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case Study

Cutting eCommerce Drop-Off at the Address Check for a Top Canadian Telco

7 min read • August 2026

For a top Canadian telecom, customers vanished at the one step they could not skip, the service-address eligibility check, and every drop-off was a sale lost to friction.

Executive Summary

“Ask for a full address too early and customers leave. Ask for a postal code and they stay.”

Telcos must check a service address to show location-eligible plans, but for one of the largest digital service providers in Canada that step was causing a major drop in traffic. Customers were reluctant to disclose full addresses, the system could not auto-correct invalid entries, and verification latency reached up to 26 seconds because addresses in backend databases lacked standardization.

ML arteka ran problem-framing workshops, built personas, and studied best practices, discovering that journeys starting at the postal code with progressive disclosure changed user attitudes. The team mapped the journey to balance privacy and convenience, tested three concepts (Banner, Modal, and Enhanced Layout) with real users, and built a proof of concept: automatic browser location with consent, address auto-complete, postal-code-only sharing, and a microservice architecture with standardized databases to cut latency.

The result: a validated proof of concept that simplifies eligibility, protects privacy, reduces latency, and improves customer conversion.

Business Outcomes

A privacy-first, postal-code-led flow removed the friction and latency that were costing conversions.

Lower
Address-check latency

Reduced from up to 26 seconds.

Postal-code
First, privacy-friendly flow

Progressive disclosure, not full address.

Higher
eCommerce conversion

Less friction at the eligibility step.

The Transformation

From a high-drop-off address check to a validated, privacy-first flow.

  • 1
    FrameProblem-Framing WorkshopsDetermined exactly why customers dropped off at the eligibility step.
  • 2
    ResearchPersonas and Best PracticesFound that postal-code-first journeys with progressive disclosure change user attitudes.
  • 3
    MapBalance Privacy and ConvenienceMapped the journey to accommodate different personas and their tradeoffs.
  • 4
    ValidateConcepts and a POCTested three concepts with real users and proved a hybrid solution with a proof of concept.

The Business Challenge

Losing Customers at a Step They Cannot Skip

A required address check was driving a major traffic drop in the browse-buy journey.

🔒

Privacy concerns

Customers were reluctant to disclose their full address at that stage.

Address-check failures

The system could not auto-correct invalid addresses, showing inaccurate results.

Slow verification

Unstandardized backend data caused latency of up to 26 seconds.

Business Outcomes in Detail

What the Numbers Mean

LowerAddress-check latency

Reduced from up to 26 seconds.

Postal-codeFirst, privacy-friendly flow

Progressive disclosure, not full address.

HighereCommerce conversion

Less friction at the eligibility step.

Technology Snapshot

The Conversion Solution

Browser Geolocation (Consent)
Auto-detects location to remove manual entry.
Address Auto-Complete
Reduces friction and input error.
Standardized Databases
Cuts search failures and latency.
Microservice Architecture
Flexible, scalable delivery of the new flow.
ML arteka Executive InsightThe fix was not more validation, it was asking for less. A postal-code-first flow with progressive disclosure respected privacy, reduced errors, and kept customers moving toward the sale.

Executive Questions and Answers

The questions leadership tends to ask when evaluating an approach like this.

Privacy
How do you reduce drop-off without demanding full addresses?

By starting with the postal code and using progressive disclosure, plus browser geolocation with consent, so customers share only what they are comfortable with.

Speed
How was the 26-second latency addressed?

By standardizing the backend databases and deploying a flexible microservice architecture, cutting the search failures and latency that slowed verification.

Proof
How was the solution validated?

Through remote testing of three concepts with real users and a proof of concept that proved the experience and technology improvements.