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Featured case study

A multi-tiered retailer saves $9.2M a year through digital adoption

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Case study

Cutting Text-Messaging Compliance Risk, Fast

How a leading automotive parts retailer protected a revenue-critical SMS program built on 170 million phone numbers.

Challenges & solutions

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Automotive Parts Retail

Why it matters

As the line between text and voice compliance narrows, large SMS programs face real and growing risk. This engagement shows that meaningful risk reduction does not require a long implementation. A retailer with one of the largest consumer databases in its category was scrubbing data on day one.

Automotive Parts Retailer Cuts Text-Messaging Compliance Risk, Fast

Automotive retail

170M

phone numbers protected

How a leading automotive parts retailer protected a revenue-critical SMS program built on 170 million phone numbers.

SMS screening at scale

protects a 170-million-number texting program

Database

2

  • 170M | Phone numbers protected | A loyalty database built over decades, much of it before modern consent capture.
  • 100M+ | Scrubbed on day one | Numbers processed the day the agreement was signed.
  • < 2 mo | First contact to signed agreement | Chosen over several providers for solution fit and support.

A Revenue-Critical SMS Program at Risk

For a decades-old automotive parts retailer, text messaging had become a core revenue engine that drove store visits and loyalty engagement. Years of loyalty-program growth had built a database of roughly 170 million phone numbers, much of it collected before modern consent-capture practices.

Some numbers had likely been reassigned to new owners, and some may never have carried documented consent to receive texts. With courts treating texts with the same scrutiny as calls, and with active litigation already tied to its SMS programs, the retailer needed its outreach data clean, current and defensible.

Why PossibleNOW

The retailer ran a competitive process across several providers. PossibleNOW worked with its marketing, marketing operations, IT, compliance and executive teams to scope a solution to its specific risk profile and technology stack.

PossibleNOW was not the lowest-cost option and was selected anyway. The deciding factors were solution fit and confidence in the support and responsiveness the team would provide.

Screening at Scale, in Two Phases

  • Reassigned Numbers Database: capacity to screen ~360 million numbers a year for numbers that have changed hands
  • DNC scrubbing: ~20 million numbers a month (~240 million a year)
  • Litigator List: flags known serial litigators before outreach
  • Phase 1, high-volume batch scrubbing so the retailer could start cleaning data immediately
  • Phase 2, API integration into the existing stack (Listrak, Twilio and an in-house rewards app) for ongoing automated scrubbing

Results

  • 100+ million phone numbers scrubbed on the day the contract was signed
  • Under two months from first contact to signed agreement
  • Reduced exposure from reassigned numbers, DNC-listed numbers and known litigators
  • A protected, revenue-critical SMS channel