Match & Clean

Intelligent Address Matching &
Location Master Data

Turn unstructured location data into a reliable, geocoded, continuously improving location master — built for logistics operators.

1 API call
Free-text in, Golden Record out
learning
Improves with every match
EU infra
EU-based processing
How a request flows
📥
InputFree-text location string via API
🔍
Parse & separateAddress isolated from operational notes
🧹
Validate & standardizeAddress corrected, completed, normalized
📍
GeocodePrecise lat/lng assigned
🔗
Match against masterExisting record or new Golden Record created
Result via webhook
Golden RecordMatch confidenceCoordinatesAliasesCleaned notes
The Challenge

Location data arrives in every shape imaginable

Logistics organizations constantly receive location information in inconsistent formats — from customers, carriers, systems, and humans.

✏️

Different spellings, same place

«Müller GmbH», «Mueller GmbH Lager», «Mueller Warehouse» — three names for one physical location, none linked.

🧩

Incomplete addresses

Missing house numbers, wrong postal codes, outdated street names — partial data that breaks geocoding and routing.

📝

Instructions mixed into address fields

"Drive around the warehouse and ring at the green door" embedded directly in the address line of the TMS.

🔢

Multiple IDs for the same site

Customer ID, ERP reference, carrier code, TMS key — all pointing to the same location with no shared truth.

👯

Duplicate records across systems

The same depot appears four times in the location master — slightly different names, coordinates, or missing fields.

📞

Manual dispatch clarification

Dispatchers resolve address ambiguities by phone — time that a clean data layer would free up entirely.

How It Works

Submit free text. Receive a Golden Record.

Match&Clean processes each submission through a structured pipeline — parsing, validating, geocoding, and matching in a single async call.

1

Parse & separate components

The input string is decomposed into address fields. Non-address content — driver instructions, gate info, contact names — is identified and separated out.

2

Validate & standardize

Address fields are corrected, standardized, and completed — normalized against postal reference data.

3

Geocode

Precise latitude/longitude coordinates are assigned to the validated address.

4

Match against location master

The processed location is matched against the customer's existing database. If found, the existing reference is returned. If new, a record is created.

5

Return structured result

A structured, geocoded, enriched location record is delivered via webhook — ready for immediate operational use.

Live example
Raw input
"Müller Logistik, Hauptstr. 12 Frankfurt, drive around the back, ring at green door, ask for Klaus"
⚑ Mixed address + operational notes
Match&Clean result
nameMüller Logistik GmbH
streetHauptstraße 12
cityFrankfurt am Main
postcode60311
lat / lng50.1109 / 8.6821
matchEXISTING · 97%
location_refLB-00482
op_notes"Back entrance, green door, Klaus"
What Match&Clean Returns

A structured record ready for operations

Every result is standardized, geocoded, and enriched — usable immediately in TMS, ERP, routing, or IoT systems.

Structured address fieldsStreet, house number, postcode, city, country — all separated and normalized.
Standardized location nameCanonical name matched to the Golden Record in your location master.
Latitude / longitude coordinatesPrecise geocoding for routing, geofencing, and IoT event matching.
Match confidence & location referenceConfidence score plus the LogBook location ID — existing or newly created.
Customer-specific identifiersYour own ERP, TMS, or site IDs mapped back to the Golden Record.
Known aliases & naming historyAll previously seen names for this location across customers, carriers, and drivers.
Separated operational notesDriver instructions, gate codes, contact persons — extracted and stored separately.
Smart separation in action

Operational notes extracted automatically

Match&Clean recognizes and separates non-address content — contact persons, driver instructions, gate references, warehouse handling notes, and informal descriptions — keeping address data clean.

Input: "Drive around the warehouse and open the green door"
↓ recognized as operational context, not address data
Address: Cleaned, geocodable address
op_notes: "Green door, rear entrance"
Business Benefits

Cleaner data. Smoother operations. Better automation.

The impact of reliable location master data runs through every layer of logistics operations.

