For distributors, catalog management has always been a challenge. Balancing a huge number of SKUs and data inputs from different manufacturers with varying data schemas only to then translate that information into easy-to-navigate websites for B2B buyers is no easy feat.
All the while, B2B buyers are no less demanding. Loyalty is weak. Omnichannel demands and price sensitivities are high, and distributors are in an increasingly difficult position.
So, what’s the next best step?
Turn Your Ecommerce Catalog into a Competitive Advantage
Boston Consulting Group (BCG) recommends that distributors focus on building “resilience” from what they call the “digital attackers,” or ecommerce behemoths like Amazon and Alibaba.
While ecommerce giants are investing in B2B, BCG predicts that they are likely to focus on the lower-hanging fruit: simple products that are easy to sell and require little industry-specific expertise or extensive client support.
This is where distributors can be disruptors — by leveraging their ecommerce catalog, internal expertise, purchaser data, and technology stack to create great buying experiences.
A great buying experience for distributors means ensuring your users find the right products with the right price at the right time. The impact is seen in your buyer performance indicators: lifetime value (LTV), revenue, brand reputation, and more.
To build this, your business needs clean product data, a B2B ecommerce platform, a robust search and discovery solution, and strong search filters. Fortunately, emerging technologies like modern catalog software and generative AI solutions make each of these easier for even complex businesses to achieve.
Turn Your B2B Catalog Into a Purchase Pathway with Generative AI
Distributors with large or complex catalogs can make buyers’ paths to purchase more efficient and smooth by leveraging generative AI solutions. They serve personalized, curated product recommendations and collections, which facilitate purchasing decisions and increase sitewide engagement.
Add a Shopping Assistant
B2B distributors can add an LLM-powered Shopping Assistant to their site to allow users to ask for assistance in doing a task (i.e., “I need to tile a bathroom.”).
Large language models (LLMs) ingest natural language queries to return relevant products, effectively shortening the time it takes users to go from goal to reality. So, if a user asks a question — or starts a conversation — about tiling a bathroom, the shopping assistant will determine which products categories and items to surface (i.e., tile options; caulk, grouting, and floor primer; and spacers).
Auto generate collections
Solve for the challenge of creating timely, SEO-friendly, and buyer-centric product collections with AI. Leverage the power of ecommerce-centered machine learning (ML) models and LLMs to automatically generate hyper personalized collections, rather than relying on manual tasks or tagging rules.
This automation frees up time for your ecommerce team to work on needle-moving tasks, such as strategizing how to further improve product rankings based on search trends, local events, or buyer preferences.
Optimize B2B Catalog Management and Merchandising Operations
As you’re solving for your user experiences, help your ecommerce team operate more smoothly and effectively. The following solutions powered by generative AI also allow you to further streamline catalog management operations.
Use Merchant Intelligence
Merchant Intelligence empowers B2B ecommerce teams with a more guided commerce experience. By leveraging AI-driven insights to optimize global search, browse, and slotting rules, teams can:
- Reduce operational overhead needed to analyze and understand analytics data and determine next actions.
- Conclusively determine instances of revenue loss in mere seconds.
- Prove empirically that their actions are driving positive results.
Advanced insights not only optimize teams’ time, but also allow them to drive better user experiences that improve engagement and retention in addition to business metrics that matter most.
Enrich product attributes
Your product data is a critical part of your ecommerce catalog. High-quality product data that provides accurate and detailed information about products’ features, specifications, dimensions, materials, etc. optimizes the buying experience. This lets site users search, filter, compare, and choose the right product quickly and confidently.
On the other hand, inaccurate or incomplete product data can lead to buyer dissatisfaction and increased return rates.
For distributors in particular, maintaining product data quality is extremely difficult. You’re often working with external vendors’ product data (which isn’t always accurate, complete, or normalized) in addition to extremely manual processes and an unstructured or under-utilized taxonomy. It becomes a huge resource drain for distributors to clean, correct, and manage product attributes to provide great search experiences.
AI-powered Attribute Enrichment can solve for this challenge. Attribute Enrichment uses proprietary ML algorithms and behavioral data to learn which attributes are important to users. It then enriches existing attributes and creates new ones in real-time.
This automation provides operational benefits for your business and ecommerce team:
- Remove manual tasks for attribute enrichment, categorization, and tagging.
- Provide better context for offline inventory forecasting discussions.
- Customize functionality for your business by manually overriding AI’s suggestions where it makes sense.
Attribute Enrichment also enhances the entire product discovery experience, minimizes returns and refunds, and increases conversions.
How Distributors Can Choose the Right B2B Tech Stack
When it comes to purchasing products and services online, B2B buyers report that they start their product research on whatever site they find easiest to use (33%), where they find the broadest selection (21%), and where they already make personal purchases (18%).
With a competitive market, complex inventories, and pricing demands, where should distributors focus their revenue efforts?
For distributors, building resilience from digital attackers translates to making your catalog as discoverable as possible, and then creating experiences that keep your buyers happy and returning.
AI-enhanced search is a key part of this process and an underutilized competitive choice:
"One of the most overlooked ways to increase ecommerce revenue is to enhance search functionality. You want to make sure that when [buyers] search for products, they’re truly being shown the most relevant results. This may sound like a simple and obvious goal, but it’s surprisingly hard to pull off…. For Amazon, [AI-]optimized search brings in roughly $10 billion extra dollars annually (more than 3% of their revenue).... If you’re looking to boost your ecommerce revenue, using AI to optimize search results is a great place to start."
Discover how Constructor’s product search and discovery solutions powered by advanced algorithms, transformers (the “t” in ChatGPT), and LLMs improve your organizational efficiencies while creating competitive B2B purchasing experiences that convert.