01
Write down who you sell to, and who you do not
Also called Ideal customer profile (ICP) and anti-ICP
Put your ideal customer, the customers you avoid, the people you sell to, their problems and your proof into one short document. Every list, score, email and AI agent reads from it, so everyone works from the same picture.
Why it matters. If "a good customer" is fuzzy on paper, it is fuzzy in every tool, score and email that follows. The written version becomes the agreement between sales and marketing.
How to do it
- Describe what you sell in one sentence a buyer would use, not your internal wording.
- List the industries, countries and company sizes you actually sell to and support today.
- Write what must be true for a real fit, and how you could prove it from public information.
- List who is not a fit: competitors, partners, look-alike businesses and existing customers.
- Name the roles you sell to, in priority order, including how their titles vary by country.
- Write their problems in their words, with one piece of proof for each.
What goes wrong
- Describing the customer you wish you had instead of the ones who actually buy.
- Forgetting the "not a fit" list, so the same wrong companies keep coming back.
Run it with the Account brief agent
02
Only add companies that pass hard checks
Also called Target account list (TAM) with account gates
Build your list of target companies from the bottom up, then let a company in only if it passes every check: big enough to pay, a real team that owns your problem, enough people to sell to, the right market and no open deal or recent rejection.
Why it matters. A short list that passes every check beats a long list you hope is right. The single best predictor is usually whether a real team owns the problem you solve.
How to do it
- Start from your written customer profile and pull every company that could match.
- Clean company websites to one standard format so duplicates show up.
- Check money: a revenue floor, or part of a group above it.
- Check ownership: is there a named team working on your problem, with visible output?
- Check reach: at least three people you could talk to across two teams, one of them senior.
- Check status: not a customer, no open deal, no "no" in the last 12 months.
What goes wrong
- Loose labels. If one tool says "Retail" and another "retail ", the rules downstream silently fail. Use one fixed list of values.
- Letting a company in because it "looks right" without evidence for each check.
03
Run cheap checks before paying for data
Also called Formula checks, exclusion lists and an enrichment waterfall
Before you pay for any data, let free checks decide which companies stay on the list. Simple formulas in your sheet or Clay table flag missing, wrong or duplicate rows, your exclusion lists remove customers and companies that are never a fit, and only the companies left get paid lookups. Personal contact details come last, once someone has decided to reach out.
Why it matters. Most data budgets are spent on rows that were incomplete, wrong or off-limits from the start. A free formula or an exclusion list would have ruled them out in seconds.
How to do it
- Remove duplicates, matching on the company website domain rather than the name.
- Add formula columns that check every row for free: is the website a real domain, are name, country, size and industry filled in, does the size fall inside your range, is the record recent? In Clay these are formula columns; in a sheet, simple IF and COUNTIF checks do the job.
- Add one "ready" column that is true only when every check passes. Rows that fail go to Hold with the reason, so you can fix or drop them.
- Apply your exclusion lists: your customer list, so customers are never cold-emailed, and your "not a fit" list of competitors, partners and look-alike businesses. Keep the two lists separate and give every excluded row a reason.
- Only then run paid company lookups, and only on rows marked ready. Set each paid column to run only when the ready column is true.
- Find people and pull email addresses and phone numbers last, only for companies and people you will actually contact.
What goes wrong
- Enriching first and filtering later, which pays for rows you throw away.
- Paid columns that run on every row by default. Add a run condition to each one.
- Mixing customers and "not a fit" companies in one list, so you cannot tell "already bought" from "never a fit".
- Trusting one data provider everywhere. Coverage differs by country.
04
Score fit and timing separately
Also called Fit score vs intent score, account tiers
Use two scores for two jobs. Fit (who they are) changes slowly and decides how much effort a company deserves. Timing (what they are doing now) changes daily and decides how fast you act. Crossing the two tells each rep what to do today.
Why it matters. Mixing both into one number hides the reason. A perfect-fit company that is quiet needs a different move than an average company showing strong interest.
How to do it
- Score fit from 0 to 100 using a few weighted facts: team ownership, size, sector, reach.
- Split companies into three tiers by fit: top (one-to-one attention), middle (small groups), rest (one-to-many).
- Score timing from live buying signals, letting old signals fade.
- Set a response time for each combination, for example top tier with strong signals gets a reply within 24 hours.
- Refresh fit every quarter and timing every day.
What goes wrong
- Ranking one global list, so one noisy segment floods the top tier. Rank within each segment.
- Treating the score as fact. It is a guess that you tune with results.
Timing comes from buying signals
05
Know where each company sits, from "never heard of you" to deciding
Also called Funnel stage mapping: unaware, aware, considering, deciding
Give every company on your list one stage: unaware (they do not know you exist), problem aware, aware of you, considering, or deciding. Base the stage on what the company actually did, not on a guess, and let the stage decide the message. Most of a good list starts at unaware, and that is normal.
Why it matters. A company that has never heard of you and a company comparing you with two rivals need completely different messages. Sending a demo request to the first wastes the contact. Sending a generic intro to the second loses the deal.
How to do it
- Unaware: a good-fit company with no visits, no replies and no engagement from anyone there. Goal: be seen. Use ads to your account list, useful posts and a short, helpful first message about their problem, not your product.
