The Account List: Building a Tiered TAL for a New Vertical
Objective: Given synthetic firmographic, technographic, and intent data for 20 prospective accounts, build a tiered Target Account List (1:1 / 1:Few / 1:Many) using the lesson's four-input framework.
Adyen's enterprise sales team wants to push harder into mid-market fashion and beauty e-commerce retailers. You have a spreadsheet of 20 candidate accounts with headcount, tech stack, and intent signals.
Layer ICP firmographics, technographics, intent data, and sales input to assign each account to a tier, then justify the split.
Before you start
What you'll need
Free path (everything below is enough to finish)
Free, handles a 20-row scored list without needing a paid intent-data platform
Free CRM tier is enough to tag and track account status alongside the TAL
The process
2 steps
Step 01 of 02
A strong TAL layers four inputs: ICP firmographics (industry, size, geography), technographics (which tools the account already runs), intent data (who's actively researching now), and sales input (which accounts AEs already know are live).
Of your 20 candidate accounts, 12 run a checkout platform Adyen already integrates with, 5 show recent intent spikes on 'payment orchestration' content, and sales flags 3 as already in active conversation. How do you combine these into one ranked list?
Procedure
- List all 20 accounts as rows
- Score firmographic fit (industry + headcount match) as a checkbox column
- Score technographic fit (already runs a compatible checkout stack) as a checkbox column
- Mark intent-spike accounts and sales-flagged accounts separately
- Sum checked columns per account to get a raw priority score
Account -> Firmographic -> Technographic -> Intent -> Sales flag -> Score Account A (mid-market beauty, 300 staff) -> yes -> yes -> yes -> yes -> 4 Account B (mid-market fashion, 250 staff) -> yes -> yes -> no -> no -> 2 Account C (out of size range) -> no -> yes -> no -> no -> 1
Healthy
The top-scoring accounts have hits across at least 3 of the 4 inputs, not just one strong signal masking three weak ones.
Unhealthy
Prioritizing an account purely on intent data while ignoring that it doesn't fit the firmographic ICP at all.
What this means
A 4-input score separates real fit from noise. An account with only an intent spike and nothing else is a lead, not yet a target account.
So what do I do about it?
| Symptom | Action | Effort |
|---|---|---|
| TAL built from intent data alone | Cross-check every intent-flagged account against firmographic fit before adding it | 30 min |
Step 02 of 02
1:1 (Strategic) gets bespoke content for 20-50 must-win accounts and 50-60% of budget. 1:Few (Cluster) groups lookalikes with semi-customized content. 1:Many (Programmatic) runs templated content at scale for hundreds of ICP-fit accounts.
Your top-scoring 3 accounts (score 4/4) include sales-flagged, in-conversation deals. Your next 8 accounts (score 2-3) share the same fashion-retail profile. The remaining 9 are ICP-fit but unengaged. How do you tier them?
Procedure
- Assign the top 3 score-4 accounts to 1:1 (bespoke content, executive outreach)
- Assign the 8 score-2/3 fashion-retail accounts to 1:Few (one shared industry-specific campaign)
- Assign the remaining 9 ICP-fit accounts to 1:Many (templated, intent-triggered ads)
- Confirm the 1:1 tier stays capped near 20-30 accounts even as the list grows
Tier -> Accounts -> Content approach 1:1 -> 3 (score 4, sales-flagged) -> Custom ROI model + executive briefing per account 1:Few -> 8 (fashion-retail cluster) -> One industry-specific case study + tailored landing page for the cluster 1:Many -> 9 (ICP-fit, unengaged) -> Intent-triggered display ads + templated nurture
Healthy
1:1 stays reserved for the highest-scoring, sales-confirmed accounts, not padded with borderline fits just to look ambitious.
Unhealthy
Putting all 20 accounts into 1:1 because the team wants to feel like every account gets VIP treatment, which no one can sustain.
What this means
Tier size should shrink as personalization depth increases. If 1:1 has more accounts than 1:Few, the program is over-committing bespoke effort it can't deliver.
So what do I do about it?
| Symptom | Action | Effort |
|---|---|---|
| 1:1 tier has grown past 30 accounts | Demote the lowest-scoring 1:1 accounts to 1:Few before the next quarter | 30 min |
Final deliverable
A tiered Target Account List (1:1 / 1:Few / 1:Many) for 20 accounts, each tagged with the firmographic, technographic, intent, or sales-input signal that justified its tier.
See a reference example
Wise Business, Fintech Vertical TAL (excerpt) 1:1 (3 accounts): Includes one account where sales already has a live proposal in review, custom ROI model in progress. 1:Few (6 accounts): Mid-market fintech app cluster sharing the same 'multi-currency payout' pain point, one shared case study in production. 1:Many (11 accounts): ICP-fit fintech accounts with no engagement yet, entered into intent-triggered ad sequence.
Success criteria
You're done when you can:
- Every account's tier assignment is traceable to at least 2 of the 4 TAL inputs
- The 1:1 tier stays reserved for the highest-scoring, sales-confirmed accounts only
- Tier sizes shrink as personalization depth increases (1:1 smallest, 1:Many largest)