My 30-year technology career has taught me many things…and one big thing: the companies that treat technology as a cost center are the ones that get blindsided. In manufacturing, that blindside is already here — and it’s wearing the name tag “AI.”

For decades, manufacturers have been locked into rigid systems, long upgrade cycles, and siloed data. The result? Operations that run on yesterday’s insights while competitors are making tomorrow’s moves. Sound familiar? It’s the same trap traditional IT outsourcing fell into — and it’s just as deadly in the age of smart manufacturing.

The AI Advantage in Manufacturing

Oracle Fusion AI for Manufacturing Smart Operations isn’t just another software upgrade. It’s a shift from reactive to predictive, from siloed to synchronized. Think:

• Real-time anomaly detection that flags quality issues before they hit the line.
• Predictive maintenance that slashes downtime and extends asset life.
• Intelligent scheduling that adapts to supply chain disruptions in minutes, not weeks.
• Embedded analytics that turn every operator, planner, and manager into a decision-maker armed with live data.

This isn’t about replacing people — it’s about giving them superpowers. Read more from Oracle here.

Proof in Action: Roeslein & Associates

If you want to see what this looks like in the wild, look at Roeslein & Associates. They were running on disparate, outdated legacy systems — the kind that make global process consistency a pipe dream. Perficient stepped in and implemented Oracle Fusion Cloud Manufacturing with Project Driven Supply Chain, plus full Financial and Supply Chain Management suites. The result?

• A global solution template that can be rolled out anywhere in the business.
• A redesigned enterprise structure to track profits across business units.
• Standardized manufacturing processes that still flex for highly customized demand.
• Integrated aftermarket parts ordering and manufacturing flows.
• Seamless connections between Fusion, labor capture systems, and eCommerce.

That’s not just “going live” — that’s rewiring the operational nervous system for speed, visibility, and scale.

Why Standing Still is Riskier Than Moving Fast

In my words, “true innovation is darn near impossible” when you’re chained to legacy thinking. The same applies here: if your manufacturing ops are running on static ERP data and manual interventions, you’re already losing ground to AI‑driven competitors who can pivot in real time.

Oracle Fusion Cloud with embedded AI is the equalizer. A mid‑sized manufacturer with the right AI tools can outmaneuver industry giants still stuck in quarterly planning cycles.

Where Perficient Comes In

Perficient’s Oracle team doesn’t just implement software — they architect transformation. With deep expertise in Oracle Manufacturing Cloud, Supply Chain Management, and embedded Fusion AI solutions, they help you:

• Integrate AI into existing workflows without blowing up your operations.
• Optimize supply chain visibility from raw materials to customer delivery.
• Leverage IoT and machine learning for continuous process improvement.
• Scale securely in the cloud while keeping compliance and governance in check.

They’ve done it for global manufacturers, and they can do it for you — faster than you think.

The Call to Action

If you believe your manufacturing operations are immune to disruption, history says otherwise. The companies that win will be the ones that treat AI not as a pilot project, but as the new operating system for their business.

Rather than letting new entrants disrupt your position, take initiative and lead the charge—make them play catch-up.

For manufacturers, customer experience is no longer a differentiator, but a growth strategy. We’re proud to share that Perficient was selected as a company interviewed for Forrester’s May 2025 report, “Transform Your Manufacturing Extended Enterprise For Maximum Business Impact.”  We believe being interviewed for this report underscores our leadership in helping manufacturers modernize their digital ecosystems to deliver seamless, scalable, and personalized experiences across the value chain. 

Access the report here. 

Partnering With Manufacturing Companies As They Digitally Mature 

At Perficient, we have a proven track record in integrating complex systems like PLM (Product Lifecycle Management), PIM (Product Information Management), and OMS (Order Management Systems) to streamline product content and availability. 

As Forrester notes in the report, “As B2C digital experiences become more convenient and more B2B buying groups include younger members, manufacturers must curate, enrich, and distribute product content that supports compelling customer experiences at every touchpoint in the product buying group’s journey.” 

Our client-centric approach addresses these real-world challenges in manufacturing CX — from abandoned carts due to inaccurate lead times to inconsistent product content across channels. We also regularly publish thought leadership on leveraging AI and generative AI to scale personalization and automate product data management. 

“We’ve seen firsthand how aligning product data, systems, and customer expectations can unlock real business value, and we’re proud to contribute to the broader industry conversation on what it takes to lead in this space.” – Kevin Espinosa, Director of Digital Strategy and Manufacturing Industry Lead 

Perficient’s Vision for the Manufacturing Extended Enterprise 

Key insights the Perficient team provided in their interview for the Forrester report included the critical role content plays in customer experience, the responsible use of AI, strategies for overcoming organizational silos, the importance of inventory accuracy, and the path to digital maturity. 

Perficient’s position is that these changes should be addressed with urgency, and we are well-positioned to offer expert guidance. Below are some brief perspectives on each of these topics. 

Content is the Cornerstone of CX 

Accurate, timely, and localized product content is essential to building trust and driving conversions. This is especially true in B2B and D2C manufacturing, where buying decisions hinge on technical accuracy and availability.  

According to a recent Perficient survey of multiple manufacturers, commercial customers, and consumers of connected products, trust in a manufacturer is critical for the end consumers in making a buying decision. Providing consistent, accurate and up to date information about the products is a crucial first step in establishing this trust factor. 

AI is a Game-Changer — But Only When Used Responsibly 

Generative AI is transforming areas like product design, search, product descriptions and recommendations, virtual agents, agent assistance, coding, content creation, narrative reporting, and process automation, but human oversight remains critical. Our vision for the future of genAI includes agentic architectures where AI agents validate each other’s outputs and flag for human review, ensuring quality and compliance before content reaches the customer. 

System Integration is the Secret to Speed and Scale 

Manufacturers often struggle with siloed systems and disconnected teams. We’ve helped clients overcome these barriers by integrating PLM and PIM systems, establishing clear ownership models and creating enterprise-wide catalogs that reduce friction and accelerate time-to-market. 

Syndication and Availability Drive Revenue 

A number of our clients have experienced abandoned carts and dissatisfied customers when ATP (available-to-promise) and lead times are not available or inaccurate. Further, if the ordering experience is different online than the information received when calling an agent, the credibility of the brand is at risk. From ATP data to local inventory visibility, we help manufacturers ensure that what’s promised online matches what’s available in reality.  

Maturity Matters 

We help manufacturers assess and evolve their digital maturity, from foundational capabilities like centralized content management to advanced practices like AI-powered hyper-personalization and dynamic UI generation based on user personas. 

Invest in End-to-End Digital Transformation for Manufacturing 

We believe that Perficient being interviewed for the Forrester report is a validation of our commitment to helping manufacturers transform their extended enterprise for a differentiated customer experience. Whether you’re looking to modernize your product content strategy, integrate complex systems, or harness the power of AI, Perficient is the partner to help you lead with confidence. 

