- Researching evidence via AI + web search...
- Validating URLs & checking domains...
- Verifying page content matches signals...
- Computing ICP fit score...
- Running AI scoring model...
CSV should have columns: company, website (optional: annual_revenue, industry, number_of_partners)
Drag & drop a CSV file, or
Connect your Salesforce org to import Accounts.
Raw SOQL WHERE clause. Overrides dropdowns above when filled in.
| Company | ICP Fit | SFDC Tier | Tier Conf. | Signals | Status |
|---|
| Company | ICP Fit | SFDC Tier | Score | Signals |
|---|
Most frequently detected competitors across all analyzed accounts.
Search, filter, and push channel contacts to Amplemarket lead lists or sequences.
How often each signal is found across all analyzed accounts.
ICP Evidence Analyzer — FAQ
Everything your GTM team needs to know about how the tool works, what the signals mean, and how to act on the results.
The ICP Evidence Analyzer is ChannelScaler's proprietary tool that automatically evaluates whether a company runs a structured channel partner program. It scans the public web for 14 specific evidence signals — things like partner program guides, deal registration pages, MDF programs, and tiering structures — then scores the company as a Strong Fit, Likely Fit, Moderate Fit, Emerging, or No Fit.
This replaces hours of manual research per account. Instead of an AE spending 30-60 minutes Googling a prospect's partner program, the tool delivers a scored, evidence-backed assessment in under a minute.
Enter a company website and click Analyze. Results appear in ~30-60 seconds with the ICP fit score, all 14 signals, and evidence URLs. Push results to Salesforce with one click.
Switch to Multi mode on the Single Lookup tab. Paste up to 10 websites (one per line) and analyze them all at once. Results are shown side-by-side.
Upload a CSV file on the Batch tab with columns for company and website. The tool processes them in the background via a queue. Download results as CSV when done.
Connect Salesforce and use the built-in filters (Owner, CSM, Industry, Tier, ICP Score, Last Analyzed) to pull accounts. Preview and select which ones to analyze before running.
After analysis, push results to SF individually or in bulk. The tool searches for matching Accounts by website/name. Evidence URLs, YN fields, ICP Score, and Last Analyzed timestamp are all written.
Re-run any completed batch with fresh data (cache busted). Use the "Re-analyze All" button on batch results to get updated scores as companies evolve their channel programs.
The Insights tab shows ICP tier distribution, top accounts by score, competitor landscape across your analyzed accounts, and signal coverage heatmap showing which signals are found most/least often.
Download batch results as CSV with company, ICP fit, signal score, signals found, all 14 evidence URLs, competitors detected, strategic alliances, and tier reason. Ready for leadership reporting.
When importing from Salesforce, you can narrow your account list using these filters. All filters combine with AND logic. Use Advanced SOQL for custom queries.
Search by company name using LIKE matching.
Searchable dropdown, multi-select. Filters by OwnerId.
Searchable dropdown, multi-select. Filters by CSM_Owner__c.
Standard picklist and checkbox filters for common Account fields.
Comma-separated state codes (e.g. CA, NY, TX).
Filter by score range: Not Yet Scored, Below 20/40/60, Above 40/60/80.
Filter by Last_ChatGPT_Run__c: Never Analyzed, Not in Last 7/30/90 Days.
Raw WHERE clause override for power users. Overrides all dropdown filters when filled in.
The analyzer looks for 14 specific signals that indicate a company runs a structured channel partner program. These are grouped into four categories.
A published guide or overview that explains the company's partner program structure, benefits, requirements, and tiers.
Example: cisco.com/partners/program-guide
A dedicated portal or PRM (Partner Relationship Management) system where partners log in to access resources, register deals, and manage their relationship.
Example: partners.microsoft.com
A formal process for partners to register sales opportunities to receive deal protection and priority.
A tier or level system (e.g., Gold/Silver/Bronze, Premier/Select) that differentiates partner benefits based on performance or certification.
Market Development Funds — co-marketing budgets the vendor allocates to partners for demand generation activities.
Financial incentive programs like volume rebates, SPIFs, or performance bonuses for partners.
Structured training programs, certifications, or enablement resources for partners (e.g., learning portals, partner university).
A defined onboarding process for new partners — application forms, welcome kits, onboarding portals, or partner signup pages.
Dedicated channel chief, VP of Partnerships, or Channel team leadership roles. Searched via public Google/LinkedIn/ZoomInfo lookups for named executives.
Mentions in CRN (Computer Reseller News) Channel Chiefs, Partner Program Guide, or annual lists.
Evidence of structured joint business planning with partners (QBRs, planning templates, joint GTM).
Partner award programs, partner of the year, or marketplace listings for partner integrations.
A public-facing partner directory or "Find a Partner" tool on the company's website.
Evidence of working with distributors (e.g., Ingram Micro, TD SYNNEX, Arrow) for two-tier channel distribution.
