Property Search That Actually Finds What You're Looking For

It's 3:47pm on a Friday. An anxious landlord calls asking about "that property on Victoria Road—the two-bed flat, the one we talked about last week."

You type "Victoria Road" into your property system's search box.

Fifty-three results.

Victoria Road Flat 1, Victoria Road Flat 2, Victoria Road Flat 3... alphabetically sorted, meaningless order. The two-bed flat you need? Buried somewhere on page 2 or 3. You're scrolling and scrolling while the landlord waits on hold.

This is ridiculous. You know exactly which property the landlord means—the two-bed you discussed last week, the one you recently updated. Why is your software showing you 53 alphabetical results instead of the obviously relevant one?

This week, we rebuilt LetAdmin's property search to rank results intelligently by relevance. Exact reference matches appear first. Properties with search terms in headlines rank higher than mentions buried in descriptions. Recently updated properties get priority. The result: find what you need in seconds, not minutes.

The Problem: Alphabetical Sorting Doesn't Scale

When you manage 20-30 properties, alphabetical search works fine. Scroll through the list, spot your property, done.

But at 100+ properties? Alphabetical sorting becomes a time-wasting nightmare:

Problem 1: Exact Matches Get Buried

Example:

• You search for property reference "VIC123"
• Results show alphabetically: "Flat 1 Victoria Road", "Flat 2 Victoria Road", "VIC123 Victoria Terrace"
• Your exact match (VIC123) appears 40th in the list because "Flat" comes before "VIC" alphabetically

Result: Scrolling through irrelevant results to find the exact property you know exists.

Problem 2: Important Matches Ranked Same as Vague Matches

Example:

• You search "Victoria Road"
• Property A: Headline = "Two-Bed Flat, Victoria Road" (highly relevant)
• Property B: Description mentions "near Victoria Road shops" (vaguely relevant)
• Both rank equally in alphabetical sort

Result: Wading through tangentially-related properties to find the obviously relevant one.

Problem 3: Recent Work Gets Lost

Example:

• You worked on a property yesterday (updated rent, changed status)
• Today you search for it
• It's alphabetically sorted with 20 other matching properties
• You can't remember if it was "Flat 2" or "Flat 3"

Result: Clicking through multiple properties to find the one you just worked on.

Time Cost of Bad Search

Let's be honest about the cumulative time waste:

Scenario: 150-property agency, staff searching properties 15 times per day average

With alphabetical sorting:

• Average search time: 45 seconds (typing query, scrolling results, clicking through to verify correct property)
• Time per day: 11.25 minutes per staff member
• Time per year: 47 hours per staff member

With intelligent relevance ranking:

• Average search time: 12 seconds (typing query, clicking top result—usually correct)
• Time per day: 3 minutes per staff member
• Time per year: 12.5 hours per staff member

Time saved: ~35 hours per year per staff member (nearly a full work week)

For a 3-person office, that's 105 hours saved annually just from better search ranking.

How LetAdmin's Intelligent Search Works

We rebuilt property search to rank results by relevance, not alphabetical order. Multiple factors combine to produce a "smart" ranking that puts obviously relevant properties first.

Here's what changed:

Factor 1: Exact Reference Matches Always First

Property references (like "ABC123", "VIC456") are unique identifiers. If you search for a reference, you almost certainly want that exact property.

Intelligent search: Exact reference matches appear first, regardless of alphabetical position.

Example:

• Search: "VIC123"
• Result #1: VIC123 Victoria Terrace (exact match)
• Results #2-10: Other Victoria properties (partial matches, alphabetically sorted)

Benefit: No more scrolling through dozens of "Flat 1", "Flat 2" results to find your exact property.

Factor 2: Headline Matches Rank Higher Than Description Matches

Property headlines contain core identity: "Two-Bed Flat, Victoria Road, Modern Kitchen."

Property descriptions contain everything else: "Located near Victoria Road shops, 10-minute walk from Victoria Park..."

Matching the headline is far more relevant than matching buried description text.

Intelligent search: Headlines get 3x weight vs descriptions.

Example:

• Search: "Victoria Road"
• Property A: Headline = "Two-Bed Flat, Victoria Road" → High score
• Property B: Description = "Near Victoria Road shops" → Low score
• Result: Property A ranks first

Benefit: The property you're actually looking for appears at the top, not mixed with vaguely-related properties.

Factor 3: Recently Updated Properties Get Priority Boost

Human memory is recency-biased. If you worked on a property yesterday, you're more likely to search for it today than a property untouched for 6 months.

Intelligent search: Recently updated properties receive small relevance boost.