Explore our manufacturing industry expertise and our portfolio of commerce and contact center capabilities that make an excellent customer experience a reality. 

This blog is written for developers, merchandisers, or client teams looking to display visual indicators (e.g., “New”, “Sale”, “Non-Returnable”, “Best Seller”) on products within the storefront. In Ecommerce, badges are small visual cues that communicate important product information to customers, such as “New Arrival”, “Sale”, or “Limited Stock”. In Optimizely Configured Commerce (Spire), product badges can be a powerful way to highlight key promotions or product statuses, thereby improving the user experience.

This blog post walks through how to enable and customize badges within Spire-based sites.

What Are Product Badges?

Badges are visual elements displayed over product images or titles to indicate special status or promotions. Common use cases include:

• New – recently added products
• Sale – discounted items
• Non-Returnable – not returnable items (innerwear, Digital downloads, Razors or blades, etc.)
• Best Seller – top-performing SKUs
• Limited Stock – low inventory

Step 1: Enable and Configure Badges in the Admin Console

• Log in to the Admin Console
• Go to Admin Console > Marketing > Product Badges

• Click Add Badge

• Fill in the fields:
  • Name: e.g., “Sale”
  • Activated On: Start date of showing the “Sale” product badge on the Product. The default current date.
  • Deactivated On: End date of showing “Sale” product badge on Product.
  • Sort Order: Sort Order determines badge display order in cases where multiple badges are displayed. Items with the same sort order will be displayed alphabetically by Badge Name.
  • Display Locations:
    1. Overlay – On/Off: Shows badge as an overlay on main product images
    2. Badge Widget – On/Off: Shows badge wherever the badge widget is displayed. You can assign badges manually or automate them based on rules via custom logic.
    3. Badge Styling:

       Badge Type: Text or Image

       Text

       1. • 1. • Display Text: Add display text on product e.g “Sale”. Translate this text in other languages.
               • Text Color Hex Code: Enter hex code without #. e.g. 000000
               • Badge Color Hex Code: Enter hex code without #. e.g. fffffff
               • Badge Style: Select “Round” and “Rectangle”
               • 

       Image

       1. • 1. • Large Image Badge Path: Browse the image path and preview it.
               • Image Alt Text: Add image alternate text so that text will be shown if the image is not available.
               • 
       1. • Badge Positioning:
            1. Large Image Placement: Default “None”. Other Top Center, Top Left, Top Right, Bottom Center, Bottom Right, and Bottom Left
            2. Large Image Text Size: Select Large, Mediu,m and Small

       Create a new badge as “Sale,” and the badge styling is text.

       

Step 2: Assign Badges to Products, Product Rules, and Product Attributes

Products

Click on the “Assign Products” button

• Open the pop-up and search for products.

• Select products. Click on the “Assign” and “Done” buttons.

• This badge is assigned to selected products.

Product Rules

You can create product rules based on “Product Custom Properties” and “Product fields”.

Product Attributes

You can assign multiple product attributes for this badge.

Step 3: Enable Product Badges in CMS

1. Go to Content Admin
2. Go to any product list page
3. Click on the Edit icon

4. Click on the Edit icon on “ProductList/ProductListCardList” widget

• • Show Image Badges and set the maximum number of image badges
  • Show Text Badges and set the maximum number of text badges

Step 5: Display Product Badges in Spire Frontend

Text Product Badges example:

Product List Page:

Product Detail Page:

Conclusion

Badges in Optimizely Configured Commerce are a simple yet effective way to elevate merchandising on your storefront. By combining back-office configuration with simple frontend customizations, you can create a more engaging and informative shopping experience.

Can a Product Information Management (PIM) System Make Your Data AI-Ready?

Yes, a PIM system can help get your data ready for AI—but only if it’s set up the right way.

If you’re managing product info across channels, you already know that bad data means bad results. And if you’re thinking of adding AI—like auto-tagging, personalization, or predictive tools—your product data needs to be spot-on.

This post breaks down what “AI-ready data” actually means, why messy product data kills your AI plans, and how a PIM system fits into fixing it.

What Does “AI-Ready” Data Mean?

AI-ready data is clean, complete, consistent, and structured to match what the AI needs to do. If any part of that is missing, the results from your AI model will be wrong or useless.

Gartner outlines five key steps to make data AI-ready:

1. Assess the data needed for each AI use case. You can’t just throw all your product data into an AI tool and expect magic. You need to know what the AI is supposed to do—recommend products, tag images, write descriptions—and check if the data supports that.

2. Align your data with the AI’s goals. Let’s say your goal is to personalize search results. That means every product needs the right tags, images, and categories. If that info’s missing or inconsistent, AI can’t deliver what you want.

3. Set clear rules for data governance. This includes naming standards, formatting rules, and tracking changes. AI systems rely on patterns. Without strong data governance, the AI can’t recognize patterns well enough to learn or predict accurately.

4. Use metadata to give your data context. Metadata helps AI understand what each piece of data means. It’s how you tell a machine the difference between a color and a size, or between an image and a feature.

5. Make data everyone’s job. If only IT or product teams handle data cleanup, you’ll never scale. You need marketing, content, and sales to be part of the process. That cross-team input helps AI models learn faster and smarter.

Without these steps, AI tools waste time trying to clean or guess data—and that leads to mistakes.

Common Product Data Problems That Hurt AI Outcomes

AI depends on structured, reliable data. When product data is messy or incomplete, AI tools can’t learn correctly or make accurate decisions.

Here are the most common issues that mess up AI results:

1. Missing values. If your product descriptions don’t always include size, color, or materials, the AI can’t group or recommend items correctly.

2. Inconsistent formats. “Red”, “RED”, and “#FF0000” might mean the same thing to people—but not to machines. AI models treat each format as different unless the data is standardized.

3. Duplicate entries. Two versions of the same product can confuse the AI. It might see them as separate products and deliver incorrect suggestions or analytics.

4. Unstructured content. If your product titles are crammed with keywords but no pattern, AI can’t extract useful meaning. Structured data is easier for models to work with.

5. Lack of metadata. AI models need more than just the product image or title. Without tags, category labels, and usage context, the model can’t learn how to connect products.

6. Outdated info. AI training requires current, real-world data. If product details change often but don’t get updated fast enough, the AI works off bad inputs and gives wrong outputs.

Each of these issues reduces the accuracy of your AI’s predictions, recommendations, or automations.

How PIM Systems Solve These Problems

A PIM system helps fix the data issues that stop AI from working well. It brings structure, control, and context to your product data—all of which AI needs to deliver value.

Here’s how PIM lines up with the five AI-readiness steps from Gartner:

1. Data aligned with use case: In a PIM, you define which attributes are required for each product category. If your AI needs color, size, and material to personalize product recommendations, PIM ensures that data is there—before the product is published.

