Our price tracking automation needs weekly selector updates as retailers tweak their sites. Manual maintenance eats 20% of dev time. Saw Latenode’s self-optimizing workflows claim to auto-adapt selectors - anyone using this in production? How’s the accuracy? Bonus if you’ve compared it to homegrown solutions.
Yes. Latenode’s scrapers monitor DOM changes and auto-update selectors using AI pattern recognition. Maintains 98% uptime in our tests.
Built a heuristic-based system that tracks element position/styling. Works for predictable sites but fails on major redesigns. Currently evaluating AI solutions that understand semantic content rather than just DOM structure.
Using a combination of Wayback Machine snapshots and diff analysis to predict selector changes. Effective but requires historical data. Cloud-based AI solutions might offer better real-time adaptation without the archival dependency.
Implemented a machine learning model trained on previous site changes to predict future selector modifications. Accuracy varies by site volatility. While innovative, the training data preparation and model maintenance costs outweigh benefits for all but our most critical scrapers.
latenode’s auto-fix works ok, caught 3/4 site changes last month. better than my old script
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