The Scenario
A sales engineer at a dev-tools startup got handed a 300-row prospect list on a Tuesday afternoon. The list came from a data vendor — domains in column A, company names in column B, nothing else. Her ICP is companies running AWS or GCP in their infrastructure, and she needs to get this down to a qualified shortlist before the Thursday pipeline review.
She's been through this before. Last quarter she spent a day manually checking tech stacks on BuiltWith, flagging rows in a column, and still missed a dozen because the data was stale. The VP of Sales has specifically asked her to stop spending Thursday mornings rebuilding the same filter from scratch.
The bad version:
- Pull tech stack data from BuiltWith or a similar tool, cross-reference it against the prospect list row by row
- Create a manual "ICP Match" column, evaluate each company's stack one by one against the AWS/GCP criteria
- Realize on Thursday morning that forty rows are still flagged as "Check Later" because the stack data was ambiguous or missing, and you're presenting in ninety minutes
The problem isn't the filter logic — that part takes thirty seconds to specify. The problem is that the data retrieval and scoring are separate manual steps that compound each other's errors.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It can call Bigpicture.io to retrieve technology stack data for each domain and apply your scoring logic in the same pass — no intermediate export, no second prompt, no manual flag column to maintain.
For each domain in column A, fetch the company's technology stack from Bigpicture.io and write it to column C. Then add a "Target" flag in column D for any company using AWS, GCP, or Azure in their infrastructure stack.
What You Get
- Column C: Full technology stack as returned by Bigpicture.io (comma-separated or structured list)
- Column D: "Target" for any company with AWS, GCP, or Azure in the stack; blank for companies that don't match
- Rows where Bigpicture.io returned no tech stack data get a "No Stack Data" note in column D so you know which ones to verify manually
The shortlist is ready to sort and filter. The pipeline review has real data behind it.
What If the Data Is Not Quite Ready
You want to score on a more specific stack — e.g., only companies using Kubernetes or Docker, not just any cloud provider
For each domain in column A, fetch the technology stack from Bigpicture.io and write it to column C. In column D, mark rows as "ICP Match" only if the stack includes Kubernetes, Docker, or Terraform. Leave column D blank for companies that don't match.
Some domains in column A are already enriched from a previous run — don't re-enrich them
For rows in column A where column C is blank, fetch the technology stack from Bigpicture.io and write it to column C. Apply the ICP scoring logic — flag "Target" in column D for any stack containing AWS, GCP, or Azure.
You want a second-tier filter — companies using Salesforce or HubSpot as CRM, on top of cloud infrastructure
For each domain in column A, fetch the technology stack from Bigpicture.io and write it to column C. In column D, mark rows as "Tier 1" if the stack includes AWS or GCP and also includes Salesforce or HubSpot. Mark rows as "Tier 2" if they have AWS or GCP but not a recognized CRM. Leave column D blank for all others.
Full kill chain: deduplicate, enrich stacks, score by ICP criteria, and sort by employee count
Remove duplicate domains from column A. For each unique domain, fetch the technology stack from Bigpicture.io and write it to column C. Fetch employee count and write it to column D. In column E, mark rows as "ICP Match" where the stack includes AWS, GCP, or Azure. Sort the ICP Match rows by column D (employee count) descending so the largest targets appear at the top.
One prompt handles the deduplication, the enrichment, the scoring, and the sort — no intermediate steps.
Try It
Open a Google Sheet with a prospect list and get the 7-day free trial of SheetXAI. Ask it to enrich each domain with Bigpicture.io tech stack data and apply your ICP criteria in one prompt — you'll have a scored, sortable shortlist in minutes instead of a morning. For name-to-domain resolution before enrichment, see the company name to domain matching spoke, or return to the Bigpicture.io hub overview.