2. Data normalization: PIM tools standardize formats. “Blue” won’t show up as “BLU” or “navy blueish” in different listings. The system enforces data rules, so your AI can trust the inputs.

3. Data governance: PIM systems let you set validation rules, version tracking, and user permissions. This means every change is tracked, and only approved data moves forward—key for AI systems that depend on clean histories.

4. Metadata management: PIM systems store and manage metadata like categories, usage tags, and even SEO terms. This extra layer helps AI models understand context—whether it’s matching a product to a search or choosing the best image.

5. Cross-team collaboration: With a PIM, marketing, product, and eCommerce teams work from the same source. This reduces errors, speeds up updates, and gives AI a steady flow of reliable product information.

By solving these issues at the source, a PIM platform creates the clean, structured, and well-governed data foundation that AI tools need to do their job right.

Can PIM Alone Get You There?

A PIM system solves the data problems—but it doesn’t replace the AI stack. Think of PIM as the prep kitchen. It gets everything clean, sorted, and ready to go. But you still need the right tools to cook.

Here’s what PIM does well:

• Cleans up product attributes

• Standardizes formats and values

• Adds missing metadata

• Makes data accessible across teams

But once the data is ready, you still need AI platforms to do the heavy lifting. That includes:

• Machine learning models to drive personalization

• Predictive tools to forecast demand or returns

• Agentic AI tools that take action (like re-tagging or alerting on gaps)

• Analytics platforms to visualize outcomes

So no, a PIM alone won’t give you full AI capabilities. But without a PIM, your AI tools will spend most of their time cleaning up your mess instead of giving you results.

PIM Is Your First Step to Smarter AI

AI can only work well when the data behind it is complete, consistent, and structured. A PIM system lays that foundation. It organizes your product information, enforces data standards, and adds the context that AI tools need to operate accurately.

Without clean data, AI models deliver flawed results. But with a strong PIM in place, you give AI the best chance to succeed—whether it’s automating product tagging, powering recommendations, or optimizing digital experiences.

Need help setting up a PIM or making your product data AI-ready?
Connect with us today—We help businesses use the right mix of PIM and AI to get real results faster. Whether you’re starting fresh or upgrading what you’ve got, we’ll make sure your data is ready for the next step.

Optimizing B2B E-commerce with Optimizely Commerce: Best Practices and Key Features

In today’s fast-paced digital landscape, businesses need robust and scalable e-commerce solutions to meet the growing demands of B2B buyers. Optimizely Commerce (formerly Insite) is a leading platform that empowers businesses with cutting-edge tools to enhance the online purchasing experience.

In this blog, we’ll explore Optimizely Commerce’s key features, which make it a powerful choice for B2B businesses, and discuss best practices for maximizing its potential.

Why Optimizely Commerce for B2B?

Unlike B2C platforms, B2B commerce has complex requirements, such as bulk orders, contract pricing, and account-based purchasing. Optimizely Commerce is explicitly designed to address these challenges.

5 Key Features That Drive B2B Success

1. Personalized Customer Experiences

• Leverage AI-driven product recommendations.
• Provide dynamic pricing based on contracts and customer segments.

2. Advanced Account Management

• Self-service portals for order history, quotes, and invoices.
• Multi-user roles with approval workflows.

3. Seamless Integration with ERP & CRM

• Automate order processing and inventory management.
• Ensure real-time data synchronization.

4. Mobile-Friendly & Headless Commerce

• Optimize for mobile experiences.
• Leverage API-driven commerce for greater flexibility.

5. Powerful Search and Merchandising

• AI-powered search to deliver relevant results.
• Customizable catalogs and product visibility settings.

5 Best Practices for Maximizing Optimizely Commerce

1. Optimize Site Performance

• Use caching mechanisms for faster page loads.
• Ensure a responsive design for mobile buyers.

2. Leverage Personalization & AI

• Tailor content and pricing based on customer behavior.
• Implement AI-driven product recommendations.

3. Enable Self-Service Capabilities

• Provide customers with self-service portals to check order history, request quotes, and manage accounts.

4. Streamline Checkout & Payments

• Simplify the checkout process with saved payment options.
• Offer multiple payment methods, including net terms and PO-based ordering.

5. Continuously Analyze & Improve

• Use analytics to track customer behavior and identify trends.
• A/B test different UI elements for better engagement.

Conclusion

Optimizely Commerce offers a powerful and flexible solution for businesses looking to optimize their B2B e-commerce operations. By leveraging its robust features and following best practices, companies can enhance customer experiences, improve efficiency, and drive revenue growth.

Is your business ready to take B2B e-commerce to the next level? Start optimizing with Optimizely Commerce today!

Artificial Intelligence (AI) is revolutionizing B2B ecommerce, enabling capabilities such as personalized product recommendations, dynamic pricing, and predictive analytics. However, the effectiveness of these AI-driven solutions depends heavily on the quality of the underlying data. Despite AI’s potential, poor data governance remains a significant challenge in the industry. A recent Statista survey revealed that 25% of B2B ecommerce companies in the United States have fully implemented AI technologies, while 56% are experimenting with them.

As AI adoption grows, B2B companies must address data quality issues to leverage AI’s benefits fully. Anyone who has spent time in the B2B industry will acknowledge that quality data is often a struggle. This article explores the critical importance of clean data in AI applications and offers strategies for improving data governance in the B2B ecommerce sector.

Common Symptoms of Bad Data Governance

Bad data governance is a pervasive issue in the B2B ecommerce landscape, particularly in industries like manufacturing, where complex supply chains and product catalogs create unique challenges. Here are some of the most common symptoms:

1. Duplicate Records: Customer and product data often contain duplicate entries due to inconsistent data entry processes or a lack of validation protocols. For example, a single customer might appear in the database multiple times with slight variations in name or contact information, leading to inefficiencies in communication and order processing.
2. Inconsistent Formatting: Manufacturing and distribution often involve extensive product catalogs, and inconsistencies in SKU formats, product descriptions, or units of measurement can disrupt operations. For instance, some entries might use “kg” while others use “kilograms,” confusing systems and causing inventory management and procurement errors.
3. Outdated or Missing Data: Stale data, such as outdated pricing, obsolete product details, or inactive customer accounts, can lead to misinformed decisions. Missing data, like incomplete shipping addresses or contact details, can result in delayed deliveries or lost opportunities.
4. Siloed Data Systems: Many B2B companies, especially in manufacturing, rely on disparate systems that don’t communicate effectively. A lack of integration between ERP systems, CRMs, and ecommerce platforms leads to fragmented data and manual reconciliation efforts, increasing the risk of errors.
5. Unreliable Vendor and Supplier Information: Manufacturing businesses often deal with a large network of suppliers, each with varying formats for invoices, contracts, and delivery schedules. Poorly managed supplier data can result in delayed production, stockouts, or overordering.

