BounceProtect

Clean your email lists before you send

Customer stories

Real results from real teams.

See how B2B teams use BounceProtect to reduce bounce rates, protect sender reputation, and send with confidence.

8% → 2%

Bounce rate reduction

AquiferGrowth

7% → 1%

Bounce rate reduction

Freight Right

0

Credits wasted on duplicates

Both

1 rule

Replaces manual list review

AquiferGrowth

B2B Sales & Marketing Agency

AquiferGrowth

How AquiferGrowth reduced client bounce rates and protected sender reputation across outbound campaigns.

DS

Divjot S. Mehton

CEO @ AquiferGrowth

LinkedIn →
8%2%

Bounce rateacross client campaigns

ManualAutomated

List prep timeno more spot-checking

The challenge

AquiferGrowth runs outbound lead generation campaigns for B2B clients across multiple industries. As their client roster grew, so did the volume of contact lists from data providers like Apollo and ZoomInfo. These lists varied significantly in quality — some were clean, others had been sitting in a spreadsheet for six months. The team had no reliable way to assess list quality before uploading to a sequence. They were watching bounce rates as a lagging indicator, which meant problems showed up after the damage was done.

How they use BounceProtect

AquiferGrowth now runs every client list through BounceProtect before it enters a sequence. The workflow is straightforward: export from the data provider, upload the CSV, review results by send recommendation, and pass only the Send and Send With Caution segments to the campaign tool. The send recommendation removed the need for team members to interpret scores themselves — a simple rule replaced manual judgment on every list.

The send recommendation means the VA running our list cleaning doesn't need to make judgment calls. The tool makes the call and they execute on it.

Divjot S. Mehton, CEO

Key outcomes

  • Domain typo detection catching gmial.com and yaho.com style errors silently bouncing before
  • Spam risk score used to tier high-risk domains into lower-volume sequences
  • Consistent quality standard across all client accounts without senior oversight on every list
International Freight Forwarding & Logistics

Freight Right

How Freight Right keeps its contact database clean for outbound logistics campaigns across 180+ countries.

HR

Han Ryoo

Head of Product @ Freight Right

LinkedIn →
7%1%

Bounce rateon major campaigns

Mixed inSegmented

Role accountsrouted to phone outreach

The challenge

Freight Right has been moving cargo across more than 180 countries since 2007. Their contact database grew to include records from multiple sources — CRM entries, trade show lists, inbound form submissions, and legacy data going back years. Running campaigns to a mixed-quality database created two problems: bounce rates were higher than they should have been, and the team had no easy way to distinguish contacts worth prioritising for personalised outreach from those that were low-quality or unlikely to engage.

How they use BounceProtect

Freight Right exports segments of their contact database on a regular cadence and runs them through BounceProtect before any major campaign. Contacts marked Send go into the main campaign. Contacts marked Send With Caution get a lighter touch version. Do Not Send contacts are suppressed and flagged for CRM cleanup. The role account detection was particularly relevant — a significant portion of freight contacts use shared inboxes like ops@ or logistics@, and BounceProtect flags them so the team can route those accounts to phone outreach instead of email.

The deep domain analysis was a bonus we didn't expect to use as much as we do. Seeing which companies actually have a functioning website and a legitimate business behind the domain helps when deciding who to call versus who to email.

Han Ryoo, Head of Product

Key outcomes

  • Catch-all detection separating shared inboxes from individual contacts
  • Deep analysis identifying company legitimacy before high-touch outreach
  • Periodic database hygiene gradually cleaning the CRM rather than accumulating bad data

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