Example:

• Property A: Updated yesterday, matches your search
• Property B: Updated 3 months ago, matches your search equally
• Result: Property A ranks slightly higher (recency boost)

Benefit: Properties you recently worked on appear near the top when searching.

Factor 4: Typo Forgiveness

Nobody types perfectly, especially when rushed.

Intelligent search: Fuzzy matching catches common misspellings and abbreviations.

Examples:

• Search "Hig Street" → finds "High Street"
• Search "Vic Rd" → finds "Victoria Road"
• Search "streat" → finds "street"

Benefit: Dead-end searches eliminated—even imperfect queries find relevant results.

Real-World Example: Finding the Landlord's Property

Before intelligent search:

1. 3:47pm: Landlord calls about "Victoria Road two-bed"
2. 3:48pm: You search "Victoria Road"
3. 3:48pm: 53 alphabetical results appear
4. 3:49pm: You scroll through Flat 1, Flat 2, Flat 3... looking for two-bed
5. 3:50pm: Click Property #17, wrong one, back to list
6. 3:51pm: Click Property #23, still wrong, back to list
7. 3:52pm: Click Property #31, found it
8. 3:52pm: Resume landlord conversation (after 5-minute hold)

Total time: 5 minutes Landlord experience: Frustrated by hold time Your experience: Frustrated by inefficient search

After intelligent search:

1. 3:47pm: Landlord calls about "Victoria Road two-bed"
2. 3:48pm: You search "Victoria Road two-bed"
3. 3:48pm: 8 relevance-ranked results appear
4. 3:48pm: Top result: "Two-Bed Flat, Victoria Road" (headline exact match)
5. 3:48pm: Click top result, found it immediately
6. 3:48pm: Resume landlord conversation (15-second hold)

Total time: 15 seconds Landlord experience: Impressed by quick response Your experience: Confident search worked first time

The difference? Intelligent ranking puts obviously relevant results first instead of forcing you to hunt through alphabetical noise.

What "Smart" Search Feels Like

After deploying relevance-based search:

It feels fast: Type query, click top result, done. No scrolling, no hunting, no verifying 3 properties before finding the right one.

It feels accurate: The property you're thinking of is usually #1 or #2 in results, not buried on page 3.

It feels forgiving: Typos don't kill searches. Abbreviations work. Partial matches still find what you need.

It feels obvious: Search results make sense. "Victoria Road" headline matches rank above "near Victoria Road" description matches—exactly how you'd expect search to work.

Mostly, you stop thinking about search. It just works. Which is how software should feel.

How Agencies Use Improved Search

Beyond the obvious "find property faster," intelligent search enables better workflows:

Use Case 1: Phone Queries

• Landlord/tenant calls with partial property info
• Quick search finds correct property in seconds
• Resume conversation immediately, appear competent and responsive

Use Case 2: Multi-Property Portfolios

• Landlords with 5-10 properties
• Search landlord name, see all their properties ranked by recency
• Recently discussed properties appear first

Use Case 3: Status Tracking

• Search "High Street" to find all High Street properties
• Filter by status (Available, Let, Withdrawn)
• Recently updated properties (status changes) appear first

Use Case 4: Duplicate Detection

• Adding new property, want to check if it already exists
• Search address, exact matches appear first immediately
• Avoid accidental duplicates

Implementation: No External Services Required

Intelligent search runs entirely on LetAdmin's existing database. No external search services, no additional infrastructure, no extra costs.

Benefits:

• Fast response (no network calls to third-party services)
• Private data stays in your database (no sending property info to external search engines)
• Simple architecture (less complexity = more reliability)
• No usage limits or additional fees

For agencies managing hundreds or even thousands of properties, database search handles the load efficiently.

What We're Building Next

The intelligent search foundation enables future features:

Saved searches: Store common queries ("Available two-beds", "Victoria Road properties") for one-click access

Search filters: Combine search with advanced filters (price range, bed count, status) interactively

Search analytics: Track common searches, identify patterns, improve ranking algorithm

Autocomplete: Suggest property references as you type

The goal: Make finding properties so fast and obvious you stop thinking about search entirely.

We'd Love to Hear from You

How many properties does your agency manage? 50? 150? 500+?

How much time do you waste searching for properties in your current system? Most agents underestimate this—it's dozens of small delays daily that add up.

What would make property search easier for your agency? We're building LetAdmin based on real agency workflow needs.

Get in touch: paul@letadmin.com

LetAdmin is in active development, built by letting agents for letting agents. This intelligent property search is being used at Phillip James (370+ properties) to find properties in seconds instead of minutes. If you're interested in seeing how it works or want to join the priority list, we'd love to hear from you.