Why is Bad Data Governance So Prevalent in B2B Manufacturing?

Unlike B2C industries, where streamlined data processes are often a core focus, manufacturing businesses face unique challenges due to their operations’ complexity, reliance on legacy systems, and decentralized structures. Understanding why these problems are so prevalent is key to addressing the underlying causes and fostering long-term improvements.

1. Complexity of Operations: Manufacturing involves numerous moving parts—raw materials, suppliers, distributors, and customers—making data governance inherently more challenging. The sheer volume of data generated across the supply chain increases the likelihood of inconsistencies.
2. Legacy Systems: Many B2B manufacturing companies rely on outdated legacy systems not designed for modern ecommerce integration. These systems often lack robust data validation and cleaning mechanisms, perpetuating bad data practices.
3. Decentralized Operations: Manufacturing companies frequently operate in multiple locations, each with its own systems, processes, and data entry standards. This decentralization contributes to a lack of standardization across the organization.
4. Focus on Production Over Data: In traditional manufacturing mindsets, operational efficiency and production output take precedence over data accuracy. Thus, data governance investments may be considered a lower priority than equipment upgrades or workforce training.
5. Limited Awareness of the Impact: Many B2B organizations underestimate the long-term impact of bad data on their operations, customer satisfaction, and AI-driven initiatives. The focus often shifts to immediate problem-solving rather than addressing root causes through improved governance.

By recognizing these symptoms and understanding the reasons behind poor data governance, B2B manufacturing companies can take the first steps toward addressing these issues. This foundation is critical for leveraging AI and other technologies to their fullest potential in ecommerce.

Why Clean Data Governance is Non-Negotiable in the AI Era

AI thrives on data—structured, accurate, and relevant data. For B2B ecommerce, where AI powers everything from dynamic pricing to predictive inventory, clean data isn’t just a nice-to-have; it’s the foundation for success. Without clean data governance, AI systems struggle to provide reliable insights, leading to poor decisions and diminished trust in the technology.

As the B2B commerce world embraces AI, those who recognize and prioritize addressing a systemic industry problem of bad data will quickly move to the front of the pack. Garbage in, garbage out. Implementing AI tools with bad data will be doomed to failure as the tools will be ineffective. Meanwhile, those who take the time to ensure they have a good foundation for AI support will overtake the competition. It’s a watershed moment for the B2B industry where those who recognize how to get the most value out of AI while those who refuse to alter their own internal workflows because “that’s the way it’s always been done” will see their market share diminish.

1. Accuracy and Relevance: AI models rely on historical and real-time data to make predictions and recommendations. If the data is inaccurate or inconsistent, the AI outputs become unreliable, directly impacting decision-making and customer experiences.
2. Scalability and Growth: In an era where B2B companies are scaling rapidly to meet global demands, clean data ensures that AI systems can grow alongside the business. Bad data governance introduces bottlenecks, stifling the scalability of AI-driven solutions.
3. Customer Experience: AI-powered personalized recommendations, accurate delivery timelines, and responsive customer service are critical to building customer trust and loyalty. These benefits rely on clean, well-governed data. A single misstep, like recommending the wrong product or misquoting delivery times, can damage a company’s reputation.
4. AI Amplifies Data Issues: Unlike traditional systems, AI doesn’t just process data—it learns from it. Bad data doesn’t just result in poor outputs; it trains AI systems to make flawed assumptions over time, compounding errors and reducing the ROI of AI investments.
5. Competitive Advantage: Clean data governance can be a differentiator in a competitive B2B market. Companies with well-maintained data are better positioned to leverage AI for faster decision-making, improved customer service, and operational efficiencies, giving them a significant edge.

Ignoring data governance in the AI era isn’t just a missed opportunity—it’s a liability. Poor data practices lead to inefficient AI models, frustrated customers, and, ultimately, lost revenue. Moreover, as competitors invest in clean data and AI, companies with bad data governance risk falling irreparably behind.

Clean data governance is no longer optional; it’s a strategic imperative in the AI-driven B2B ecommerce landscape. By prioritizing data accuracy and consistency, companies can unlock AI’s full potential and position themselves for long-term success.

How B2B Companies Can Address Bad Data Governance

Tackling bad data governance is no small feat, but it’s a journey worth undertaking for B2B companies striving to unlock AI’s full potential. The solution involves strategic planning, technological investment, and cultural change. Here are actionable steps businesses can take to clean up their data and ensure it stays that way:

1. Conduct a Comprehensive Data Audit
2. Standardize the Data Entry Process
3. Implement Master Data Management (MDM)
4. Leverage Technology for Data Cleaning and Enrichment
5. Break Down Silos with Integration
6. Foster a Culture of Data Ownership
7. Commit to Continuous Improvement

The first step is conducting a thorough data audit—think of it as a spring cleaning for your databases. By identifying gaps, redundancies, and inaccuracies, businesses can reveal the full extent of their data issues. This process isn’t just about finding errors; it’s about creating a baseline understanding of the company’s data health. Regular audits prevent these issues from snowballing into more significant, costly problems.

Once the audit is complete, it’s time to set some ground rules. Standardizing data entry processes is critical for ensuring consistency. Clear guidelines for formatting SKUs, recording customer details, and storing supplier information can prevent the chaos of mismatched or incomplete records. Employees should be trained on these standards, and tools like automated forms or validation rules can make compliance seamless.

Of course, even the best data entry standards won’t help if different systems across the organization aren’t communicating. That’s where Master Data Management (MDM) comes in. By centralizing data into a single source of truth, companies ensure that updates in one system are automatically reflected across all others. With MDM in place, teams can work confidently, knowing that their data is accurate and consistent.

But standardizing and centralizing aren’t enough if you’re already sitting on a mountain of messy data. Performing this step by hand is significantly time-intensive. Enter data cleaning and enrichment tools. AI-powered solutions can quickly identify and correct errors, deduplicate records and fill in missing fields. These tools don’t just clean up the past; they automate routine processes to keep data clean moving forward.

For many B2B companies, fragmentation is one of the biggest hurdles to clean data. Silos between ERP systems, CRM platforms, and ecommerce tools create inconsistencies that ripple across the business. Breaking down these silos through system integration ensures a unified flow of data, improving collaboration and decision-making across departments. This requires a thoughtful integration strategy, often with the help of IT experts, but the payoff is well worth the effort.

Clean data isn’t just a technical problem—it’s a cultural one. Companies must foster a culture of data ownership, where employees understand the importance of the data they handle and feel accountable for its accuracy. Assigning clear responsibilities, such as appointing a Chief Data Officer (CDO) or similar role, can ensure that data governance remains a priority.

