Skip to content

Sales Blueprint

Safety checked

Account Intent Prioritizer

15Matt R.SVP, RevenueG2May 2026

Skip the noise and call only accounts actively buying. This workflow ranks your target list by real-time intent signals—so your SDRs focus on hot prospects today, not cold calls tomorrow.

1 File Included

  • pasted-prompt.md

    4 KB

What problem does this solve?

SDRs waste 60-70% of their time calling companies with zero near-term buying intent because outreach is sorted by company size or territory, not by real-time purchase signals. High-intent accounts get missed buried in static CRM lists, and reps have no way to know when a cold account starts actively researching.

How does it work?

Upload a target account list to the workflow. The agent queries G2's Model Context Protocol for live buyer intent data on each account, pulling intent scores (0-100), signal types (profile view, compare page, pricing page, category research), number of stakeholders engaged, and competitor research activity. The agent applies a prioritization model: intent score above 90 means multiple stakeholders actively evaluating (call today), 70-90 is active single-stakeholder research (call this week), below 70 is early awareness (nurture). The output is a ranked call sheet sorted by intent score with account name, intent score, signal type, competitor threats, and a tailored outreach angle for each account. Optional integration pushes the prioritized list back to Salesforce or HubSpot.

What's the biggest win?

Reps focus outreach exclusively on in-market accounts instead of cold lists. Accounts with intent scores above 70 are 3-5x more likely to accept a meeting. Competitive flags allow proactive counter-positioning in outreach. Eliminates wasted dials on zero-signal accounts.

What's required to run this?

Scoring model: Intent score 90+ = multiple stakeholders actively evaluating (call today); 70-90 = active single-stakeholder research (call this week); below 70 = early awareness (nurture, don't push). Competitor activity flags elevate priority regardless of score. Critical implementation notes: (1) Reps instinctively prioritize by company size or brand recognition — behavioral change requires explicit training that a 90-intent score at a 200-person company outweighs a 40-intent score at a Fortune 500. Recency of research activity matters far more than logo size. (2) Company name matching is error-prone across systems. Run a normalization pass on your account list before querying the G2 MCP — strip legal suffixes (.com, Inc., LLC), standardize capitalization, and resolve common aliases (e.g., 'Salesforce.com' → 'Salesforce'). Name formatting mismatches cause valid high-intent accounts to be dropped from results.

What are the constraints?

Requires access to G2 MCP server and live buyer intent data. Effectiveness depends on quality and recency of G2 signal data. Only works for accounts that are actively researching on G2 — accounts doing private evaluation won't appear in intent data.

Tools in this Blueprint

G2
Agentforce Sales (formerly Salesforce Sales Cloud) logo
Agentforce Sales (formerly Salesforce Sales Cloud)View on G2 ↗
4.4(25,876 reviews)
HubSpot Sales Hub logo
HubSpot Sales HubView on G2 ↗
4.4(13,936 reviews)

About This Blueprint

Industry
Computer Software
Sales

ICP-Filtered Outreach Lists from G2 Buyer Intent

Stop wasting rep time on weak intent signals and mismatched accounts. The workflow ranks ICP-fit buyers by readiness, finds the right contact, and supplies tailored outreach angles for the strongest opportunities.

ClaudeClaudeG2 Buyer Intent (G2 MCP Server)ZoomInfo (MCP)+3 more

Ishani D.

Account Manager at G2

1 Skill
Customer Experience

Answer pre-purchase questions to convert hesitant shoppers with AI

Shoppers get accurate answers about fit, compatibility, ingredients, and delivery even when your team is offline, so fewer leave before checkout. Conversation insights also reveal which product-page details could prevent the next unanswered question.

Yuma AIYuma AIClaudeClaudeShopify

Urska B.

GTM Lead at Yuma AI (YC W23)

1 Skill
Customer Experience

Find the root cause behind repeat support tickets with AI

Catch a few unusual tickets before a product or fulfillment issue turns into hundreds of refunds, chargebacks, and bad reviews. Cluster transcript evidence by SKU, order date, location, and carrier so operations can trace the cause and support can reach affected customers early.

Yuma AIYuma AIClaudeClaudeShopify

Urska B.

GTM Lead at Yuma AI (YC W23)