01

Better Address Quality

  • Reduced duplicates across systems
  • Cleaner, standardized master data
  • Consistent location references everywhere
  • Improved data consistency across teams
02

Operational Efficiency

  • Better route planning & consolidation
  • Reduced dispatch clarification effort
  • More accurate ETA calculations
  • Lower operational friction overall
03

Foundation for Automation

Reliable location intelligence creates the basis for the next generation of logistics automation — geofencing, IoT triggers, event-driven workflows, and AI-ready data pipelines all depend on a clean location layer.

Continuous Learning

It gets smarter with every location processed

Unlike static address validation, Match&Clean continuously expands and improves your location knowledge base — becoming more aligned with your real-world logistics network over time.

01

Improved future matching

Each processed location raises the quality of subsequent matches against the same or similar entries.

02

Better alias recognition

The system learns how the same location is described by different customers, drivers, and systems.

03

Expanded name history

Historical names, abbreviations, and informal descriptions are captured — so no match is ever missed.

04

Stronger operational context

Operational notes and site-specific knowledge accumulate over time into a living, searchable knowledge base.

Technical Integration

Simple API. Async processing. Webhook delivery.

Match&Clean is a standard REST API — minimal integration effort, maximum flexibility.

📤
Submit via POSTSend a JSON payload with a free-text location string and optional customer-specific references (ERP ID, TMS key, site identifier).
Instant acknowledgementHTTP 200 + LogBook task ID returned immediately. No blocking, no timeout risk.
⚙️
Async processingMatch&Clean processes asynchronously — parsing, validating, geocoding, and matching in the background.
🔔
Webhook deliveryStructured result delivered to your endpoint — location reference, geocoding, match details, and separated notes.
Request · POST /match-clean
// Submit a location for processing { "location_string": "Müller Logistik, Hauptstr 12 Frankfurt, green door, ask for Klaus", "customer_refs": { "erp_id": "C-00482", "tms_key": "MUELLOG-FRA" } } // Immediate response { "status": 200, "task_id": "lb-task-8f2a91c" } // Webhook delivery (async) { "task_id": "lb-task-8f2a91c", "location_ref": "LB-00482", "match_type": "EXISTING", "confidence": 0.97, "address": { ... }, "coordinates": { ... }, "op_notes": "Green door, ask for Klaus" }
ROI Example

What clean location data is worth

Illustrative calculation based on industry benchmarks — for a mid-size freight forwarder processing ~5,000 shipments per day.

Assumptions
Daily shipments processed 5,000
Address error / ambiguity rate ~3–5 %
Problematic addresses / day 150–250
Manual resolution time per case 4–8 min
Dispatcher cost (fully loaded) € 45 / hr
Misdirected shipment cost € 80–200 / case
⚠ Illustrative — based on publicly available industry benchmarks. Actual values vary by operation and can be measured precisely during onboarding.
Manual dispatch effort eliminated
€ 450–750
per day · ~1–2 FTE hours saved in dispatch
~80% reduction in manual address resolution
Misdirected & delayed shipments avoided
€ 800–2,400
per day · at 10–30 misdirected shipments avoided
conservative estimate · improves as location master matures
Annual savings potential
€ 320k – 820k
combined · 250 operating days / year
Not included: ETA accuracy gains, routing improvements, IoT enablement, and reduced duplicate master data maintenance — all of which add compounding value over time.
🧮
Calculate your individual ROI
The numbers above are illustrative. Your actual savings depend on your shipment volume, current error rates, and operational setup. We've built a dedicated ROI calculator to model your specific situation — get your personalized estimate in minutes.
Request ROI Calculator Access
Send a quick email to info@logbook.li
and we'll get you access
Typical Use Cases

Where Match&Clean makes the difference

From one-time data cleanup to continuous real-time enrichment of incoming shipment data.

Freight forwarding master data cleanup
Carrier location normalization
Dispatch & planning optimization
Customer onboarding data quality
TMS / ERP location synchronization
Automated geofencing enablement
IoT event contextualization
Consolidation of duplicate logistics sites
Multi-system location harmonization
ETA accuracy improvement
Infrastructure & Geographic Coverage
✓ EU-based infrastructure
✓ Europe — full coverage
⚠ Japan & South Korea — limited
✕ China & Russia — excluded
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