Enterprise Search Platforms: Moving Past the Basics for B2B

Editor’s Note: Following our recent webinar with Dell Technologies on transforming enterprise search, we received numerous questions about implementing modern search solutions. Frazer LaChance, our Digital Experience Strategist, expands on the key insights and provides a comprehensive guide for organizations looking to evolve their enterprise search capabilities.

What we’re seeing right now is a real disconnect between what users expect from an enterprise search platform and what they’re actually getting. I spend a lot of time helping organizations improve their search experience, and it’s fascinating – they have more data than ever, but they’re sort of struggling to make it useful. 

The Search Experience Gap 

Working in search and discovery, I notice that most B2B search software hasn’t really evolved much in the last couple of decades. I’m seeing this constantly with manufacturers and distributors – their customers are used to these really intuitive experiences in their personal lives, but when they come to work, it’s almost like going back in time. 

Let me give you an example: I was working with a manufacturing client whose engineers were exploring their site to determine if they had products that fit their needs and could support their projects. Even with modern technology in place, these highly skilled professionals were spending 15-20 minutes just trying to track down basic product information to inform their decisions—that’s the kind of friction that sort of pushes people to look elsewhere. 

Real-World Success: Insights from Dell’s Search Transformation 

I recently discussed this challenge with Tom McElroy, Senior Director of Global Search at Dell Technologies, during our webinar on transforming enterprise search. Dell’s experience is telling: after implementing a unified search strategy, they saw conversion rates triple for customers using their AI-powered product advisor compared to traditional search. 

“At Dell, we created an AI product advisor that’s delivering triple the level of conversion compared to customers who don’t use it,” explains McElroy. “And the conversion is even higher than traditional search.” 

Watch the full webinar with Dell and Lucidworks. 

The Realities of AI-Powered Product Discovery for B2B 

When working with clients on enterprise search platform implementations, two big challenges come up again and again. 

1. The Data Bottleneck – A lot of organizations feel like they can’t move forward until their data is perfect. I had a client who spent nearly a year and a half just cleaning up data while their customers kept struggling with basic search problems—and revenue slipped through the cracks. But here’s the thing: waiting for perfect data just isn’t realistic. The best approach is to work with what you have, improve search experiences now, and refine the data as you go.
2. The Ripple Effect Across the Organization – Bad search doesn’t just frustrate customers; it creates a chain reaction across the business: 

• Support teams get flooded with basic questions that should be handled by self-service. 

• Engineers waste valuable time trying to work around system limitations instead of focusing on actual problem-solving. 

• Sales teams miss out on opportunities because products and supporting content aren’t surfacing when they should. 

Why Traditional Search Falls Short 

So why does this keep happening? It comes down to the limitations of traditional search: 

• Lagging Real-Time Updates – Inventory and pricing change constantly, but search indexes can be hours or even days behind. I recently worked with a client whose customers were finding products that had been out of stock for days—not exactly a confidence booster. 

• Rigid, One-Size-Fits-All Systems – Most traditional search platforms are black boxes—you can’t tweak them to fit your business. But in B2B, every company has unique needs. Buyers don’t always search the way a rigid system expects them to, which means they’re often missing out on the very products they came to find.
  

The good news? AI-powered search solutions are changing the game, making it easier for customers to find what they need while reducing friction across the business. And when search actually works, everyone wins—customers, support teams, engineers, and sales. 

Neural Hybrid Search Technology: A Different Approach 

What’s interesting about neural hybrid search technology is how it changes the game. Let me give you an example of what this looks like in practice: imagine an engineer searching your enterprise search platform for ‘high-temp materials.’ A traditional search might return a basic list of materials that can withstand heat—useful, but not necessarily insightful. But a smarter system using Neural Hybrid Search could recognize patterns in their previous searches—maybe they’ve also looked up ‘electric car parts’—and infer that they’re actually looking for high-temp materials specifically for EV battery applications. Instead of just listing materials, the system could surface tailored recommendations, design insights, problem-solving guides, and supplier options relevant to that context. 

