The story How we approached it What it took The sales motion What I learned The workflow Do it yourself

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BUILD LOG · THE ENRICHMENT BAKE-OFF

I ran a bake-off between two enrichment vendors for pennies. The answer was not pick one.

We needed a verified email and cell for every contact. The email was easy. The cell phone was the wall, the signal no single vendor reliably had, and that is what led to the bake-off: two vendors, a controlled sample, about thirty-three cents to find out who could actually land a mobile.

Steal this build ↓See the stack The people part →

>1 in 3

of pipeline dollars booked, up from about 1 in 5

2x+

new-business bookings per AE

$0.33

the bake-off that started it

1 signal

the scarce one it all turned on: a verified cell phone

THE STORY, FROM THE SEAT

Here is one I actually shipped. What happened, what I did, and the stack if you want to run it yourself.

Reps needed a verified email and a cell for every contact. Email is easy; almost anyone has it.

The cell phone is the wall, the field most vendors are thin on, and the one that actually gets a rep a live conversation. The instinct is to pick one vendor and hope. But a head-to-head that only asks who is better misses the real question: who can land the hard signal, the mobile, and where does each one fall short.

Keep Building,

Heath

FOUNDER, THE SALES OPERATOR

THE BUILD IN FIVE MOVES · THE GIANT METHOD

GReps needed a verified email and a cell for every contact. The email was easy; the cell phone was the wall.
IIt took a controlled sample, both vendors on the same accounts for about thirty-three cents, and Deepline orchestrating the cost-ordered waterfall.
ADeepline runs the cost-ordered waterfall; the operator decides which vendor owns which half of the signal.
NReps saw the source and the verification behind each contact, so they worked the list instead of second-guessing it.
TA dollar of pipeline booked better than 1 in 3 instead of about 1 in 5, and new-business bookings per AE more than doubled.

RUN THE PLAY YOURSELFThis exact build is a playbook. Run it on your own data.

→

01 / HOW WE APPROACHED THE PROBLEM

Ran the loop.

The instinct was to pick one vendor and hope. A head-to-head that only asks who is better misses the real question: who lands the hard signal, the mobile, and where each one falls short. So both vendors ran against the same accounts, about thirty-three cents total, scored on the field that actually mattered: a valid, reachable cell. Neither won.

1
Test both vendors on the hard signal
I ran both vendors against the same accounts for about thirty-three cents total, scoring them on the field that actually mattered: a valid, reachable cell phone, not just an email.
2
Map coverage, not a winner
Neither vendor won. They covered different halves, so on any given contact one might have the cell and the other the email. The right answer was a waterfall that ran each for what it owned, then verified, not a single pick.
3
Find the cheapest predictive question
The most predictive signal was a free MX-record lookup. A simple domain check instantly flagged which accounts ran our best-fit email stack, and it cost nothing. The expensive data was not the valuable data.
4
Turn it into a cost-ranked model
The bake-off did not end at coverage. It became a prioritization model, orchestrated through Deepline: enrich in cost order, the free MX check first, cheap fields next, the expensive vendor only when the cheaper rungs miss. One workflow, not a pile of vendor logins. Same data, a fraction of the spend, and a model that scales.

02 / WHAT IT TOOK CROSS-FUNCTIONALLY

Nobody ships this alone. Here is who had to move.

A bakeoff is a spend decision wearing a data costume. The test design was ours; the standards and the sign-off were shared.

REVOPS

The data standards the vendors were judged against.

Coverage and accuracy only mean something against a defined bar: which fields matter, on which segments, verified how. The bar came first, then the bakeoff.

FINANCE

The vendor spend.

The receipt of a bakeoff is a contract decision. Measured coverage per dollar is what turned a tooling preference into a defensible spend call.

03 / HOW WE TURNED IT INTO A SALES MOTION · THE PEOPLE PART

The waterfall filled the data. Reps still had to trust it enough to act.

Clean contact data is only worth the outreach it powers, and reps ignore a list they do not believe. The leadership half was making the enriched data something the team acted on, with a message worth sending.

THE FRAMEWORK BEHIND IT

SMART Prospecting on enriched targets

The waterfall gives you the verified human; SMART gives the rep the reason to reach out. Show you understand the account, map the problem, acknowledge the cracks, reveal the impact, take action, grounded in the enrichment, not a merge field.

01
Made the data earn rep trust with a receipt
Showed reps the source and the verification behind each contact, so they worked the list instead of second-guessing it.
02
Paired every contact with a reason, not just an email
A verified address with no angle is still a cold list, so I coached the angle, not just the coverage.
03
Closed the loop on bad rows
Reps flagged the misses back into the waterfall, so the data and the trust both improved over time.

Turn the list into outreach →

04 / WHAT I LEARNED

Not proof. Just what the build taught me.

01
The expensive data was not the valuable data
The most predictive signal was a free MX-record lookup. A simple domain check flagged which accounts ran the best-fit email stack, and it cost nothing.
02
Run a bake-off to map coverage, not a winner
Neither vendor won; they covered different halves of the signal. The right answer was a waterfall that ran each for what it owned, then verified, not a single pick.
03
A verified address with no angle is still cold
Clean contact data is only worth the outreach it powers, and reps ignore a list they do not believe. The coaching was the angle, not just the coverage.
04
Cost order beats a pile of vendor logins
The bake-off became a prioritization model: the free MX check first, cheap fields next, the expensive vendor only when the cheaper rungs miss. Same data, a fraction of the spend.

05 / THE WORKFLOW

The runnable version. Copy it into your stack.

