Account tiering is the most important decision in ABM. It determines which accounts get your best resources, which get scaled attention, and which get nurture.
Get tiering wrong, and you over-invest in low-value accounts or under-invest in high-value ones. Get it right, and you allocate resources where they drive the most revenue.
This guide walks you through building a tiering methodology: criteria, quantitative scoring, qualitative factors, and implementation.
Tiering is your resource-allocation framework. You probably have:
You can’t serve all 500 accounts the same way. You tier them.
Your Tier 1 accounts should drive 40-60% of your pipeline. Your Tier 2 should drive 25-40%. Your Tier 3 should drive 10-15%.
If the distribution is different (e.g., Tier 1 drives 20% of pipeline), your tiering criteria are wrong. Adjust them.
Tiering criteria are the factors you use to decide which tier an account belongs to.
Most teams use a mix of quantitative (revenue, company size) and qualitative (ICP fit, strategic importance) factors.
Revenue potential:
What’s the largest deal you could close at this account? This is a function of: - Company size (number of employees, revenue). - Department size (size of the team that would use your solution). - Budget allocation (what percent of their budget goes to solutions like yours).
Example: Your average deal is 50K. An enterprise with 5,000 employees and a large sales team might have 200K potential. A small startup might have 5K potential.
Define bands:
Company size:
Measured in employee count or revenue.
Example:
(These are illustrative; adjust based on your business.)
Geographic region:
If you have geographic expansion goals, prioritize regions where you’re investing.
Example:
Industry vertical:
If you have certain verticals where you’re strong, prioritize them.
Example:
Deal characteristics (if already in pipeline):
If the account has an active opportunity, consider:
A Tier 3 account with a 200K active deal should be re-tiered to Tier 1 for the duration of that deal.
ICP fit:
How well does the account match your Ideal Customer Profile?
Define 3-5 ICP characteristics (e.g., “use Salesforce,” “have a dedicated RevOps team,” “50-500 employees,” “SaaS industry”).
Score the account: How many characteristics does it match? 0-2 matches = low fit. 3-4 = medium fit. 5+ = high fit.
Strategic importance:
Some accounts matter beyond revenue. Examples:
A small company that’s a strong reference might be Tier 1 despite small revenue potential.
Competition and win likelihood:
Some accounts are more likely to buy because of competitive positioning, existing tool usage, or relationships.
Score: Low win likelihood = Tier 3. Medium = Tier 2. High = Tier 1.
Market timing:
Some accounts are in a market window and some are not.
Combine quantitative and qualitative criteria into a scoring model.
Tier 1: (Revenue Potential > 150K) OR (Company Size > 2000 employees AND ICP Fit > 80) OR (Strategic account AND Revenue > 50K)
Tier 2: (Revenue Potential 30K-150K) OR (Company Size 500-2000 AND ICP Fit > 60) OR (Strategic account AND Revenue < 50K)
Tier 3: All others
This model is simple but covers most cases. Implement it in a spreadsheet or Salesforce formula and apply to your account database.
If you want more precision, build a weighted score:
Account Score = (Revenue Potential × 40%) + (ICP Fit × 30%) + (Strategic Importance × 20%) + (Intent Signals × 10%)
Revenue Potential: 0-100 scale
- 0-50K ARR: 20 points
- 50K-150K ARR: 60 points
- 150K+ ARR: 100 points
ICP Fit: 0-100 scale
- Matches 0-2 ICP criteria: 25 points
- Matches 3-4 criteria: 60 points
- Matches 5+ criteria: 100 points
Strategic Importance: 0-100 scale
- Not strategic: 0 points
- Reference account or partner: 50 points
- Logo account or exec relationship: 100 points
Intent Signals: 0-100 scale
- No recent signals: 0 points
- 1-2 signals (job posting, news): 50 points
- 3+ signals (job posting + funding + news): 100 points
Tier thresholds:
- Score 80-100: Tier 1
- Score 50-80: Tier 2
- Score <50: Tier 3
Calculate this quarterly. Accounts move between tiers as scores change.
Combine both approaches:
If (Revenue Potential > 150K AND ICP Fit > 80) = Tier 1 (rules-based, most important)
Else If (Account Score > 75) = Tier 1 (quantitative)
Else If (Account Score > 50) = Tier 2
Else = Tier 3
This gives you speed (tier most accounts with simple rules) and precision (quantitative score for edge cases).
Your tiering model will have edge cases. Define how you handle them.
How do you tier existing customers for expansion/upsell?
Option A: Use same tiering criteria. A small existing customer with low upsell potential stays Tier 3.
Option B: Create separate expansion tiers. Existing customers use different criteria (existing contract value, expansion potential, account health, customer success score).
Recommendation: Separate tiers. Expansion tiering is different from new business tiering. You want different resources and motions.
An account is Tier 3 but has an active 200K deal.
Option A: Tier it as Tier 1 for the duration of the deal (6 months or until close/loss), then re-tier.
Option B: Keep it Tier 3 per the model, but assign an AE and give it AE-level resources during the deal.
