Lead quality and outbound
Lead quality is a model, not a list.
Bought lists and generic intent feeds produce the same leads your competitors get. A signal-based pipeline starts from who actually bought from you, adds custom signals for your market, and controls for freshness and false positives before anyone sends an email.
Part of one fixed build: $7,500, 21 days, $2,500 back if it isn't running as scoped. Pricing details
Ask yourself
Three questions that usually expose it.
- What do your best five customers had in common the month before they bought?
- Does your lead score ever go down?
- How old is a signal by the time a rep acts on it?
Failure modes
What breaks, and why.
| Failure | What you see | Root cause |
|---|---|---|
| Scores everyone ignores | Lead score says 90, the rep says junk. | The score adds points for activity but never subtracts. No negative signals, no decay, and weights that were guessed instead of tested against closed-won deals. |
| Signals everyone else has | Funding and hiring alerts fire, but so does every competitor's outbound. | Single generic signals are public. Value comes from composite signals specific to your market: combinations of events and context that mean 'ready to buy' for you. |
| Old news treated as fresh | Reps reach out about a hire or round from months ago. | Signals have no freshness window, so a stale event scores like a new one. |
| Outbound that hurts the domain | Replies drop while volume rises. | Sending was scaled before list quality and deliverability were controlled, and nothing writes outcomes back to tune targeting. |
First 48 hours
What I check before changing anything.
- Closed-won and closed-lost accounts from the last 12 to 24 months, to derive fit
- The current lead score: inputs, weights, decay and negative criteria
- Which signals you track today, how fresh they are when a rep sees them
- Hit rate: share of routed leads reps actually work
- Sending setup: domains, authentication and complaint and bounce handling
- Whether replies and meetings write back to the CRM with the signal that triggered them
Decisions we make with you
Tradeoffs, written down.
Fit vs. timing
Fit (who should buy) and timing (why now) are scored separately. A perfect-fit account with no signal goes to nurture, not to a rep.
Precision vs. coverage
Tighter signal rules mean fewer, better accounts. We start precise and loosen only when hit rate holds.
Composite signals
We build signals that combine events, for example a new leader in the buying function plus a related job posting within a set window, instead of reacting to any single event. Hiring, funding and tech changes are only starting examples.
A team scored any account that raised money. Most were too early to buy. A composite signal requiring a funding event plus a relevant open role within a set window produced far fewer accounts, and reps worked a much larger share of them.
Want this checked on your own CRM first? Get a free one-page teardown, no call needed.
FAQ
Common questions.
How do you know a signal actually predicts buying?
Each signal is tested against your closed-won and closed-lost history before it's switched on, and then tracked on hit rate: the share of signalled accounts your reps actually work and convert.
What stops reps getting flooded with false positives?
Composite rules, freshness windows and negative signals. We start precise, cap daily volume, and loosen rules only when hit rate holds.
What if our ICP is wrong to begin with?
Then the closed-won analysis will show it, and that's worth knowing on its own. We define fit from who actually bought and stayed, not from the ICP slide, and flag where the two disagree.
Whose domains and inboxes send the email?
Accounts in your company's name, set up with proper authentication on separate sending domains so your main domain is protected. Every email includes an opt-out, following CAN-SPAM and platform terms.
What happens on day 22?
You own the system and the operating guide. Either your team runs it, or I run and improve it on the month-to-month Pipeline Ops retainer at $5,000/month.
Connected problems
The build fixes these as one system.
CRM data foundation
Duplicates are a symptom. The disease is uncontrolled record creation.
HubSpot
Most HubSpot problems come from a handful of platform behaviours nobody designed for.
Salesforce
Salesforce gives you every control. Most orgs have them configured against each other.
Pipeline reporting
If two people can define 'pipeline' differently, your dashboard is an opinion.
Find out what your best customers had in common before they bought.
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