DeeplineOrchestrated the whole cost-ordered waterfall as one workflowControlled sampleBoth vendors, same accounts, about thirty-three cents totalThe free question firstA free MX lookup flagged best-fit email-stack accountsProvider oneKept only for the half of the signal it ownsProvider twoKept only for the other half it owns

[ SALES OPERATOR ]

The Enrichment Bake-Off

Heath Barnett · Sales Operator

G / Groundthe problem that started all of it, with the receipt and the cost

Data strategy

The cell phone is the wall.

Email is easy; the mobile is the field most vendors are thin on, and the one that gets a rep a live conversation.

Drag

Pick one vendor and hope is the wrong game.

A head-to-head that only asks who is better misses who lands the hard signal and where each one falls short.

A / Assignthe build, block by block, and who owns each one. Open a step to see it run.

HUMAN + AI, IN THE LOOP

Deepline orchestrates the cost-ordered waterfall; the operator decides which vendor owns which half of the signal.

Ask the free question first

Deepline01

Run a free MX lookup

Details

A free domain check flags which accounts run our best-fit email stack. The cheapest predictive signal, and it costs nothing.

Waterfall the hard signal

Enrich in cost order until one hits02

Orchestrated by

Deepline

Waterfall, first hit wins · 4 providers

FullEnrichtry 1

Findymailtry 2

LeadMagictry 3

ContactOuttry 4

Deepline waterfalls each provider cheapest-first until one returns a verified cell. The free field first, the expensive vendor last.

Deepline03

Verify the cell

Details

Only a reachable mobile counts, not just an email.

Decide the model

The operator04

Keep each vendor for the half it owns

Details

Neither vendor won; they covered different halves. The answer was a waterfall, not a single pick.

Human

N / Normalizethe motion that made it stick

A workflow without a motion is dead. This is how it became the way the team works.

Data earned rep trust with a receipt

Reps saw the source and the verification behind each contact, so they worked the list instead of second-guessing it.

Every contact came with a reason

A verified address with no angle is still a cold list. SMART on enriched targets gave the rep the reason to reach out, grounded in the enrichment, not a merge field.

Bad rows closed the loop

Reps flagged the misses back into the waterfall, so the data and the trust both improved over time.

T / Tie backthe result it drove, and how they know

RESULT · 01

9 of 10

supposedly-cold accounts already known to a vendor.

RESULT · 02

2 halves of the signal

neither vendor owned alone.

RESULT · 03

A fraction of the spend

same data, cost-ordered.

OUTPUT · 01

Free MX pre-filter

Best-fit accounts flagged for nothing.

OUTPUT · 02

Cost-ordered waterfall

Cheapest predictive field first, vendor last.

OUTPUT · 03

Verified email and cell

The hard one, landed and checked.

The Sales Operator

06 / HOW YOU DO IT TOO

Here is what I built. Here is how you build it.

The whole thing installs as one plugin. Or grab the skills a la carte. Everything on this page, runnable, on what you paste today.

✓ EVAL PASS · 4/4

THE PLAYBOOK · ONE INSTALL

Book a meeting at a target account

5 skills chained into one runnable play. Installs as a single plugin, no copy-pasting each skill. It runs on what you paste; connect your stack to go live.

SEE THE FULL PLAYBOOK →

SEE IT RUN IN CLAUDE

EXAMPLE CHATJordan, an SDR, running the loop in one sitting

I own the mid-market fintech segment this quarter and I'm starting from a blank list. Can you build me a target list from our ICP?

Step 1· Outbound List Builder

Pulled accounts matching your ICP, ran fit gates, and scored each one 0-100 so the strongest land on top. Tiered them and tagged the personas to hit inside each account, with a one-line reason each earns its spot.

tier A18 accts

tier B31 accts

Receipt

64 fintech accounts scored and ranked, top 18 flagged as tier A worth working first.

A few of these just raised or are hiring hard. Which ones have a fresh reason to reach out right now?

Step 2· Trigger Outreach

Scanned the list for live signals and found funding rounds, new VP hires, and product launches inside the last 30 days. Kept only the ones still fresh and picked the single angle each trigger earns.

Receipt

9 accounts with a trigger in the last 30 days, each with one angle to lead on.

Take the top account, the one that just hired a VP of Rev Ops, and write me a cold email.

Step 3· Cold Email Writer

Built the email on one idea, the new VP inheriting a messy handoff, with an opener that shows I actually looked. Short, soft CTA, no filler. Added two follow-ups so it's a 3-touch sequence.

Receipt

3-touch email sequence, opener under 90 words, one ask at the end.

Same person, but for LinkedIn. What do I send there?

Step 4· Linkedin Outreach

Wrote a connection note that doesn't pitch, then two value-first follow-ups for after they accept. Since this prospect is cold, the thread opens with something useful to them, not a demo ask.

Receipt

Connection note plus 2 follow-ups, matched to a cold prospect.

Okay, now stitch all of this into one cadence so I know what to do on which day.

Step 5· Cadence Builder

Laid out the full sequence across email, LinkedIn, and call, with timing and the intent behind every touch so nothing is just a bump. Ended it with a clean break-up so dead threads close themselves.

touches11

days18

Receipt

18-day, 11-touch cadence ready to launch across the top 18 accounts, first meeting expected inside 2 weeks.

THE SKILLS IT USES

Fill the gaps: email, phone, LinkedIn, title.

enrichment-analyst

Stack the right tools and signals for the workflow.

stack-the-tech

Start any analysis without connecting a thing.

bring-your-data

THE OTHER HALF · LEAD THE TEAM