Indeed, web clipper, like many aspects of Airtable suffer from very low operating ceilings. And despite the fact that I don’t really keep tabs on all things Airtable, I can quickly name a dozen critical features that are severely limited.
In my view, web clipping doesn’t even make the top twenty most critical things in the scope of clear-headed product management.
I don’t intend to lessen the importance of web clipping to you or any other user, but I do intend to call out the deep contrasts between poorly-implemented “features” that fall into the nice to have category and deeply dependent infrastructure requirements that have been ignored for more than half a decade.
This is the difference between features that help users in a narrow scope of activity – versus – features that help people help themselves which have a vastly broader and deep-reaching impact on the ability for users solve many data management challenges, the latter of which tend to be boundless.
Airtable does some things really, really well and they’ve captivated the attention and imagination of a large segment of underserved workers who need information management solutions that are both delightfully appealing and easy to use.
How did Airtable win these customers?
Not by making it easy to import data. To the contrary - Airtable’s data ingestion and importing capabilities are among the weakest in their segment. Certainly, this aspect of the product must be improved, but seamless flows of data into their platform is not in their wheelhouse. As such, I must ask -
Will more users come to Airtable because it has a great web clipper?
Will vastly more users come to Airtable because it is a great data management platform – AND STAY – because they can effortlessly solve complex data management problems with advanced formula methods such as Split()?
Across this forum, I can’t recall a single instance where a user has announced their departure from Airtable because it couldn’t clip data from the web. Yet, I see many such announcements from serious business users who cannot sustain their interest going forward because the product lacked essential infrastructures that make it possible to solve data manipulation objectives.