What ‘better search’ actually means (and how to get there)

To be fair, search can only work with what it’s given. If your content is clear and maintained, even a basic search implementation will feel pretty effective. If it’s not, no amount of technology is going to save you.

You see it happen all the time. A result shows up, but it’s not clear why. The right page is there, but the title doesn’t match what the user meant. Three pages compete for the same idea, and none of them feel like the right answer.

That usually gets labeled as a ranking problem. But often, it’s a content problem. Most search issues come down to a mismatch between how content is written and how people actually look for it. We name things based on internal structures that users don’t know exist. If someone searches for “scholarships” and your site calls it “financial aid,” the system isn’t “broken”; the content and the user are just speaking different languages.

Then there’s the governance side of things. Search is very good at surfacing content no one has looked at in years: expired events, outdated pages, or duplicates. That’s not a bug. That’s the system doing exactly what it was designed to do.

The interesting part is that fixing these things doesn’t just “fix search.” It improves how you perform in external search engines, how accessible your site is, and how well an AI might be able to parse your data later. It’s the same foundation.

Most search experiences look the same on the surface: a box, a list, maybe some filters. It’s easy to think of it as a single feature, but behind the scenes, I find it helpful to break it down into three separate decisions.

Indexing: This is how your content gets into the system. You can use a crawler to scan the site, which is easy but gives you less control. Or, you can “push” content from your CMS, which gives you more control but requires a lot more intentional structure.

Ranking: Every system has a logic that decides what’s relevant. Maybe titles are weighted more than body text. Maybe newer content gets a “boost.” If you haven’t made these decisions intentionally, the system is still making them for you; you just don’t have a seat at the table.

Interface: This is what the user actually sees. The snippets, the filters, the way results are grouped. You can take something off the shelf, or you can build something custom. Either way, this is where you build (or lose) user trust.

What’s useful about this framework is that it shifts the conversation. You’re not just choosing a “tool”; you’re deciding how much effort you want to put into managing your data, your logic, and your experience. Those choices don’t always line up with the highest price tag.

1. The “off-the-shelf” path (lower effort, lower control)

This path usually relies on a Crawler. The tool “reads” your site much like a user does. It’s the fastest way to get a search box on a page.

• The go-to: Google Programmable Search
• Best for: Smaller sites or organizations that need a “set it and forget it” solution and don’t require custom “boosting” of specific content. An easy way to search across multiple sites on the same domain.
• The tradeoff: You are often stuck with a “prebuilt widget” that looks like a guest on your own website.
• The strategic note: Watch out for the “trust gap.” If your tool serves ads or carries external branding, it can feel less like an authoritative resource and more like a third-party plugin.

2. The “configuration” path (the middle ground)

This is the “sweet spot” for many mid-to-large organizations. These tools offer more control over ranking and interface without requiring you to manage complex server infrastructure.

• The tools: SearchStax Studio or SwiftType
• How it works: You can often choose between a crawler or “sending” your data via an API.
• Best for: Teams where search is a primary navigation tool and needs to feel integrated, but you don’t want to hire a full-time search engineer.
• The strategic note: This is the “agility” choice. These tools provide a marketing dashboard, empowering content teams to tune results, like boosting “Giving Tuesday” to the top for a week, without needing a developer.

3. The “engineered” path (high control, high investment)

This is the “send” approach. Your CMS (like Drupal) pushes highly structured data directly into the search index via modules like Search API. This gives you total control over the experience.

• The tools: Solr or Elasticsearch
• How it works: Deeply integrated into your hosting environment (like Pantheon’s managed Solr) or a dedicated provider like SearchStax.
• Best for: Enterprise-level sites, multidomain ecosystems, or situations where search is the “core product” (e.g., a complex program finder or resource library).
• The strategic note: This offers the most power, but it requires a “search owner.” While the software is often open source (no license fee), it is the most expensive to run because it requires specialized engineering hours to maintain and tune the logic.

The right choice depends on your search maturity. Don’t buy the “engineered” solution if you don’t have the staff to steer it; don’t settle for “off-the-shelf” if your users rely on search to make high-stakes decisions.

When search underperforms, the instinct is to add more power through better tools, more features, and more controls. That’s a reasonable reaction. There’s a lot these systems can do. But what we tend to see is a familiar pattern: a more complex system running on the same content. Filters get added. The UI gets heavier. Configuration grows. The results don’t really improve.

It’s the “Lamborghini to pick up groceries” problem. Sure, the car is capable of a lot, but you’re still sitting in the same traffic, and you still have nowhere to put the bags. If the underlying content isn’t in place, more technology doesn’t fix the problem; it just makes the failures scale faster.

There are situations where a more advanced search makes sense (large datasets, multiple domains, deeper filtering), but even in those cases, the outcome still depends on the same thing: how clear and structured the content is.

If that part isn’t in place, more technology doesn’t fix the problem; it just makes it scale faster.

Improving search usually starts with getting the right people in the room. It sits at this awkward intersection of UX, content, and engineering. If those perspectives aren’t aligned, you end up with three different people trying to solve three different versions of the problem.

The way I usually approach this is to move away from “search feels off” and toward something concrete. What are the top 10 queries? What should the first result be? Are users finding things, or are they just trying again and leaving?

Once you look at search logs and identify where the language doesn’t match, the conversation changes. Instead of asking “what tool do we need,” we start asking: “What content should we exclude? How do we prioritize this department over that one? Where is search being asked to fix a gap in our main navigation?”

That’s where progress actually happens. Search will always have a subjective element, but it shouldn’t be driven by gut feel alone. Once you have a shared understanding of what the user is trying to do, and visibility into how the system is actually behaving, the technology becomes a lot less confusing.

You’re never really “done” with search. But when your content is clear, and your priorities are aligned, search starts to feel predictable. And once it’s predictable, you can stop guessing and start solving the actual problem.