Step-by-Step Tutorial 🗂️

🔹 Step 1: Scraping Reviews with Apify

I used an Apify actor (`nikita-sviridenko/trustpilot-reviews-scraper`) to scrape customer reviews or testimonials from websites, online stores, or review platforms.

• Apify fetches reviews automatically and stores them in a dataset or pushes them via a webhook.
• Apify’s output is a structured JSON with review text and other metadata.
• Optionally, you can schedule the scraping actor to run regularly to keep your data fresh.

🔹 Step 2: Create a New Zap in Zapier

1. Log in to your Zapier account. Click “Create Zap”.
2. Add a Schedule by Zapier step and have it run how often you want. For this, I set it to every day at 10 AM.

🔹 Step 3: Trigger Zapier Workflow to Process Stored Reviews

The first action is a Zapier Storage — Retrieve Value step that fetches the stored JSON review data from Zapier Storage.

*I parse this JSON to extract individual reviews for processing.*

🔹 Step 4: Parse and Prepare Each Review

Next, you add a Code by Zapier step (I used Python).

In this step, you: Parse the JSON string retrieved from Storage, Extract individual values, Format each review as needed for the API call, and Return a random review to loop over in the next steps.

Python Code Used:

import json
import random

raw = input_data['reviews']

# Try to decode once
try:
    decoded_once = json.loads(raw)
except Exception as e:
    raise Exception(f"Failed to decode JSON first time: {e}")

# If the result is a string, decode again (double-encoded JSON)
if isinstance(decoded_once, str):
    try:
        data = json.loads(decoded_once)
    except Exception as e:
        raise Exception(f"Failed to decode JSON second time: {e}")
else:
    data = decoded_once

review = random.choice(data)
output = {
    'text': review.get('reviewBody', ''),
    'author': review.get('authorName', ''),
    'date': review.get('datePublished', '')
}

🔹 Step 5: Webhooks by Zapier — Send Each Review to Flask API

Use Webhooks by Zapier (POST) to send each review to your custom Flask API endpoint (exposed via Ngrok).

• The webhook payload includes the review text in JSON format.
• Your Flask API runs the Hugging Face model and responds with generated ad copy (title, description, CTA).
• Zapier captures the JSON response from your API.

*You can see what the AI model sent back in the test step: Title, Description, and CTA for our Ad.*

🔹 Step 6: Google Sheets — Save Generated Ad Copy

Finally, the Zap inserts a new row into Google Sheets for each review processed.

• Each row contains: Original review text, Generated Title, Generated Description, Generated Call To Action (CTA).
• This creates an organized log of all reviews and their AI-generated ad copy, easy to review or share.