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The deck we used to raise our seed funding

airbyte.io

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Re: The deck we used to raise our seed funding

#81
post #80

Earlier quoted context omitted.

To determine this you'd have to track how many companies raise funds and how much they raise (at what valuation) both inside and outside of YC. From my own view on this supported by quite a bit of data I would say that YC is as close as you're going to find to a stamp of approval in the start-up scene, it has a substantial effect on your chances to raise funds and on the amount you will raise when you do.

Actually, Airbyte is a pivot from a first product. And we struggled a lot to raise with the previous product, even though we were fresh out of YC. YC is an indicator but not enough by itself.

Yes, but you did raise. Now ask yourself if you would have raised this round without YC backing and the same product.

Time will tell if you will succeed, best of luck to you and your team.

But keep in mind that raising money is not success in itself.

Re: The deck we used to raise our seed funding

#82
post #80

Earlier quoted context omitted.

Actually, Airbyte is a pivot from a first product. And we struggled a lot to raise with the previous product, even though we were fresh out of YC. YC is an indicator but not enough by itself.

Yes, but you did raise. Now ask yourself if you would have raised this round without YC backing and the same product. Time will tell if you will succeed, best of luck to you and your team. But keep in mind that raising money is not success in itself.

Raising money is not a success indicator at all. We agree. Having your first paying customer is typically a much more important one :).

Re: The deck we used to raise our seed funding

#83
post #13

Interesting to see the competitive analysis with Fivetran in the article but then see almost identical copies of infographics used between their site and Fivetran's. Airbyte: https://airbyte.io/wp-content/uploads/2021/03/Airbyte-Seed-D... Fivetran: https://images.cms.fivetran.com/mgtdf72hs0mx/6qYtmEEotXqScar...

Shhh the investors don’t know that. > if can’t beat em join em.

Or don't care

Re: The deck we used to raise our seed funding

#85

One thing that’s not clear to me is why is there so much competition and crowding in “data massage” space. There is Snowflake, there are all kinds of ETL tools. The customer lists these startup posts have overlaps. Is it just Marketing departments inside these companies playing around with these tools or the CIOs cycling through the hottest startup on TechCrunch list ?

Coming from an ad agency background I’ve seen a lot of attempts at “unifying” various data sources from client’s analytics and sales data, agency tools, and third party data sets that are all in different formats, date ranges, and scopes. Warehousing that data might also require firewalling clients or teams for privacy or “competitive/conflict” reasons. These aren’t difficult problems to solve with a few knowledgeabl…

Ad agencies have neither the stomach nor the business model to support hiring devs at market rate.

Re: The deck we used to raise our seed funding

#86

I notice they use GitHub stars as a metric in the Appendix, supposedly to "insist that we hadn’t done a hard launch yet." I wonder how meaningful this metric is. Is 350 a lot of stars? A little? What am I supposed to take away from this?

It was more about showing the growth rate which was higher than all the other open-source projects related to data integration :)

Re: The deck we used to raise our seed funding

#88

One thing that’s not clear to me is why is there so much competition and crowding in “data massage” space. There is Snowflake, there are all kinds of ETL tools. The customer lists these startup posts have overlaps. Is it just Marketing departments inside these companies playing around with these tools or the CIOs cycling through the hottest startup on TechCrunch list ?

There is value to having all your data in one place and managing data connectors is generally not very fun. They also tend to be annoyingly brittle and it's very visible when they go down. That all makes for a perfect recipe to cause burnout in a small data team. Competent data engineers are also fairly difficult to hire right now.
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