs and founders. Founded in 1999 in London and Menlo Park, the firm today has 13 offices spanning Europe and the US. For more information, please visit www.gpbullhound.com.

 

About Akeneo

Akeneo is the product experience (PX) company and global leader in Product Information Management (PIM); creating a world where every product interaction is an experience that guides consumers and professionals to the best purchase, anytime, anywhere. Akeneo empowers business leaders with software, education, and an engaged community all focused on the practice of product experience management.

Leading global brands, manufacturers, distributors, and retailers, including Chico’s, CarParts.com, TaylorMade Golf, Rail Europe, Kering, and more trust Akeneo to scale and customize their omnichannel commerce initiatives. Using Akeneo’s intelligent Product Cloud, companies can create elevated product experiences with user-friendly and AI-powered product data enrichment, management, syndication, and supplier data onboarding; as well as a comprehensive app marketplace and partner network to meet business and buyer needs.

For more information: akeneo.com

Spring has always been a season of renewal and innovation, and this year, it’s brought something truly special for the Product Experience (PX) Community. In case you missed it, the team at Akeneo announced some pretty exciting updates during the Spring Release keynote at Unlock Boston. From a sleek new Salesforce App to new sales channels available in Akeneo Activation, there are a slew of developments that we’re buzzing for, but there is one area that we’re particularly excited about: AI. In a world where technology continually shapes and reshapes how we interact and shop, staying ahead of the curve is not just an advantage – it’s a necessity. That’s why we’re so excited to unveil some of the newest native AI capabilities within the Akeneo Product Cloud. But first . . .  

What’s a Product Cloud?

A product cloud is a composable SaaS-based technology suite designed to orchestrate, activate, and optimize the entire product story across all owned and unowned channels. The modular nature of a product cloud means that your team is able to personalize your tech stack to fit the exact needs of your organization.  Plus, a product cloud should be able to support the entire product record, including both hot (dynamic) and cold (static) data. From pricing to digital assets to size dimensions to user-generated content, the product cloud acts as a single system of record to house all of this data that is scattered across different technologies. The last defining feature of a product cloud is its usability; any number of users, managers, administrators, developers, or integrators should be able to hop in at any point and understand what product information lives where, how to access it, and how to syndicate it to the right channels in the right way. Technologies that require extensive IT knowledge, or rely on individual employees who know how to operate the system, simply aren’t scalable.  

The Intelligent Product Cloud

After acquiring the AI platform Unifai in September 2023 and announcing over 20 AI apps in the Akeneo App Store, the team here at Akeneo has invested heavily in AI, even assembling a team of experts with deep knowledge in the field of AI who will serve as the foundation for all future AI innovations in the Akeneo Product Cloud. But before we get too ahead of ourselves, let’s take a look at some of the new and improved AI capabilities within the Akeneo Product Cloud that were announced in our 2024 Spring Release.

1. Native GenAI in Akeneo PIM

In the fast-paced nature of today’s market, the ability to quickly generate and adapt content is crucial. Harnessing the power of generative AI, Akeneo PIM now enables your business to create bulk product content in minutes that not only resonates with your target audience but also aligns with your brand voice and product specifics. Expanding into global markets requires content that speaks the language of your customers – literally. New functionality in Akeneo PIM also offers the ability to translate product data and romance copy into more than 50 languages, enabling your organization to easily adapt content to meet regional market expectations and personalize the customer experience. Not only do these updates amplify productivity, accuracy, and scalability in the content creation, translation, and localization process, but they also help to streamline the entire product content creation and translation process as you’ll be working within the product edit form that you’ve already been working in in Akeneo PIM – no additional tools or AI expertise needed.  

2. Native GenAI in Akeneo Supplier Data Manager

Akeneo Supplier Data Manager is also now equipped with native AI capabilities to onboard suppliers faster and more efficiently.  By automating critical processes such mapping and normalizing supplier data to PIM attributes, categorizing products according to PIM families and categories, and enriching product records with unstructured product data, and by simplifying the complexities involved in handling vast amounts of supplier information, Akeneo SDM is creating a more streamlined and efficient supplier onboarding process for all. How you manage your supplier relations has a direct impact on the customer: faster onboarding means businesses can bring their products to market more quickly, and streamlined operations can result in less data errors and inconsistencies. Overall, Akeneo’s AI-powered Supplier Data Manager enables your organization to:

• Automate some of your more manual grunt work, ensuring data consistency for product experiences across all channels
• Improve time-to-market
• Increase the accuracy and completeness of your entire product data record
• Foster a more efficient, mutually beneficial collaboration between your organization and your suppliers

