The Scenario
Your sales ops lead is standing over your shoulder — figuratively, via Slack — asking why the lead quality from last month's campaign looks off. You pull up the 1,500-row leads sheet. Every row has a form-submission IP in column G. Some of those IPs are from real people filling out the form. Some are almost certainly bots coming from hosting ranges.
Nobody checked before the leads went to the dialer.
The bad version:
- Look up five IPs manually on ipdata.co to spot-check the ASN type. Two come back as "hosting." Three look residential.
- Try to write a formula that calls an external API — discover Sheets does not work that way.
- Consider building a script. Realize you have 1,500 rows, no Python environment set up, and a sales team asking for the cleaned list by tomorrow morning.
The budget for this campaign did not include a data cleaning sprint. But the budget for wasted dialer minutes is even smaller.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the leads data, calls ipdata.co for each IP, and writes company type and threat flags into the columns you specify — then labels the likely-bot rows so you can filter them out before passing the list to sales.
For each IP in column G, fetch the ipdata.co company type and ASN type and write them to columns H and I, then flag any row where the type is "hosting" or "datacenter" as LIKELY BOT in column J.
What You Get
- Column H: company type string from ipdata.co (e.g., "hosting," "business," "isp," "education")
- Column I: ASN type string (e.g., "hosting," "isp," "business")
- Column J: "LIKELY BOT" label on any row where either column H or I indicates a datacenter or hosting network
- Residential and ISP rows left unlabeled so you can filter to clean leads in one step
What If the Data Is Not Quite Ready
The IP column has blank rows mixed in from conditional form logic
For each non-blank IP in column G, fetch ipdata.co company type and ASN type and write to columns H and I. Skip blank rows and leave H and I empty for those rows. Flag LIKELY BOT in column J where type is hosting or datacenter.
You also need Tor and proxy flags for compliance reasons
Run threat detection on all IPs in column G using ipdata.co. Write Tor status to column H, proxy status to column I, datacenter flag to column J, and known-attacker flag to column K. In column L, write FLAGGED for any row with at least one true value.
Leads came from two separate form sheets that need to be merged first
Combine the IP addresses from the Form-A tab column G and Form-B tab column G into a single deduplicated list on a new sheet called Combined-Leads. Then enrich each IP with ipdata.co company type and write LIKELY BOT in column C for hosting or datacenter rows.
Kill-chain: deduplicate leads, enrich, flag bots, and output a clean list
Remove duplicate email addresses from column B of the Leads tab. Then for each unique lead, fetch ipdata.co company type and ASN type from the IP in column G and write to columns H and I. Flag LIKELY BOT in column J for hosting or datacenter results. Finally, copy all non-flagged rows to a new tab called Clean-Leads.
One prompt handles the deduplication, the enrichment, the bot flagging, and the clean-list extraction.
Try It
Get the 7-day free trial of SheetXAI and open your leads sheet, then ask SheetXAI to screen the IP column for datacenter traffic using ipdata.co. See also bulk enriching suspicious login IPs or the ipdata.co integration overview.