Finally, data governance isn’t a one-and-done project. Continuous improvement is essential. Regular review of data policies and feedback from team members help refine processes over time. Establishing KPIs for data quality can also provide measurable insights into the success of these efforts.

By taking these steps, B2B companies can move from reactive problem-solving to proactive data management. Clean, well-governed data isn’t just the backbone of AI success—it’s a strategic asset that drives better decisions, smoother operations, and stronger customer relationships. In an increasingly data-driven world, those who master their data will lead the way.

Conclusion: Turn Your Data into a Competitive Advantage in the AI Era

In the rapidly evolving landscape of B2B ecommerce, integrating AI technologies offers unprecedented opportunities for growth and efficiency. However, as we’ve explored, the effectiveness of AI is intrinsically linked to the quality of the underlying data. Companies risk undermining their AI initiatives without robust data governance, leading to inaccurate insights and missed opportunities.

Perficient stands at the forefront of addressing these challenges. With extensive experience in implementing comprehensive data governance frameworks, we empower B2B organizations to harness the full potential of their data. Our expertise encompasses:

• Product Information Management (PIM): We assist in managing all aspects of your product data—from SKUs and descriptions to stock levels and pricing—ensuring consistency and accuracy across all platforms.
• Digital Asset Management (DAM): Our solutions help organize and distribute digital assets related to your products, such as photos and videos, enhancing the efficiency of your operations.
• Data Integration and Standardization: We streamline your data processes, breaking down silos and ensuring seamless communication between systems, which is crucial for effective AI implementation.

Investing in clean data governance is not just a technical necessity but a strategic imperative. With Perficient’s expertise, you can transform your data into a powerful asset, driving informed decision-making and sustainable growth in the AI era.

A strong and successful search engine optimization (SEO) strategy is essential in the extremely competitive world of e-commerce today. You can increase the visibility, draw in more visitors, and raise conversion rates with the correct tools and strategies. Product information management (PIM) is a crucial tool for accomplishing these objectives.

What is PIM?

PIM provides a central repository for product information, ensuring that information is accurate, consistent, and up-to-date. This allows businesses to streamline the management of product data, such as descriptions, images, specifications, and other key information related to their products. Having this organized and easily accessible information can be extremely beneficial to businesses looking to improve their customer service, increase sales, and ultimately enhance their SEO performance.

By using PIM, businesses can save time and resources by reducing manual work, increasing accuracy, and eliminating redundant data entry. A PIM system can also help with managing different versions of product descriptions, images, and other data fields in different languages and currencies. This allows businesses to quickly launch products into new markets and keep them updated across multiple channels.

How can PIM help improve your SEO?

Product Information Management (PIM) systems are designed to help businesses store, manage, and distribute product information in an efficient and organized manner. It has become a popular tool for businesses looking to improve their SEO rankings.

PIM can help improve your SEO rankings in several ways:

1. High-quality Content: PIM can help ensure that product information is accurate, complete, and consistent, which can lead to better on-page optimization and search engine visibility.
2. Enhanced Product Descriptions: PIM enables the creation of detailed and optimized product descriptions, which can help improve the relevance and quality of content for search engines.
3. Better Keyword Targeting: PIM can provide insights into which keywords are most relevant for each product, enabling e-commerce websites to better target those keywords in their product pages and other content.
4. Improved Taxonomy: Taxonomy helps to improve the customer experience by making it easier for customers to find what they are looking for, and to compare products based on relevant attributes. In addition, a well-structured taxonomy can also help to improve search engine optimization (SEO) by increasing the relevance of search results, which can drive more traffic to a company’s website.
5. Cross-Channel Distribution – PIM systems also make it easy to distribute your product information across multiple channels. This helps increase the visibility of your product pages and will help improve your SEO rankings.
6. Faster and More Efficient SEO Updates – PIM can also help make SEO updates faster and more efficient. With PIM, you can quickly and easily make changes to your product information, which can then be automatically updated across all of your sales channels. This saves time and reduces the risk of errors, making it easier to optimize your product pages for search engines. With PIM, you can keep your website up-to-date with the latest product information and take advantage of new SEO opportunities as they arise.
7. Asset Management – Asset management in a Product Information Management (PIM) system refers to the process of organizing and managing digital assets, such as images, videos, and other multimedia files, associated with a product. This includes storing, categorizing, and versioning these assets to ensure that they are easily accessible and up-to-date. We can also attach metadata to digital assets to help improve the search.

This can lead to improved organic search traffic and more conversions for your business but business always questions how do I know the optimization we were doing in PIM is helping us, One way to identify is utilizing Digital Self analytics.

inriver’s digital self-analytics tool, Evaluate, significantly enhances SEO optimization in several ways:

1. Content Compliance: Evaluate ensures that your product information is accurate and consistent across all channels, which is crucial for SEO. Accurate data helps search engines understand your products better, improving visibility.
2. Keyword Optimization: The tool tracks keyword performance and helps you optimize product listings for better search rankings. This includes monitoring keyword search and share-of-shelf.
3. Real-Time Insights: Evaluate provides real-time insights into how your products are performing on the digital shelf. This includes monitoring product search rankings, competitor pricing, and stock levels, allowing you to make data-driven decisions to improve SEO.
4. Engagement Intelligence: By analyzing customer interactions and engagement with your product listings, Evaluate helps you understand what works and what doesn’t. This information is vital for refining your SEO strategy to attract more traffic and improve conversions.
5. Automated Monitoring: The tool uses smart automation to constantly monitor your products, providing actionable insights that help you stay ahead of the competition and ensure your product information is always optimized for search engines.

Using inriver Evaluate, you can take control of your digital shelf, drive revenue growth, and enhance your SEO efforts with precise, actionable data.

By following these recommendations, you can make sure that you get the most out of your PIM system and improve your SEO performance. PIM can help you stay ahead of the competition in the e-commerce space. So if you’re looking to improve your SEO performance and reach more customers, it’s time to invest in PIM. For more information on this, contact our experts today.

For organizations to remain competitive in today’s fast-paced digital environment, product information management (PIM) needs to be precise and effective. inriver latest innovation, the Expression Engine, aims to transform how consumers manage and manipulate product data. It allows users to configure rules that automatically apply to product data, similar to using formulas in a spreadsheet. If you’re an inriver PIM user and haven’t yet enabled this powerful feature, here’s what you’re missing out on:

1. Enhanced Data Transformation Capabilities

The Expression Engine allows users to configure enrichment rules, enabling the automation of complex calculations, data string generation, and logical rule application. This significantly reduces manual effort and boosts efficiency. For example, you can create SEO friendly description by concatenating key attributes. This automation significantly reduces the time and effort required to prepare data for various channels.