3. AI for PX in the Akeneo App Marketplace

The Akeneo App Marketplace is the third exciting area of AI investment announced in Spring Release 2024. With over 200 apps and integrations, including 37 new additions in 2023 alone, the Akeneo App Marketplace offers an unparalleled array of technologies that leverage the power of AI to transform the quality, accuracy, and relevance of product information across all channels and markets. Though not an exhaustive list, a few noteworthy additions to the Marketplace are:

• Grand Shooting – Catalog Sync App: This is an AI-powered solution which facilitates image quality control by retouching non-compliant images in real time. This real-time correction ensures that product images are always of the highest quality, enhancing the visual appeal of online catalogs and improving the overall product experience for customers.
• Copysmith AI App: Recognizing the importance of compelling and accurate product descriptions in eCommerce, the Copysmith AI App empowers users to generate engaging product narratives effortlessly, simplifying the creation of product descriptions and conveying key product features effectively.
• Smartling App: This application supports seamless automation and management of product descriptions and other content across different languages, facilitating a truly global reach for businesses. By automating the translation and localization process, this app ensures that product information is accurate, culturally relevant, and resonant with international audiences, thereby enhancing the global product experience.

Our ever-growing selection of AI apps in the Akeneo App Store supports the flexibility of a composable commerce tech stack, while enabling customers to take advantage of AI innovation from trusted business partners.  

The Future of the Intelligent Product Cloud

AI is changing the name of the game, and those organizations who embrace the future of technology will be the ones to stand the test of time as AI only promises to become more and more prominent in our everyday lives. These native GenAI enhancements to the Akeneo Product Cloud are designed to empower businesses to streamline workflows and elevate the overall quality of product experiences across the globe. But this is just the beginning! With our team of AI experts on board, we are only getting started with our AI journey, so make sure you stay tuned to see what’s coming next. For those keen to explore these advancements further, we invite you to discover the full details of our 2024 Spring Release. Learn more here!

As we commemorate International Women’s Day, we’d like to take a moment to reflect on the ongoing journey towards gender equality within the tech sector. As of late 2023, women made up about 35% of the tech workforce, but that number starts to dip as you climb up the corporate ladder. In C-suite leadership roles, women make up only 25%, and that dwindles to a measly 5% for women of color.  The tech industry continues to be a hotbed of innovation and transformation, influencing virtually every aspect of our lives – women have to have a seat at that table of discussion, not just as participants but as leaders shaping the future of technology.  In light of this, we’d like to highlight the voices of a few great women leaders in our industry. At NRF this year, the Women of MACH recorded an episode on emerging trends to come in this year and beyond.  Hosted by Amanda Cole, Chief Marketing Officer at Bloomreach, the episode featured insightful discussions with Kristin Naragon, Chief Strategy Officer at Akeneo; Casey Gannon, VP of Marketing & Technology Partnerships at Bold Commerce; and Isabell Aakervik, Chief Expansion Officer at Sitoo.  Together, they shared their expertise on a variety of interesting topics, including generative AI, omnichannel experiences, strategies for reducing returns, and the future of sustainability initiatives. Plus, these women share their advice on how to not only navigate a male-dominated industry, but how to bring your fellow women along. You can watch the full video here or check out the 5 key takeaways we’ve distilled for you below.

1. The rising prevalence of genAI

“I think a lot of our technology companies are learning how to respond to AI and make sure that we focus on the customer experience.” – Amanda Cole, Chief Marketing Officer, Bloomreach Throughout 2023 and into 2024, the conversation around AI and large language models gained significant momentum. The women in the panel shared how their individual companies are navigating this new wave of technology, and how they incorporated AI-powered solutions to enhance operations across various instances. While the potential of AI can often be hyperbolized and oversold, the panel focused on the practical use cases that companies could employ AI technology today, such as:

• Generating and enriching product content
• Cleansing data for reduced inaccuracies
• Enhancing work automation
• Supporting customer service roles
• Automating content translation

2. The importance of omnichannel experiences

The “shop anywhere” concept has been gaining traction for a while now, underlining the need for brands and retailers to offer seamless experiences across every customer touchpoint. The women of the panel touched on innovative strategies for merging the digital and physical realms of customer engagement, and highlighted the consequences of incomplete, poor product experiences; the dreaded return. To meet these growing customer expectations, brands and retailers are increasingly adopting new technologies that blur the lines between online and offline experiences, be it unified customer profiles, integrated inventory management systems, or advanced analytics platforms to personalize customer interactions regardless of the touchpoint. The goal is to create a shopping experience that is not only convenient but also consistent, allowing consumers to switch between channels and touchpoints effortlessly. The panel also delved into the specific challenges and opportunities presented by returns that occur from poor product experiences. They highlighted that returns are an integral part of the shopping experience but often come with significant logistical challenges and environmental impacts, and even shared their tips on how to minimize the impact of these returns, particularly through new technologies.

