Automatic parser of competitor reviews for online stores

Client's task:
The owner of an online store wanted to know which products sell best among competitors. Customer reviews are a direct indicator of demand: the more reviews there are and the fresher they are, the more actively the product sells. A tool was needed that collects this data automatically across all stores simultaneously.

Solution:
I developed an automated system based on n8n that parses all products and all reviews from a specified list of stores. The list is stored in Google Sheets, and the system automatically visits each site, determines which review system is used, and collects data through the corresponding API. The results are exported to a separate Google Sheets table, breaking down reviews by month. For each product, not only the total number is visible, but also the dynamics.

Result for the business:
The client sees which products are currently selling the most actively and directs the budget towards purchasing these items. Instead of spending weeks on manual monitoring of competitor stores, they receive ready-made analytics with one click and make decisions based on data rather than assumptions.

Figures:
- 10 competitor stores monitored
- ~75,000 products and ~190,000 reviews collected in one run
- Support for 4 review systems: Yotpo (v1 and v3), Reviews.io, Judge.me, Okendo
- Full data collection cycle - without human involvement

Stack:
n8n · Google Sheets · Yotpo API (v1 + v3) · Reviews.io API · Judge.me API · Okendo API · JavaScript Code Nodes · HTTP request