2. Improved Speed to Market

By automating data transformations, the Expression Engine helps businesses accelerate their time to market. As product information is processed and updated automatically, you can quickly adapt to new market demands and ensure that your product data is always current and accurate. This is particularly beneficial for companies managing large product catalogs across multiple channels.

3. Increased Data Quality and Visibility

The dynamic functionality of the Expression Engine guarantees that any updates to your PIM data are instantly mirrored across all connected fields. This minimizes the likelihood of human error and helps maintain consistent and dependable data. Furthermore, users can view the formulas used in each field, enhancing transparency and simplifying the process of troubleshooting any issues.

4. Cost and Resource Efficiency

Traditionally, businesses often turned to custom code or manual processes to manage complex data transformations. However, the Expression Engine streamlines this process by eliminating the need for these costly and time-consuming methods. With its intuitive interface for configuring expressions, businesses can reduce their reliance on IT support, resulting in lower costs and a more efficient way to maintain their PIM systems.

5. Seamless Integration and Extensibility

The Expression Engine utilizes familiar tools and interfaces, like Microsoft IntelliSense for code completion and color coding, making it simple for users to create and manage expressions. This smooth integration allows you to fully leverage the PIM’s features without requiring advanced technical expertise.

6. Future-Proofing Your PIM Strategy

The Expression Engine’s adaptable and scalable architecture ensures that your PIM system can evolve alongside your business needs. By enabling this feature, you’re investing in a future-proof solution that will keep providing value as your product information requirements evolve.

Achieving PIM Efficiency with Expression Engine

A few example use cases of Expression Engine in PIM –

• Retail: In the retail industry, the Expression Engine can automatically calculate and populate fields like product attributes (e.g., size, color, and material) based on predefined rules. For example, if a retailer defines a rule that certain product types should always include specific care instructions or packaging details, the Expression Engine can automate the inclusion of these values, ensuring consistency across all product listings.
• Manufacturing: For manufacturers using PIM, the Expression Engine can generate and manage product codes and specifications dynamically, based on product attributes such as part numbers, materials, or dimensions. This ensures that each product is accurately categorized and described without needing to manually update multiple fields for every new product variation, reducing errors and enhancing efficiency.
• E-commerce: In the e-commerce sector, the Expression Engine can help create SEO-optimized product descriptions by automatically combining product attributes such as category, key features, size, and material. This automated approach ensures that every product page is consistent, relevant, and keyword-rich without requiring manual entry, thereby saving time and improving search engine visibility.

Conclusion

Activating the Expression Engine in your inriver PIM system offers numerous benefits that can greatly improve your product information management. You’ll see enhancements in data quality, quicker time to market, cost savings, and increased efficiency. Don’t miss the chance to optimize your PIM strategy—enable the Expression Engine today and witness the positive impact on your business.

If you’re ready to get started, contact us to discover how we can assist you on your PIM implementation journey and learn more about how enabling the Expression Engine can streamline your enrichment process.

In today’s digital landscape, efficiently managing product information is vital for businesses to enhance customer satisfaction and drive sales growth. A robust Product Information Management (PIM) system with excellent integration features, like inriver, will streamline your PIM strategy. By utilizing the integration frameworks and APIs provided by inriver, businesses can ensure relevant, accurate, and consistent product information across all channels. This article explores key inriver integration techniques that have the potential to transform your PIM approach.

The importance of PIM Integration –

Automating PIM processes leads to significant improvements in efficiency, accuracy, and scalability. By eliminating manual data entry, automated integration reduces errors and ensures that information remains consistent and current across all systems. This not only saves time and cuts labor costs but also enhances business agility and customer satisfaction. With automated integration, companies can swiftly adapt to market changes, make informed decisions, and provide timely, personalized information to their customers.

Exploring inriver Integration Options –

There are several ways to automate the integration between systems that are used to send or receive data –

Leveraging APIs (application programming interface)-

• inriver REST APIs – These can be utilized to build integrations in any programming language and customize interfaces within inriver, including creating enriched PDF/Preview templates.
• inriver Remoting APIs – These require C# programming knowledge and are used with hosted solutions. The Remoting API services consist of six major components:
  • Channel Service – Methods related to channels. e.g. Channel Structure, Publish/Unpublish a channel, Retrieve entities and links from a channel etc.
  • Data Service – One of the most widely used Service for creating, updating, deleting and finding entities and links in the system.
  • Model Service – Contains methods for building and maintaining PIM data model.
  • Print Service – Used for developing the inriver print plugin.
  • User Service – Provide methods for maintaining uses, role, permissions and restrictions.
  • Utility Service – Contains various method including Connector states, HTML Templates, Languages, and Notifications.

Remoting Services

• Content API  – A set of APIs designed to facilitate the onboarding and distribution of large volume of product data.
  • Content Onboarding API – help standardize the data onboarding process by dividing them into five key steps – Landing Area, Field Mapping, Staging area, PIM validations and Import.
  • Content Delivery API – used for distribution of product data to various channels and platforms, ensures that product data is uniform across all channels.

Integration Framework (IIF) – The Integration Framework is a foundation for building adapters and outbound integrations in inriver. It transforms customer’s unique data model into a standard integration model. It supports custom entity types, delta functionality and provide standard functions to deliver product data.

High level integration framework flow

The following table highlights the key aspects when considering integration within inriver –

These integration techniques can significantly enhance your PIM strategy, ensuring your product data remains accurate, consistent, and up to date across all channels. At Perficient, we engage in comprehensive discussions throughout our elaboration process and continue to validate during implementation phase. We help finalize best practices tailored to each customer’s unique needs, recognizing that one approach may work better for one client than another. Get in touch to explore how we can support you on your PIM implementation journey, whether you’re starting fresh or facing challenges with an existing system.

Digital shelf development is supported by Product Information Management (PIM) systems .  And they are evolving to meet the growing demands for efficient and effective online content generation across channels. Integrating Generative AI into your digital shelf is a significant advancement. This innovation transforms how retailers can transform the customer’s online experience, including subsequent reviews, ratings, and shopping behavior, with product descriptions and related content on PDPs. Let’s delve into how generative AI is reshaping PIM and your digital shelf across channels with a closer look at the offerings from leading platforms. One is designed for high customization and another designed for rapid streamlining of your enrichment and review process through configuration. 

The Benefits of Generative AI for Your Digital Shelf 

Faster Updates to the Digital Shelf

Creating digital content manually can be time-consuming. Generative AI saves publishers valuable time by automating the creation process. This allows retailers to focus on other critical tasks and content, improving overall productivity.  Consider a case where you need to quickly fix issues with a customer’s ability to search your products or review them on PDPs; you’ll have high velocity on those product changes.  That’s important because it impact customer reviews and ratings which will influence online shopper behavior for months and years to come.

Creative Springboard for Publishers

Generative AI provides a fresh perspective on digital information, offering descriptions and insights that publishers might not have considered to improve the online experience. This can serve as a creative springboard, enhancing the overall quality and appeal of your digital shelf. 

