Content Blueprint
Safety checkedCategory Trend Report Builder
Cut content research from hours to minutes by analyzing live G2 reviews and buyer sentiment to discover authentic category trends, pain points, and content angles that resonate with your target audien
1 File Included
pasted-prompt.md
4 KB
What problem does this solve?
Content briefs take 2-4 hours to research manually, and most category content is generic rather than grounded in live buyer sentiment. Teams lack structured access to G2 review data for content strategy at scale.
How does it work?
User specifies a software category and optional parameters (time window, target audience). Claude connects to G2 MCP server and runs parallel queries for top products, trending review themes, pain points by segment, and competitor positioning. Claude synthesizes the raw data to extract feature themes with sentiment scores, emergent pain points, language patterns signaling buyer intent, and category shifts. Output is a structured content brief including category overview, top review themes, competitor snapshot, suggested content angles, and anonymized review quotes—all delivered in under 10 minutes.
What's the biggest win?
Cuts content research time from 3+ hours to under 10 minutes while producing briefs grounded in live buyer language rather than vendor marketing copy. Scales to any G2 category without additional headcount.
What's required to run this?
Claude connects via G2 Model Context Protocol (MCP) server. Parallel queries extract: top-reviewed products with rating breakdowns, trending review themes by sentiment, reviewer pain points by segment, competitor positioning language, and comparison page activity.
Two critical gotchas: First, G2 MCP requires the exact category taxonomy slug — passing a fuzzy name like 'sales tools' instead of the proper slug returns empty or irrelevant results. Confirm the correct slug before running the workflow (takes ~2 minutes). Second, Claude will occasionally fill data gaps with training knowledge and present it as G2 data if not explicitly constrained. Add this instruction to every prompt: 'Only cite data returned from the G2 MCP query. Do not infer or supplement with outside knowledge.' This single line makes output fully trustworthy and prevents hallucinated G2 data from appearing in the brief.
What are the constraints?
Depends on G2 data availability and review volume for the target category. Requires API/MCP access to G2 platform.
Tools in this Blueprint
About This Blueprint
- Industry
- Computer Software
More Blueprints to explore
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.
ClaudeG2 Buyer Intent (G2 MCP Server)ZoomInfo (MCP)+3 moreIshani D.
Account Manager at G2
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 AIClaudeShopifyUrska B.
GTM Lead at Yuma AI (YC W23)
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 AIClaudeShopifyUrska B.
GTM Lead at Yuma AI (YC W23)