Any structured text works — name, role, market, any notes about their deals or activity.
Scoring contacts…
Analyzing deal signals and engagement likelihood
Rank
Contact
Score
Tier
Primary signal
Why they'll engage
Channel
Analytics
Outbound performance across all segments and channels
Outreach funnel
Scored
247
100%
Contacted
180
73%
Opened
84
34%
Replied
32
13%
Converted
17
7%
Channel performance
Email
Open 34%Reply 11%
LinkedIn
Accept 28%Reply 9%
Phone
Connect 22%Proceed 14%
Direct mail
Engaged 8%Reply 3%
Routing breakdown
AveryGPT70%
Eastern Union20%
GPARENCY10%
Score distribution
High ≥80
38
Mid 60–79
114
Low <60
95
Signal type breakdown
Property42%
Financial31%
Deal Network18%
Lender Activity9%
Reply queue
Classify incoming replies and route them to the right destination.
📬
No replies yet
When prospects reply, log them here to classify and route instantly.
Settings
Configure the engine's scoring, routing, and channel behavior
Scoring weights
Control how the composite engagement score is calculated
How much raw deal/property/financial signal data drives the score
How much the recency of signals affects score
How much product-to-segment match affects score
Routing thresholds
Adjust the confidence level required for auto-routing vs defaulting to AveryGPT
Replies with confidence below this score default to AveryGPT with a confirmation message
Active channels
Toggle which channels the orchestrator can use per segment
${[['Email','Always on — primary outbound channel',true],['LinkedIn','Enabled for brokers and GPs (day 3+)',true],['Phone','High-priority leads only (score ≥ 80)',true],['Direct mail','Disabled — low digital engagement leads only',false]].map(([c,s,on])=>`
${c}
${s}
`).join('')}
State / market scope
Restrict outreach and scoring to specific states
Comma-separated state abbreviations. Leave blank for all states.