Data challenges

Challenges
Network effect
Problem description:
On the one hand, we want our data to be reusable between different retailers. This is why allowing them to create their own questions might be a bad idea, since in this case the data will be messy. Moreover, retailers may create bad quizzes which spoil customer experience, and this might negatively impact our brand.
On the other hand, prohibiting retailers to set their own questions might have a negative impact on sales, because retailers likely want to have a freedom in their actions.
Question:
How can we solve this dilemma? Ease of sales + the reusing of data between different retailers + great customer experience?
Thoughts:
TBD
Product tagging
Problem description:
We need to ease customer onboarding as much as possible. Product annotation might be the most time-consuming part of it.
Question:
It would be great if we could come up with a product tagging solution based on ML

Thoughts:
TBD
Not go into this space rn.
0-1000 skus =manual
algos for 1k+ SKUs
Product tagging part of item: e.g. charge per sku 20c per sku
An additional revenue stream -
Need-based attributes
Problem description:
Some filters are need-based
Question:
How can we understand the relevance to a need-based filter based on product features?
Thoughts:
TBD
Saagar TBC
Data collection
Problem description:
We’ll need to create a user-centric recommendation system. However, it might be hard because of:
1) 3rd-party cookie-death - we might not have a good way to identify users between different sites
2) not enough relevant data/messy data
Question:
1) How could we tackle a 3rd-party-cokkie death problem?
2)What data do we need to use in our recommender system?
Thoughts:
TBD

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