Recommendation: Option A. Your tiering should reflect reality. An active deal is high-priority.
Sales leadership says an account should be Tier 1 because they have a strong relationship, even though the model says Tier 3.
Option A: Allow the override. Sales knows their deals.
Option B: Deny the override. The model is gospel.
Recommendation: Option A with governance. Allow overrides, but require documentation of the rationale. Track overrides and use them as feedback to refine the model. “If we’re regularly overriding for [characteristic], maybe that characteristic should be in the model.”
Your company sells to North America and EMEA. A Tier 1 account has a subsidiary in both regions.
Option A: Tier at the parent company level (one tier for the whole company).
Option B: Tier at the subsidiary level (each region has separate tier).
Recommendation: Tier at the parent level for campaign purposes (company-wide campaigns), but allow regional AEs to treat subsidiaries as separate opportunities if they’re buying independently.
Once you’ve tiered your accounts, quantify the outcome to validate.
Total accounts: 500
Tier 1: 40 accounts (8%)
Tier 2: 120 accounts (24%)
Tier 3: 340 accounts (68%)
3 AEs, each covering:
- Tier 1: 4 AEs (1 per 10 accounts)
- Tier 2: 2 AEs (1 per 60 accounts)
- Tier 3: 0 AEs (nurture + inbound only)
Total AEs needed: 6
Available: 3
Adjustment: Reallocate Tier 3 AE time to Tier 1/2. Or hire 1 more AE focused on Tier 2.
Pull your last 4 quarters of closed deals:
Closed deals:
- Tier 1: 12 deals, avg value 150K = 1.8M
- Tier 2: 8 deals, avg value 50K = 400K
- Tier 3: 4 deals, avg value 15K = 60K
Total: 24 deals, 2.26M
Tier 1 revenue contribution: 1.8M / 2.26M = 80%
Tier 2 revenue contribution: 400K / 2.26M = 18%
Tier 3 revenue contribution: 60K / 2.26M = 2%
This is healthy (Tier 1 is over-indexed). If Tier 1 was only 20% of revenue, your tiering is wrong.
Tiering isn’t static. Accounts move between tiers as factors change.
Every 90 days, re-run your tiering model:
Example changes:
Promoted to Tier 1:
- Acme Corp: Raised Series B funding, hired VP Sales (intent signal)
- XYZ Inc: Now has 2,000 employees (grew from 1,000)
Demoted to Tier 2:
- Company A: Lost major customer (less revenue potential)
- Company B: Competitor won the deal (lower win likelihood)
Don’t wait for quarterly re-tiering. Re-tier immediately if significant events occur:
If an account receives a funding round and your model flags it, move it to Tier 1 the same day.
Write down your tiering methodology. Share it with sales, marketing, and finance.
Tiering doc should include:
Share this doc with the entire GTM team. Update quarterly. Make it boring (not flashy) so people trust it.
Q: Should we share our tiering methodology with sales, or keep it secret?
A: Share it. Transparency builds trust. Sales will believe the model if they understand it. Lack of transparency breeds cynicism.
Q: What if sales disagrees with the tier a customer is placed in?
A: Document the disagreement and the rationale. If it’s a data error (you misclassified the company size), fix it. If it’s a judgment call (sales has a relationship you didn’t know about), allow an override and note it. Use overrides as feedback to improve the model.
Q: How do we handle ties (account meets criteria for two different tiers)?
A: Default to the lower tier (conservative). If an account is borderline Tier 1/2, call it Tier 2. As it proves itself, promote. This prevents over-investing in marginal accounts.
Q: Can we use the same tiering criteria as our sister company / competitor?
A: No. Your ICP, go-to-market, and resources are unique. Build your own model. That said, industry benchmarks are useful (e.g., “most SaaS companies tier the top 1-2% of accounts as Tier 1”). Use benchmarks as sanity check, not gospel.
Q: How do we adjust tiering if our product roadmap changes?
A: If a major feature ships and unlocks a new market, you might tier that market higher going forward. If a planned feature gets cancelled, you might tier an account lower. Tiering should be dynamic to strategy.
Q: Should we tier accounts differently by region (e.g., Tier 1 in US, Tier 2 in EMEA)?
A: You can, but it’s complex. Simpler: Global tiering (one tier per account), but resource allocation by region (US team focuses on US Tier 1, EMEA team focuses on EMEA Tier 1).
Q: What’s the ideal Tier 1 account list size?
A: 1 Tier 1 account per AE is a good rule of thumb. If you have 5 AEs, aim for 40-50 Tier 1 accounts. This gives each AE ~10 accounts to develop and 1-2 to actively close at any time.
Account tiering is the foundation of ABM resource allocation. Build a defensible methodology, document it, and execute against it. Re-tier quarterly. Let data guide your tier assignments, but don’t let data override common sense (if sales has a genuine relationship or market knowledge, use it).
Your tiering model won’t be perfect. But it’ll be better than no model, and it’ll improve every quarter as you measure outcomes.
Ready to tier your accounts?
Book a demo with Abmatic to see how account data helps you build and refine your tiering methodology.