The Unified Experience Equation 

At Lucidworks, we’ve been working on what we call the Unified Experience Equation—it’s based on what we’re seeing work with a wide variety of enterprises we work with. Let me break down the key pieces we’re finding make the biggest difference: 

1. Really Understanding Your Users 

It’s not just about basic journey mapping. With modern search, you need to understand that an engineer searching for technical specs at 3 AM needs a completely different experience than a procurement manager building a bulk order during business hours. 

2. Working With Your Data 

Instead of waiting for perfect data, successful organizations are starting with: 

• Validating what matters most in real-time 

• Finding smart ways to fill in the gaps 

• Keeping everything current with their business 

• Adding context that makes results relevant 

3. Constant Testing and Learning 

The most successful projects we see treat search like an ongoing product, not a one-time thing. That means: 

• Testing different approaches with real users 

• Actually looking at what’s working (and what isn’t) 

• Making adjustments based on what you learn 

• Continuing to evolve as needs change 

4. Smart Use of AI 

Look, everyone’s talking about AI, but here’s what actually matters: AI orchestration. It’s not about having one AI model do everything – it’s about knowing how to combine and coordinate (or I like the word ‘Orchestrate’) different AI capabilities for specific needs. This means: 

• Using semantic reranking for intent understanding 

• Implementing neural models that learn from your users 

• Coordinating these components to work together seamlessly 

• Making sure you can swap out and upgrade components as technology evolves 

5. Having Real Ownership 

This is something I can’t stress enough – you need a dedicated team focused on your enterprise search platform. What we’re seeing is that initiatives often struggle when nobody really owns the experience. 

Measuring What Really Matters 

When implementing new search technology, one of the things I always talk about with clients is making sure we’re measuring the right things. It’s not just about those basic metrics everyone looks at – let me break down what we’re finding actually matters: 

1. Technical Side 

You want to look at: 

• How quickly are people getting their results? 

• Is your information actually current? 

• Are your algorithms doing what they should? 

• How’s the system performing overall? 

2. User Success 

What’s interesting is that metrics need to go beyond basic click-through rates. What we’re finding really matters is: 

• How often are users getting zero results? (This should be pretty rare or never) 

• Are they finding what they need right away? 

• How often do they have to try different searches? 

• Do they actually accomplish what they came to do? 

Building Your Path Forward 

One thing I’ve learned working with enterprise search platforms is that you can’t transform everything overnight (although our new B2B Core Package gets you there in weeks, instead of months). Here’s how we typically help organizations approach this: 

1. Start With Where You Are 

You need to be honest about your starting point. I was working with a manufacturer recently who thought their search was “good enough” until we showed them that about 40% of their customers couldn’t find products they actually had in stock. 

2. Build Your Approach 

What we’re seeing is that you can’t just copy what Amazon does (nor do you have the budget to). Your solution needs to work for your specific business. Focus on: 

• Understanding what makes your customers successful 

• Finding where your current experience isn’t working 

• Identifying which improvements will make the biggest difference 

• Figuring out how you’ll measure success 

The Way Forward 

What we’re seeing in the market is that the gap between what users expect and what most organizations deliver is getting wider. The good news? The technology exists today to fix this. You don’t need perfect data or a complete rebuild – you just need a clear path forward and the right approach. 

I’ve seen organizations transform their digital experience and get really impressive results – manufacturers tripling their conversion rates, distributors cutting support tickets in half. The question isn’t whether to make these improvements – it’s how soon you can get started. 

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| Explore our B2B Core Package solutions → 

Frazer LaChance is a Digital Experience Strategist at Lucidworks, specializing in helping manufacturers and distributors optimize their search and discovery experiences. With over five years of experience in search and content discovery, he focuses on implementing hybrid operating models that drive measurable business outcomes. You can connect with Frazer on LinkedIn.