3. Flexible, adaptable tech stacks to prepare for Digital Product Passport legislation

As environmental and social consciousness continues to influence consumer choices, the ability to offer insight into product supply chains and manufacturing processes is a key differentiating factor. As the panelists highlight, although consumers are increasingly seeking out brands that can demonstrate responsibility and transparency, these factors will soon not just be suggested improvements to the customer experience but a global regulation. The European Digital Product Passport (DPP) initiative, part of the broader European Green Deal approved in 2020, is setting a new precedent for transparency in supply chains. The DPP aims to consolidate data regarding a product’s lifecycle, including its environmental impact and supply chain details, into a single, accessible format. This initiative mandates a level of openness that requires retailers to rethink their approach to data management and sharing across the value chain, including manufacturers, repairers, and consumers. Enter MACH architecture (Microservices-based, API-first, Cloud-native SaaS, and Headless) – a technological framework that offers the agility and flexibility retailers need to navigate these evolving demands and regulations. MACH architecture enables retailers to decouple their digital platforms into manageable, interchangeable components, which can be updated or replaced without disrupting the entire system. This modularity is particularly advantageous for adapting to requirements like those introduced by the DPP, as it allows for rapid integration of new functionalities or adjustments to existing processes.

4. Mitigating product returns through product information

In a retail landscape where efficiency and sustainability are increasingly paramount, the discussion of the NRF panelists shed light on a trend with substantial impact: mitigating product returns through enhanced product information.

A strategic approach to product returns can lead to more efficient customer acquisition, higher conversion rates, and strengthened customer loyalty, among others. The first step? Identify the critical details that customers may need at any point in their journey. By anticipating the questions and concerns that customers may have, you can ensure that your product information addresses their needs proactively. Once you’ve identified the essential product information, gather and enrich the data to create compelling product content (this is where genAI, once again, plays a big role, as highlighted by our panelists!). It’s also crucial to localize the product content for different regions and channels to ensure relevance and resonance with diverse audiences and channels. By ensuring consistency and accessibility across all channels, you can empower customers to make informed purchasing decisions without the need for returns.  

5. The importance of mentorship and networking for women in tech

As the discussion on emerging retail trends drew to a close, the panelists shifted focus towards fostering inclusivity and empowerment for women and diverse groups within the tech industry. Their conversation underscored the crucial roles of mentorship, self-belief, and the embrace of vulnerability as a strength in navigating the path to representation in technology and leadership roles. Below are just a few of our favorite quotes: Casey Gannon: “I have two really simple pieces of advice. The first is to find a mentor who is where you want to be  in 5 to 10 years – particularly, if you’re a woman, try to find a woman mentor {in that position}. The second is just to prioritize your network and particularly with other women in your industry.” Kristin Naragon: “If you’re a woman in a position of some influence or power, I think it’s really important not only to find and seek out females who you can lift up with you but also to really mentor the men who are coming up the ranks. I take the time on a very regular basis to work with men because it’s important for them to see our styles and how we lead, and to make sure that they feel, when they rise into those positions of power, that they understand how women lead in similar and different ways.” Isabell Aakervik: Believe in yourself – we women are very good at not believing in ourselves, so I would say stay strong!  Amanda Cole: This panel is four powerhouse professionals who just all happen to be women in MACH. There’s access to experienced professionals who also represent diverse groups and hopefully we continue to see growth in that. My advice would be, do not be a loud negative voice very similar to what Isabelle was saying! Don’t be your worst critic, and definitely take moments to celebrate yourself.  

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  International Women’s Day acts as a reminder for us all that the journey towards gender equity and diversity in tech is a collective effort. It requires the engagement of individuals and organizations alike to create environments where everyone has the opportunity to succeed and contribute to the technological advancements shaping our world. Championing inclusivity, mentorship, and support enables more voices to be heard and more talents to shine within the tech industry, and if we can continue to foster an environment where innovation thrives and diverse perspectives are valued, we can look forward to a future where the tech industry is as rich and varied as the world it aims to serve.