The Scenario
Your competitive intelligence brief arrives every Monday morning from the VP of Strategy: 100 new competitor press releases scraped over the weekend, all sitting in column A of the 'Press Releases' sheet in your Excel workbook. She wants a populated dashboard by noon — entity mentions and topic categories filled in, ready to filter by company name or subject area. It's the third Monday in a row this process has taken you most of the morning.
The bad version:
- Write a Python script that reads column A row by row, calls the TextRazor API with both entities and topics extractors enabled, parses two separate nested arrays from the response, and writes six output fields across columns B through G.
- Debug the script when it crashes at row 47 because one press release has an encoding issue and the API returns an unexpected character error.
- Run the script again, wait for the 100 API calls to complete sequentially, and then check that the column alignment survived rows where the entity array came back empty.
The dashboard is waiting. The VP's sync is at noon. You're debugging infrastructure instead of reading the competitive data.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It reads the press releases, understands what you're analyzing, and through its built-in TextRazor integration can run full multi-extractor analysis — entities and topic classification together — across every row in one ask.
Run full TextRazor analysis (entities + topic classification) on each text in column A of the 'Press Releases' sheet and write extracted entities into column B and the top topic category into column C.
What You Get
- Column B receives the top extracted entities from each press release, comma-separated and ranked by relevance score.
- Column C receives the top IAB topic category for that text.
- Rows where the entity array is empty get a noted placeholder in column B rather than a blank that breaks downstream filters.
- The output lands in consistent column positions across all 100 rows, ready to pivot or filter without reformatting.
What If the Data Is Not Quite Ready
You need entity types and category scores too
Analyze all texts in column A of the 'Press Releases' sheet with TextRazor using entity extraction and IAB classification, then write the top entity, its type, the top category, and relevance scores into columns B through E.
Some press releases are in a mix of English and another language
For each text in column A of the 'Press Releases' sheet, detect the language before sending to TextRazor analysis. Process only English texts with full entity and topic extraction, writing results into columns B and C. Flag non-English rows in column D.
The press releases are split across two worksheets
Run full TextRazor analysis on the texts in column A of the 'Q1 Competitors' sheet and column A of the 'Q2 Competitors' sheet. Write entities into column B and top topic category into column C on each respective sheet.
Full kill chain: clean, analyze, summarize
For each press release in column A of the 'Press Releases' sheet, remove boilerplate legal disclaimers (any text starting with "Safe Harbor" or "Forward-Looking Statements"), run TextRazor full analysis, write the top entity and its type into columns B and C and the top topic category into column D, then add a 'Competitive Summary' sheet with a frequency table of the top 20 mentioned organizations and the most common topic categories.
Handling the disclaimer removal and the analysis in one prompt means you get clean output the first time, not a second scrubbing pass.
Try It
Get the 7-day free trial of SheetXAI and open the Excel workbook where your weekly press release batch lands. Ask SheetXAI to run full TextRazor entity and topic analysis and write the results into the columns your dashboard is reading from. The entity extraction spoke covers the basics if you only need entity data this week.