The ICP fit score is determined by which categories of signals are present, not just how many total signals are found. Foundation signals carry the most weight.
| Fit Level | Rule | What It Means |
|---|---|---|
| Strong Fit | Foundation + Mechanics + Investment all present | Full-scale structured program. Prioritize for outreach. |
| Likely Fit | Foundation + one of (Mechanics OR Investment) | Strong program indicators. High-confidence prospect. |
| Moderate Fit | Foundation alone, OR Mechanics + Investment (no Foundation) | Some program structure in place. Worth investigating. |
| Emerging | At least 1 signal found but doesn't meet above thresholds | Early-stage indicators. Nurture or revisit later. |
| No Fit | Zero signals found | No evidence of a channel program. Deprioritize. |
The Tier Confidence percentage is calculated as: (signals found / 14 total signals) × 100. For example, if 8 of 14 signals are found, the confidence is 57%. This gives a granular view of how much evidence was discovered, independent of the category-based fit level.
The numeric ICP Score combines weighted signal scoring (0–90 max) with firmographic scoring (0–20 max). The theoretical maximum is 110, but the final score is capped at 100 using MIN(signal + firmographic, 100). This intentional overlap means strong signal scores AND strong firmographics both contribute meaningfully — a company doesn't need a perfect 90 on signals to reach 100 if their firmographics are solid.
| Category | Signals | Pts Each | Max |
|---|---|---|---|
| Foundation | Partner Program Guide, Partner Portal/PRM | 10 | 20 |
| Mechanics | Deal Registration, Tiering | 8 | 16 |
| Investment | MDF, Rebates, Training, Onboarding | 6 | 24 |
| Additional | CRN, Locator, Leadership, Tier2 Dist, JBP, Awards | 5 | 30 |
| Signal Total | 90 | ||
| + Firmographic Score (Revenue + Channel Contacts) | 20 | ||
| ICP Score = MIN(Signal + Firmographic, 100) | 100 | ||
When the analyzer runs from Salesforce (or via the "Push to Salesforce" feature), these fields are updated on the Account record.
ICP_Fit__c — Yes or No (binary)ICP_Fit_Score__c — Weighted signal score (0-90)ICP_Tier_Confidence__c — 0-100 percentageICP_Tier_Reason__c — Human-readable explanationLast_ChatGPT_Run__c — Timestamp of last analysis
[Signal]_Evidence__c — Evidence URL[Signal]_YN__c — "Yes" or "Unclear"
| Signal | Evidence URL Field | YN Field |
|---|---|---|
| Channel Leadership | Channel_Leadership_Evidence__c | Channel_Leadership_YN__c |
| CRN Recognition | CRN_Recognition_Evidence__c | CRN_Recognition_YN__c |
| Deal Registration | Deal_Registration_Evidence__c | Deal_Registration_YN__c |
| Joint Business Planning | Joint_Business_Planning_Evidence__c | Joint_Business_Planning_YN__c |
| MDF Program | MDF_Program_Evidence__c | MDF_Program_YN__c |
| Partner Awards / Marketplaces | Partner_Awards_Marketplaces_Evidence__c | Partner_Awards_Or_Marketplaces_YN__c |
| Partner Locator | Partner_Locator_Evidence__c | Partner_Locator_YN__c |
| Partner Onboarding | Partner_Onboarding_Evidence__c | Onboarding_YN__c |
| Partner Portal / PRM | Partner_Portal_PRM_Evidence_URL__c | Partner_Portal_PRM_YN__c |
| Partner Program Guide | Partner_Program_Guide_Evidence__c | Partner_Program_Formal_Guide_YN__c |
| Rebates & Incentives | Rebates_Incentives_Evidence__c | Rebate_Incentives_YN__c |
| Tier 2 Distribution | Tier2_Distribution_Evidence__c | Tier2_Distribution_YN__c |
| Tiering / Levels | Tiering_Evidence__c | Tiering_YN__c |
| Training & Enablement | Training_Enablement_Evidence__c | Training_Enablement_YN__c |
Mechanics = Deal Registration OR Tiering
Investment = MDF OR Rebates OR Training OR Onboarding
Strong Fit: Foundation + Mechanics + Investment
Likely Fit: Foundation + (Mechanics OR Investment)
Moderate Fit: Foundation alone, OR Mechanics + Investment
Emerging: Any signal but doesn't meet above
No Fit: Zero signals
ICP_Fit__c — Yes / NoICP_Tier_Confidence__c — 0-100%ICP_Tier_Reason__c — Full explanationLast_ChatGPT_Run__c — Timestamp
2. Click the "Run ICP Analysis" button
3. The Apex Queueable fires, calls the analyzer
4. Results write back to the Account in ~60s
5. Check the History tab here for a log
Scoring Model Tuning
Adjust signal weights and preview how changes affect ICP fit distribution before committing. Re-score existing results without re-running the AI.
Points awarded when evidence is found for each signal. Higher weight = more impact on signal score.
See how your weight changes would shift ICP fit distribution before applying.
Signal Weights determine how many points each evidence signal contributes to the total signal score (0-90 range by default).
ICP Fit Tiers are determined by category rules: Foundation + Mechanics + Investment = Strong Fit, Foundation + one other = Likely Fit, etc.
Preview shows how your changes would redistribute accounts across tiers without modifying any data.
Re-Score recalculates ICP fit for all completed results using the saved config. It does NOT re-run AI evidence resolution — only the scoring math changes. Use "Push to Salesforce" to sync updated scores to SFDC.