Codex checks paid search against CRM lead quality

kaancata uses Codex for paid-search account analysis, alongside Claude Code for copy and campaign messaging. The concrete recurring task is to pull search-term data through the Google Ads API, compare spend and recorded conversions with CRM lead quality, and produce negative-keyword candidates with reasons.

The workflow does not assume that an advertising conversion is a useful sales lead. Separate scripts collect search terms, campaign and ad-group spend, CRM outcomes, conversion actions and tracking checks. The agent analyses saved files and cites their rows or summaries. Another model reviews the findings, and the operator iterates before trusting them.

In a follow-up, the author clarifies that there is no universal search-term-to-individual-lead field. The matching context can include campaign, ad group, keyword, landing page and captured click identifiers, depending on tracking. That limits the precision of any proposed exclusion.

Write access is staged with a change log and a reason for each proposed negative, budget, bid or conversion change. The operator still decides what a good lead means and what should remain untouched. The source reports an actual operating process but does not publish a named excluded term or independently measured return improvement. The useful detail is grounding recommendations in saved account evidence, with the join’s limitations visible, instead of treating a confident narrative as an audit.

Prompt
Suggested prompt (written by Agents In Use, not the author's)

Source: Reddit · kaancata