Enhanced Digital Shelf Accuracy

Generative AI is less likely to have grammar or spelling issues, ensuring high-quality, error-free product descriptions on your digital shelf. This enhances professionalism and reliability. Many website search engines and customer ratings and reviews can be sensitive to issues here. 

Expanded Publisher Pool

With generative AI, the pool of potential publishers expands beyond those with exceptional marketing writing skills. Some excel in product knowledge, data quality, search, customer experience, channels marketing, and efficient enrichment workflows, thus democratizing enrichment. 

 Multilingual Capabilities

Generative AI can translate into multiple languages, reducing the effort required to expand a retailer’s PDPs reach into new online markets. This opens up more channels and customers who search online for products in your digital shelf with minimal additional workload. 

Digital Shelf Stewardship

Generative AI is robust and efficient, but retailers can still have the final reviews, allowing a human touch where appropriate. They can review how a customer would search for that product and create a final revision. 

Generative AI Platform Features for Your Digital Shelf

 Highly Customizable PIM

 We provide strategic implementations on a platform that specializes in extensive customization (customizable PIM). To learn more about this specific platform please reach out to us.  It’s generative AI feature introduces several capabilities to manage your digital shelf and improve the presentation on PDPs and category landing pages: 

Content Generation Tab: This tab is available on any data element (products, categories, etc) page, including custom-created record types, allowing for versatile application across various entities. For example, it could be used for a category description as well as for products. This will enable you to apply generative AI to more facets of your digital shelf. 

Tone Selection: Retailers can tailor the tone for the generative AI to match the brand’s voice to the customer on PDPs. 

AI Engine Selection: It currently offers two generative AI engines and gives them the flexibility to integrate additional generative AI platforms in the future. 

Digital Shelf Relevance: It generates based on existing product content, ensuring relevance and accuracy on your digital shelf. 

Custom Terms: Users can include specific terms for the generative AI engine, enhancing the results in a targeted way. This improves the specificity of your digital shelf improving the relevance to the customer.

Batch Generation: Users can create work areas for products, apply generative AI to those products, and then review them systematically before approval. 

Choices: You can control how many versions of the descriptions you want.  It will create many variations to choose for PDPs. 

Images as Input: You can ask it to look at an image and generate a product description. 

Configurable PIM

 We also provide strategic implementations on a platform that is designed to be a turnkey solution where it’s functionality is driven by adjusting natively available settings (configurable PIM). To learn more about this specific platform please reach out to us. The configurable PIM also brings a robust set of features for managing your digital shelf: 

AI-Generated Attributes: Users can define specific product data attributes to be generated by AI. A new tab for attributes, “Generative AI,” is available to configure this feature. 

Verbosity Levels: The platform allows users to select verbosity levels for descriptions, providing control over detail and length to show on PDPs. 

Mass Digital Shelf Updates: It supports rules that apply en masse to all products, streamlining large-scale generative AI. The impact is compounded by the PIM’s ability to push updates out across channels automatically.

Extensive Product Library: Trained on a library of 50 million products, It can generate content even with minimal initial data, such as a manufacturer number. Of course, a robust digital shelf needs products with much more than minimal information to create engaging PDPs.

Suppliers Can Use It: If you use the supplier portal feature, your suppliers can use the generative AI to enrich their product content and empower them to contribute effectively to your digital shelf. 

Control Over AI Instructions: Since it responds to instructions (prompts), it allows you to select from a list of prompt templates to request a short description that is SEO-friendly or even targeted for Amazon if that’s one of your online marketing channels. You are creating an adaptive digital shelf. 

Comparative Analysis 

Both platforms have powerful support for marketing rich content across channels. When comparing the customizable PIM and configurable PIM for your digital shelf, several key differences and similarities emerge: 

Data Utilization: Both platforms build on your existing product data, but the configurable PIM also uses extensive product training data to enrich product content. 

Entity Support: The customizable PIM supports AI generation for any entity type, whereas configurable PIM is limited to product information. Some retailers have a high volume of categories on their digital shelf, which could be crucial. 

Shelf Optimization: Both support applying rules to products en masse, which can be more efficient for a digital shelf with many products. 

Feature Scope: The configurable allows your suppliers to leverage its generative AI using the supplier portal. 

Image Input: The configurable PIM can leverage your existing assets to help create descriptions. 

Client Use Case: Real-World Application 

Consider a client that pulls product content from multiple sources to create comprehensive product descriptions. Their customers search shortened descriptions from the ERP, leading to search issues (e.g., “BLK” for “Black”). This client faces challenges balancing the ERP with other sources to create robust descriptions. Generative AI content could be part of the solution here. It can merge ERP descriptions with other product data to be complete and accurate, seamlessly incorporating terms like “BLK” and “Black.” 

In cases like this, AI content generation could reduce the infrastructure and development costs of pulling and merging from multiple sources. It can also significantly reduce the time to market for your product content in all of your channels. 

Conclusion 

Integrating generative AI into PIM systems represents a significant leap forward in product enrichment. By leveraging AI, businesses can save time, enhance creativity, ensure accuracy, improve customer search, and expand their reach into new markets. Platforms like these lead the way, offering unique features to meet diverse business needs. As AI technology continues to evolve, the potential for innovative applications in PIM will only grow, driving efficiency and effectiveness in product information management.   

It is vital to ensure that humans review the content created since they apply experience from search. It’s also essential to include as much product information as possible as part of the source for AI. AI generation will create compelling product descriptions but cannot add attributes, specifications, or images.  

If you don’t have a PIM yet, I don’t recommend using generative AI as a specific selection criterion. Instead, the foundations of a PIM and how it meets your needs regarding data governance, source of truth, quality of product content, syndicating across channels, measuring success, and integrability are paramount. There are commonly understood best practices you probably need to adopt before diving deeper into these features. 

You may need professional consulting to ensure your move solves the right problem. We have subject matter expertise in PIM strategy, solution architecture, best practices, and feature guidance, as well as the deep technical experience to make your vision a reality.  Contact our experts today for other inquiries and information.

Imagine running a business where you offer subscription-based products. As your customer base grows, you begin to notice something slipping—renewal deadlines, contract complexities, and your sales team being bogged down with manual updates. Enter Salesforce CPQ (Configure, Price, Quote), a powerful tool designed to help businesses streamline the often-complex process of managing quotes, pricing, and contracts. But that’s not all—Salesforce CPQ’s renewal and amend functionalities are here to make your contract management process seamless and automatic.

Let’s dive into how CPQ works, how it simplifies renewals and amendments, and why it’s a game-changer for any business using subscription models.

What is Salesforce CPQ?