- Problem aware: people there read or comment on content about the problem you solve, or show a trigger such as a new leader or a hiring push. Goal: help them name the problem. Share a guide, a benchmark or a checklist.
- Aware of you: someone visited your site, opened a message, followed your page or attended your event. Goal: show how you solve it. Send a short case example or invite them to a free tool.
- Considering: several people from the company read comparison, pricing, case or integration pages, or reply with questions. Goal: remove doubt. Offer proof from a similar company and answer the objections they raise.
- Deciding: pricing, security or "talk to sales" pages, a request for a proposal, or procurement joining the thread. Goal: make it easy to say yes. Give the owner a clear plan, the people to involve and a date.
- Move a company up only when two or more people engage, and move it back down after 90 quiet days. Review the counts per stage every month: a pile-up at one stage shows where your engine is stuck.
What goes wrong
- Ignoring the unaware stage. Most of your best-fit companies have never heard of you, and pushing them for a meeting only teaches them to ignore you.
- Letting one curious person move a whole company to "deciding".
- Using the same email for every stage because it is quicker to build.
Which signals move a company up a stage
06
Sort the people in each company into personas
Also called Persona mapping and job title classification
Once the companies are right, find out which of your personas exist inside each one. Sort every job title into a persona using fixed rules, so the same title always lands in the same place. Each persona has its own problems and its own idea of what value looks like, so the persona decides what you say to that person.
Why it matters. A head of sales, a finance lead and an operations manager at the same company want different things from the same product. One generic message fits none of them. Knowing the persona is what makes outreach feel personal at scale.
How to do it
- Write a short card per persona: typical titles, what they are measured on, their top problems in their own words, and the value they expect from a solution like yours.
- Remove non-targets first: students, interns, former employees, and roles that borrow your words but do a different job.
- Match titles to personas with rules checked in order. The first rule that matches wins and logs a reason. Strong phrases go first, then a seniority rule: remove words like "head of" or "VP" and see what is left.
- Default to "no persona" when nothing matches, rather than guessing.
- Roll it up per company: which personas you found, and which are missing.
- Write the message per persona: open with their problem and the value they care about, then add the company-specific reason for reaching out now.
- Test rule changes on a set of tricky titles before running the full list.
What goes wrong
- Filtering on keywords instead of the actual job. The same word can appear in a buyer’s title and in a title that has nothing to do with you.
- Sending every persona the same message with only the name changed.
- Changing rules without logging why, so nobody can explain the results a month later.
Run it with the Right-person check agent
07
Map everyone involved in the decision by buying role
Also called Buying committee mapping
Personas tell you what each person cares about. Buying roles tell you what part they play in the decision: the budget holder who signs, the champion who pushes for you, the evaluators who test and compare, and the daily users who live with the result. Give every contact both, and you see which companies rely on a single contact and who to approach next.
Why it matters. B2B decisions involve many people. If you only know one of them, the deal dies when that person goes quiet or leaves. The same persona can play different roles in different companies, so map the role per company, not per title.
How to do it
- Define four buying roles: budget holder, champion, evaluator, daily user.
- Give each contact a role from their seniority, team and what you know about the deal, using clear rules. Keep it next to their persona, not instead of it.
- Roll it up per company: how many people, how many teams, which roles are missing.
- Plan the order of approach, often starting with the champion and bringing the budget holder in with a senior colleague.
- Shape each message by both: the persona decides the problem you talk about, the role decides what you ask for. A champion gets material to share inside; a budget holder gets the business case.
What goes wrong
- Keyword rules that misfire, for example "president" matching "vice president". Test the order of your rules.
- Counting ten people from one team as good coverage.
- Assuming the most senior title is the budget holder. Check who actually signs.
Forrester (2026) reports an average of 13 internal and 9 external people influencing a B2B purchase. [analyst research]
08
Clean your CRM company by company
Also called CRM deduplication and data hygiene
Clean the CRM starting with the companies that hold the most contacts, using contacts’ email domains as the source of truth. Merge only when you are sure two records are the same business, because a wrong merge destroys data.
Why it matters. Duplicates split history across records, double-count pipeline and send the same person two different emails.
How to do it
- Rank companies by number of contacts and start at the top: one fix cleans many records.
- Compare each company’s name with its contacts’ email domains.
- Sort look-alike records into: true duplicate, related company (parent or subsidiary) or wrongly assigned.
- Merge only true duplicates. Send related companies to a person to decide.
What goes wrong
- Merging on "probably the same". Two companies can share a brand word.
- Tools that change record IDs when merging, so old links break.
Questions people ask
What is an ideal customer profile?
An ideal customer profile is a written description of the companies most likely to buy from you and succeed with your product: industry, size, location, the team that owns the problem, and what must be true for a real fit.
How many target accounts should a small team have?
Enough that each rep can give real attention to the top tier. Many teams start with a few hundred companies in total, of which a few dozen get one-to-one attention. Quality of the list matters more than size.
What is the difference between fit and intent?
Fit is who the company is. Intent is what the company is doing now. Use fit to decide which companies deserve effort and intent to decide when to act.