Using content based recommendation is interesting but requires a constant scraping for more data. Plus the whole cost of curating the dataset and guaranteeing data quality can be extra challenging. How are you getting around these problems?
Also, your approach with A/B Test is interesting, but how would you do it for smaller shops? Wouldn't it take too long to give appropriate results? Or are you using a Bayesian Test Methodology?
Yup, you're right! We have very significant infrastructure to have stable and scalable scraping that ensures the best data quality. This is one of the things we spend the most time on.
Thanks! Yes, in order for shops to trust the A/B-test results we tend to use Google Optimize, which use Bayesian inference.
Using content based recommendation is interesting but requires a constant scraping for more data. Plus the whole cost of curating the dataset and guaranteeing data quality can be extra challenging. How are you getting around these problems?
Also, your approach with A/B Test is interesting, but how would you do it for smaller shops? Wouldn't it take too long to give appropriate results? Or are you using a Bayesian Test Methodology?