Sales outreach · Production

Autobound gives tab32 25% higher engagement rates and 7 hours saved per rep weekly

The problem

tab32's outbound emails were too generic to resonate with dental practice decision-makers, requiring 5-15 minutes of manual research per contact that consumed 7+ hours per rep per week, while new SDRs needed months of training to produce effective dental-specific messaging.

Workflow diagram · grounded in source
1
Clay identifies ICP prospect
trigger
“When Clay identified a new prospect matching tab32's ICP criteria, the contact was automatically sent to Autobound's Insights Engine”
2
Deep signal research
ai_action
“Autobound then performed deep research on each contact, pulling from 35+ data sources to surface relevant signals like the practice's size, location, technology stack, recent events, and the individual contact's professional background”
3
Persona-specific email generation
ai_action
“Using these insights, Autobound generated a fully personalized email sequence tailored to the specific persona”
4
Rep review and approval
human_review
“Reps could review and approve AI-generated drafts with a quick scan rather than building each email from scratch”
5
Automated delivery via Outreach
output
“which was then loaded into Outreach for automated delivery”
Reported outcome

Within 90 days, tab32 saw 25% higher engagement rates across all outbound sequences, reclaimed 7 hours per rep per week, and cut new rep onboarding time to full productivity by 50%.

Reported metrics
Engagement rates25% higher
Time saved per rep weekly7 hours reclaimed weekly per rep
Rep onboarding to full productivity50% faster
Open and reply ratesSignificant improvement over previous benchmarks
Show all 7 reported metrics
engagement rates25% higher
time saved per rep weekly7 hours reclaimed weekly per rep
rep onboarding to full productivity50% faster
open and reply ratesSignificant improvement over previous benchmarks
rep moraleMeasurably improved, with reduced burnout reported
manual research time per rep weekly (baseline)7+ hours per rep per week
research time per contactdropped from 5-15 minutes to near zero
Reported stack
AutoboundInsights EngineAI StudioClayOutreach
Source
https://www.autobound.ai/case-study/tab32
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Within 90 days, tab32 saw 25% higher engagement rates across all outbound sequences, reclaimed 7 hours per rep per week, and cut new rep onboarding time to full productivity by 50%.

What tools did this team use?

Autobound, Insights Engine, AI Studio, Clay, Outreach.

What results were reported?

Engagement rates: 25% higher; Time saved per rep weekly: 7 hours reclaimed weekly per rep; Rep onboarding to full productivity: 50% faster; Open and reply rates: Significant improvement over previous benchmarks (source-reported, not independently verified).

How is this sales outreach AI workflow structured?

Clay identifies ICP prospect → Deep signal research → Persona-specific email generation → Rep review and approval → Automated delivery via Outreach.

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