At its core, Salesforce CPQ helps businesses configure their products, set pricing, and generate quotes quickly and accurately. Whether your product comes in different sizes, packages, or configurations, CPQ automates the process of calculating pricing based on your business rules, ensuring everything stays consistent. It also handles complex contracts, helping your sales team focus on selling rather than getting lost in the weeds of paperwork.

Now, imagine adding automation to this process, especially when it comes to renewing contracts or amending existing ones. This is where CPQ truly shines, offering standard functionality that reduces the workload while improving accuracy and customer satisfaction.

The Challenge of Renewals

Picture this: It’s the start of the week, and your inbox is overflowing with reminders—expiring contracts, upcoming renewals, and customer requests for service changes. Each contract has unique pricing, terms, and configurations. Manually tracking them is time-consuming and prone to human error. Missing a renewal date could lead to a loss of revenue or, worse, a dissatisfied customer.

Managing renewals manually can be overwhelming. But with Salesforce CPQ’s renewal functionality, this process is automated. Contracts are renewed at the right time, with minimal intervention from your team. No more worrying about missed deadlines or scrambling to send out renewal quotes. The system handles it for you, transforming what was once a cumbersome task into a smooth, efficient process.

How Renewal Functionality Works

Let’s say you have a loyal customer, Sara, whose subscription is nearing its end. In the past, you might have had to manually track her contract, reconfigure the terms, and send her a quote. But now, thanks to Salesforce CPQ’s renewal feature, the system automatically generates a renewal quote in advance, accounting for any updated pricing or discounts.

Your sales team receives a notification and can review the quote before sending it out. Sara, impressed with the efficiency, signs off on the renewal without delay. The entire process is handled smoothly, saving your team hours of manual work and ensuring customer satisfaction. Renewals become a way to strengthen your customer relationships, all while keeping your operations running efficiently.

Tackling Contract Amendments with Ease

But what happens when a customer wants to make changes mid-contract? Perhaps Sara reaches out midway through the year, wanting to upgrade her service package. In the past, you’d have to manually adjust the contract, update pricing, and notify the billing team. The whole process was time-consuming and left room for mistakes.

That’s where Salesforce CPQ’s amend functionality comes into play. Instead of starting from scratch, the system pulls up the existing contract, applies the requested changes, and automatically updates the quote. Whether Sara wants to add more users to her service or change the scope of her subscription, the amend functionality ensures everything is handled efficiently.

The amend feature also updates billing automatically, preventing errors that could arise from manual adjustments. Your team saves time, reduces the risk of miscommunication, and ensures that your customer is getting exactly what they need—without the hassle.

Automation Transforms Business Operations

Let’s face it—managing contracts manually is inefficient. Every contract expiration requires revisiting the original terms, configuring renewal details, and generating quotes. The more complex the contract, the higher the chances of errors. Handling amendments mid-term also introduces challenges, often leading to confusion or customer dissatisfaction.

But with Salesforce CPQ’s automated renewal and amend functionalities, the pressure is off. These features allow you to focus on what matters most: growing your business and building relationships with your customers. Automation increases accuracy, reduces manual effort, and ensures no details slip through the cracks.

Conclusion: A New Era of Contract Management

If your business is still managing renewals and amendments manually, now is the time to embrace the future with Salesforce CPQ. By automating these critical processes, you not only save time but also improve customer experience and protect your revenue streams.

Think about Sara—her smooth, seamless contract renewal and service upgrade are just one example of how CPQ’s renewal and amend features make a real difference. Your team can now focus on closing new deals, knowing that contract management is handled automatically.

Say goodbye to manual management and welcome the efficiency of Salesforce CPQ. It’s time to streamline your operations and let automation pave the way to a more successful, customer-focused future.

If you are part of an organization that utilizes an Enterprise Resourcing Planning (ERP) system, then you probably already know the many reasons why it serves as such an essential component for your business. There are more ERP platform options today than ever before, and each system has its own collection of features and capabilities. Generally speaking, they are the work horses for managing and streamlining day-to-day business operations. This typically includes activities such as managing procurement processes, financing, supply chain and logistics, administrative services, among many other critical business orientated functions. However, when it comes specifically to the management of your product data, it’s likely your ERP is lacking in some key capabilities and not providing you with everything your organization really needs.

Sure, your ERP most likely stores some general product information like a unique Identifier, or some sort of SKU. Perhaps it even stores dimensions, pricing, or some barely discernable internal description for your products. These are all valid product data points and would typically be managed in your ERP, but have you considered all the other data that is associated with your product catalog that your ERP does not manage? Data such as product variants and colors, product attributes, long and short customer friendly marketing descriptions, SEO and search friendly content, compliance information, various product relationships, product images and assets, not to mention your customer facing taxonomy structures.

By offering only the basic product attributes from your ERP, you are severely limiting the information your customers have to make an educated and informed buying decision. This ultimately reduces the effectiveness of the overall experience they have while interacting with the products you sell and how they engage with your brand. In todays’ environment customers are increasingly looking for more and more information and want to be confident and educated before purchasing a product. They want an experience that is meaningful, accurate and trustworthy. A well thought out and deliberate product data strategy can be a true differenciator in that regard.

PIM (Product Information Management) systems are built specifically to help you achieve exceptional customer product experiences and enable you to manage many facets of your customers’ product data journey.  Unlike an ERP, a PIM can and should serve as the one true source of product data within your organization that can be easily accessible to multiple groups within your organization. This allows for collaboration with consistency, accuracy and governance established through defined user roles and workflows.  No more managing data in scattered spreadsheets or in separate systems or in areas where only your IT team should roam.

A quality PIM solution (like the ones offered by Perficient’s PIM vendor partners) come loaded with built in features and functionalities which address key components that help solve organizational product data challenges. Some such features include bulk product data loads and updates, vendor data onboarding and management, the ability to easily and efficiently restructure data for specific outbound channels (ie. Syndication), digital shelf analytics and of course the ability to enrich data collaboratively across multiple groups without the need to worry about overwrites or repeated processes. A PIM system is also ideal for managing the localization of your data and for managing translated product data.

In summary, while an ERP is a key component to your technology stack and plays a vital role within your organization it is typically used to handle the big picture organizational functions, whereas a PIM exists to specialize specifically in the product data journey and management of processes related to your product content. Both can be complimentary to each other and when used in tandem can produce optimal results and great customer experiences.

Perficient’s dedicated PIM practice has well over a decade of experience implementing complex enterprise PIM solutions with experience in industries such as Manufacturing, Warehouse and Distribution, Automotive, Home Goods, Retail & CPG, Healthcare, Outdoor Landscape & Equipment and many more. With our extensive expertise in leading technologies and our ability to offer tailored engagement options, Perficient is an excellent partner choice for helping achieve your digital objectives. If you have questions or if you want to learn more about how PIM can be an asset to your organization, please reach out to our team of friendly experts.