…
)”. So we need to include those block comments? Probably yes. They gave example:…
. Also headings maybe…
. We need to produce a blog post with title line separate, then HTML content. We must not use placeholders. Must be complete, actionable content. We need to promote e-book at end with given paragraph. We need to count words. Let’s draft about 470 words. We need to include the steps and details. Let’s outline: Title line: “Title: Automating Side‑by‑Side Cancellation Policy Comparisons with AI for Solo Event Planners” Then content: – Introduction paragraph. – Step 1: Define comparison fields (list fields). – Step 2: Build extraction prompt (give example prompt). – Step 3: Use side‑by‑side template (show template with columns for vendor, caterer, photographer, venue). – Include bullet list of fields with examples. – Mention risk detection prompt. – Draft client summary. – Prepare contracts. – Highlight conflicting deadline mismatches with example table. – Conclude with benefits. – Promote e-book. We need to embed HTML with WP block comments. Let’s craft. We need to count words. Let’s write then count. I’ll draft in plain text then add HTML tags. We’ll need to count words in the final output (including title line? Probably yes). The instruction: article MUST be between 450-500 words. Count your words before finalizing. Likely includes title line and everything. We’ll count. Let’s write content then count. I’ll write:Solo event planners juggle multiple vendor contracts, and comparing cancellation policies manually is time‑consuming and error‑prone. AI can extract, normalize, and present these clauses side‑by‑side, letting you spot risks and negotiate better terms in minutes.
Step 1: Define the Comparison Fields
Start by listing the exact data points you need from each contract. Use these fields consistently:
- Cancellation by vendor (refund or penalty if they cancel)
- Date‑change or rescheduling fees (flat fee, percentage, allowed once)
- Deposit forfeiture terms (non‑refundable, partially refundable)
- Exceptions (ability to sell, transfer, or sublet the contract)
- Force majeure definition (acts of God, COVID‑19, supplier bankruptcy)
- Notice method (email, certified mail, deadline time zone)
- Refund percentage by time window (e.g., 100% if cancelled 90+ days, 50% 60‑89 days, 0% under 60 days)
Step 2: Build an Extraction Prompt for Your AI
Feed the AI a clear prompt that tells it where to look and what to return. Example:
Extract from each vendor contract the following items and output them in JSON format: - cancellation_by_vendor (refund amount or penalty) - date_change_fee (amount or %) - deposit_forfeiture (non‑refundable/partial) - transfer_allowed (yes/no with conditions) - force_majeure_clause (text summary) - notice_method (medium and deadline) - refund_by_window (percent for 90+, 60‑89, <60 days)
Adjust the wording to match your AI tool’s syntax, but keep the field names identical to those in Step 1.
Step 3: Use a Side‑by‑Side Template
Create a simple table where each column is a vendor and each row is a field. Fill it with the AI‑extracted data.
| Field | Caterer | Photographer | Venue | |---|---|---|---| | Cancellation by vendor | Full refund up to 60 days, then 50% to 30 days, 0% after | Full refund if cancelled 90 days out, then 0% | 100% refund if cancelled 180 days out, sliding to 0% at 60 days | | Deposit non‑refundable? | No (pay‑as‑you‑go) | Yes – $1,000 deposit | Yes – 50% deposit | | Refund % by window | 100% ≤60 days, 50% 60‑89, 0% <30 | 100% ≥90 days, 0% <90 | 100% ≥180 days, 50% 120‑179, 0% <60 | | Date‑change fee | None | $200 flat | 10% of total | | Transfer allowed | Yes, with notice | No | Yes, subject to venue approval | | Force majeure | Includes pandemic & supplier bankruptcy | Includes natural disasters | Includes acts of God, not bankruptcy | | Notice method | Email, 5 pm EST | Certified mail, 30 days | Email, 12 pm GMT |
The table makes it easy to see where policies diverge.
Activate Risk Detection
Run a “gotcha” prompt that asks the AI to flag conflicts, missing clauses, or hidden costs.
Identify any mismatches in notice deadlines, conflicting refund percentages, or absent force‑majeure language across the contracts above.
The AI might highlight, for example, that the caterer requires 60‑day notice while the venue needs 120‑day notice for the same event date.
Draft Client Summary
Ask the AI to produce a plain‑English report that summarizes the comparison, notes risks, and recommends actions (e.g., negotiate a longer notice window with the caterer or request a refundable deposit from the photographer).
Prepare Your Contracts
Upload all vendor agreements (PDF or scanned) into your AI workbench, run the extraction prompt, populate the side‑by‑side table, activate risk detection, and generate the client summary. Repeat the process whenever a new vendor is added.
For a comprehensive guide with detailed workflows, templates, and additional strategies, see my e-book: AI for Solo Event Planners: How to Automate Vendor Contract Comparison and Negotiation Drafting.
Now we need to count words. Let’s count manually. I’ll copy the text and count words. Title line: “Title: Automating Side‑by‑Side Cancellation Policy Comparisons with AI for Solo Event Planners” Count words: Title: (1) Automating(2) Side‑by‑Side(3) Cancellation(4) Policy(5) Comparisons(6) with(7) AI(8) for(9) Solo(10) Event(11) Planners(12). So 12 words. Now we need to count all words in the HTML content, including inside tags? Usually words are the visible text. We’ll count visible words, ignoring HTML tags and comments. But the instruction likely expects counting words in the article content (visible). Safer to count visible words only. Let’s extract visible text: Paragraph after title: “Solo event planners juggle multiple vendor contracts, and comparing cancellation policies manually is time‑consuming and error‑prone. AI can extract, normalize, and present these clauses side‑by‑side, letting you spot risks and negotiate better terms in minutes.” Let’s count. Sentence1: Solo(1) event2 planners3 juggle4 multiple5 vendor6 contracts,7 and8 comparing9 cancellation10 policies11 manually12 is13 time‑consuming14 and15 error‑prone16. Sentence2: AI17 can18 extract,19 normalize,20 and21 present22 these23 clauses24 side‑by‑side,25 letting26 you27 spot28 risks29 and30 negotiate31 better32 terms33 in34 minutes35. So 35 words. Next heading: “Step 1: Define the Comparison Fields” (visible). Count: Step1:1 Define2 the3 Comparison4 Fields5. That’s 5 words? Actually “Step” counts as word, “1:” maybe considered “1:” as a token but we count as word? Usually “1:” counts as a word? We’ll count “Step” and “1:” as separate? Safer to treat “Step” as word, “1:” as word? Might be ambiguous. Let’s count as “Step”(1) “1:”(2) “Define”(3) “the”(4) “Comparison”(5) “Fields”(6). So 6 words. Next paragraph: “Start by listing the exact data points you need from each contract. Use these fields consistently:” Count: Start1 by2 listing3 the4 exact5 data6 points7 you8 need9 from10 each11 contract.12 Use13 these14 fields15 consistently16. => 16 words. Next list items (visible). We’ll count each list item text. List: – Cancellation by vendor (refund or penalty if they cancel) – Date‑change or rescheduling fees (flat fee, percentage, allowed once) – Deposit forfeiture terms (non‑refundable, partially refundable) – Exceptions (ability to sell, transfer, or sublet the contract) – Force majeure definition (acts of God, COVID‑19, supplier bankruptcy) – Notice method (email, certified mail, deadline time zone) – Refund percentage by time window (e.g., 100% if cancelled 90+ days, 50% 60‑89 days, 0% under 60 days) Now count each. Item1: Cancellation1 by2 vendor3 (refund4 or5 penalty