By sales motion

Your TAM is too large to research manually.
Agents prioritize by context, not data points.

High-velocity teams don't lose deals because of bad reps. They lose them because reps spend Monday morning sorting by employee count and industry instead of calling the accounts that are actually ready to buy this week. Volume without prioritization is just noise.

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The problem

Volume is the game. But quality is what converts.

Prioritizing by data points, not buying context

Filtering by employee count, industry, and revenue tells you who fits your ICP on paper. It tells you nothing about who is ready to buy this week. Reps end up working accounts that look right but aren't moving, while the ones with genuine buying signals go untouched.

Research takes hours per account

Before a rep can send a meaningful email they need to understand the company, find the right contact, verify their details, and write something worth reading. Multiply that by 80 accounts and the math doesn't work.

Data-driven outreach that sounds like everyone else

When prioritization is based on data points, outreach follows the same logic: insert company size, mention industry, reference a generic pain point. Prospects receive ten versions of the same email every week. Volume without context is indistinguishable from spam.

The shift

From data-point filtering to context-driven prioritization.

Before Evergrowth

Data-driven filtering, generic outreach

Reps filter by employee count, industry, and revenue, the same data every competitor has access to
Hours of manual research per account, most of the TAM never gets touched
Contact lists built by job title from a shared database, same contacts every competitor is reaching
Outreach inserts data variables into templates, prospects feel scraped, not understood
No consistent cadence, the TAM gets worked when reps have spare time
With Evergrowth

Context-scored TAM, research-based prioritization every week

Agents score every account by research quality, how many buying signals actually came back positive, not just whether the firmographics match
Full TAM researched every week, not just the accounts reps remember to check
Contact Finder cherry-picks the right people using persona cards, not job titles
Outreach is written from what agents actually found at that account, not from a shared template with data variables
Reps start Monday with a research-scored, contact-ready queue. Every week, without asking.
How it works

Every week, agents score your TAM
and hand reps a prioritized queue.

This isn't a one-time list-building exercise. It runs every week, automatically, across your entire addressable market. And unlike data-point filtering, the ranking is based on research quality, what agents actually found, not what a database says about company size.

Account Qualification agent
01

Account Qualification

Every account in your TAM gets scored against your ICP criteria. Firmographic fit is the starting point, but it's not the ranking. Accounts that don't meet baseline fit are filtered out. The ones that do move forward for deeper research.

Account Qualification agent
Account Research agent
02

Account Research

Qualifying accounts get researched in depth. The research score reflects what percentage of your defined signal questions came back positive: hiring signals, strategic initiatives, recent news, product announcements. This is what separates context-driven prioritization from data-point filtering, two companies with identical firmographics can score completely differently based on what's actually happening inside them.

Account Research agent Data-driven vs context-driven
Contact Finder agent
03

Contact Finder

From the highest-scoring accounts, Contact Finder identifies the right people. Not by job title, but by persona cards your RevOps team built. Economic buyer, champion, influencer. Verified contacts, including people not findable through standard data vendors.

Contact Finder agent
Play Copywriting agent
04

Play Copywriting

For every cherry-picked contact, the Play Copywriting agent generates outreach grounded in what the research found. Not a template with data variables. A message that references what's actually happening at that company right now.

Play Copywriting agent

Reps start every week with a ranked list. Highest research score at the top. Not sorted by company size. Not filtered by industry tag. Ranked by how much buying context agents found. Contacts verified. Outreach ready to review and send.

The team

RevOps sets it up. Agents run it. Reps close.

Three roles, one system. Each doing the work they're actually built for.

RevOps avatar
RevOps

Configures the system once

Defines the ICP scoring criteria, builds the persona cards, specifies which signals the research agents look for, and sets the weekly cadence. Done once, updated when the strategy changes. The playbook reflects what the team knows about the market.

RevOps in Evergrowth
Agents

Run the full loop, every week

Qualify, research, find contacts, and write outreach across the entire TAM without being triggered manually. No tickets. No requests. No waiting for someone to remember to run the list. The queue is ready before the week starts.

Meet your GTM Squad
Sales Reps avatar
Sales Reps

Start the week ready to call

Open a prioritized queue on Monday morning. Every account researched. Every contact verified. Outreach ready to review and send. Time goes to conversations, not to figuring out who deserves attention this week.

Sales Reps in Evergrowth
37
True ICP-fit accounts identified from 317 in CRM
73
Verified contacts rebuilt from 4 relevant ones
+30%
More phone numbers vs. a large incumbent data vendor
+60%
Better contact accuracy vs. the same incumbent vendor
In practice

Luzmo went from a dirty CRM to a pipeline-ready list in one workflow.

Luzmo's CRM had 317 accounts and 278 contacts. After running them through qualification and persona validation, 37 accounts were true ICP fits and only 4 contacts were still relevant. Agents rebuilt the buying groups to 73 verified contacts with fresh data. Reps had a researched, contact-ready list without spending a week doing it manually.

"Accurate data is much more important than a lot of data which is not qualitative."

Jonathan Wuurman Jonathan Wuurman, VP Sales, Luzmo
Read the full Luzmo story
Related playbooks

The playbooks that power high-velocity motions

Newbiz Gap

Work your full TAM. Every account not yet in your CRM, qualified and researched automatically.

Explore

Newbiz Recycling

Dormant CRM accounts don't stay dormant. Research agents resurface the ones worth contacting again.

Explore

Signal-based Outreach

Agents monitor your TAM for buying signals and trigger outreach automatically when they fire.

Explore

Inbound Lead Qualification

Every inbound lead qualified, researched, and enriched the same way Sales would, before the rep picks up the phone.

Explore
Go deeper

Everyone has the same data. Context is what separates you.

Two reps reach the same contact at the same account. One's agent works from a list of data fields. The other's works from a research brief built from real buying signals. The difference in reply rate isn't about copywriting, it's about what the agent had to work with before it wrote a single word.

See data-driven vs context-driven
What a data-driven agent gets
{first_name}: Sarah
{company}: Acme Corp
{employee_count}: 250
{industry}: SaaS
{headquarters}: New York
{pain_point}: [select from list]
{cta}: [select from list]
What a context-driven agent gets
Account: Acme Corp — research score 87%
Signal: VP RevOps role opened 3 weeks ago
Signal: 3 BDRs hired last month
Signal: CEO — "scaling outbound is our Q3 priority"
Contact: Sarah Chen, Head of Sales Ops
Persona match: confirmed decision maker
Play: outbound efficiency at scale

Stop guessing which accounts to work this week.

Agents score your TAM by research quality, find the right contacts, and hand reps a context-driven priority list every week. Request a demo to see it run on your market.

Request a demo