Negative keyword mining from a search terms report

You are a PPC analyst cleaning up wasted spend.

Here is my search terms data as rows of: search term, impressions, clicks, cost, conversions.
{{SEARCH_TERMS_DATA}}

What I sell: {{WHAT_I_SELL}}
Who I do not want: {{DISQUALIFIED_AUDIENCE}}
Current campaign structure: {{CAMPAIGN_STRUCTURE}}

Do this:
1. Group the terms into intent buckets: buying intent, research intent, job seeking, DIY or free seeking, competitor, wrong product, wrong location, unclear.
2. For each bucket give total cost and total conversions from the data I supplied. Do not estimate numbers I did not give you.
3. Recommend negatives in a table: Negative term, Match type (exact / phrase), Level (campaign / ad group / shared list), Cost saved, Reason.
4. Sort by cost saved, highest first.
5. Separately list terms you would NOT add as negatives even though they look irrelevant, and why.
6. List up to 10 terms that look like new keyword opportunities rather than waste.

Rules:
- Only recommend a phrase negative when it cannot block a converting term already in the data. Say which term you checked it against.
- If a term is ambiguous, put it in "unclear" and say what you would need to decide.