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As someone running a data startup, this is the first guide that really made me nod my head, and say yes, yes, yes! All the other SaaS articles felt like they we

As someone running a data startup, this is the first guide that really made me nod my head, and say yes, yes, yes! All the other SaaS articles felt like they weren’t talking to me or understood the problems that come with trying to sell a data product. For instance, the idea of building a MVP in 3 months with a data product is laughable.

go_ruby 7y ago
As the CTO of a DaaS startup in stealth mode working on our MVP, expect to take a year or more. We also offer SaaS that centralizes workflow around using the data, enterprise customers expect a level of polish and reliability that is not expected from the next facebook/airbnb clone, desk procedures, train the trainer programs and other ISO processes can't be revamped every single release. Keep fighting the good fight.
mNovak 7y ago
Curious to know how DaaS startups decide what to charge for their dataset?
- cosmie 7y ago
  Not a DaaS startup, but I've managed millions of dollars worth of data acquisition and sales before. Having seen both the selling and acquisition side of the table, the only concrete advice I can give you is to pay handsomely for experienced sales staff. There is absolutely no rhyme or reason to data pricing, and no matter what you do you will invariably price out specific market segments while underpricing for other market segments. And as the article mentioned, there are a lot of potential licensing and usage covenants involved in data sales, which are all possible factors in pricing. Without a good sales team to do client and market discovery, it's really hard to understand what to settle on for norms as far as both pricing and licensing go. On the flip side of that: if you're ever purchasing data at any amount of volume, ignore listed pricing. It's absolutely fungible, and well worth the tedious dance of traditional sales. In addition to better financial terms, you can usually get adjustments to the licensing and usage covenants to better accommodate your use case. Doubly so if your use case is nonstandard for that vendor - plenty of data-oriented services are tailored for specific industries and uses, and their pricing sheets and tiers are designed around the use cases and marginal value of the data within that industry. When sourcing data, I could get pretty incredibly deals from these companies, as their sales teams basically used the transaction as a form of market discovery and saw the relationship as a way to feel out a particular market segment they hadn't been going after previously.
johnrgrace 7y ago
As someone in a fortune 50 company working in a data internal startup this guide has been one of the first that really gets the unique aspects of data.

go_ruby 7y ago

As the CTO of a DaaS startup in stealth mode working on our MVP, expect to take a year or more. We also offer SaaS that centralizes workflow around using the data, enterprise customers expect a level of polish and reliability that is not expected from the next facebook/airbnb clone, desk procedures, train the trainer programs and other ISO processes can't be revamped every single release. Keep fighting the good fight.

mNovak 7y ago

Curious to know how DaaS startups decide what to charge for their dataset?

cosmie 7y ago
Not a DaaS startup, but I've managed millions of dollars worth of data acquisition and sales before. Having seen both the selling and acquisition side of the table, the only concrete advice I can give you is to pay handsomely for experienced sales staff. There is absolutely no rhyme or reason to data pricing, and no matter what you do you will invariably price out specific market segments while underpricing for other market segments. And as the article mentioned, there are a lot of potential licensing and usage covenants involved in data sales, which are all possible factors in pricing. Without a good sales team to do client and market discovery, it's really hard to understand what to settle on for norms as far as both pricing and licensing go. On the flip side of that: if you're ever purchasing data at any amount of volume, ignore listed pricing. It's absolutely fungible, and well worth the tedious dance of traditional sales. In addition to better financial terms, you can usually get adjustments to the licensing and usage covenants to better accommodate your use case. Doubly so if your use case is nonstandard for that vendor - plenty of data-oriented services are tailored for specific industries and uses, and their pricing sheets and tiers are designed around the use cases and marginal value of the data within that industry. When sourcing data, I could get pretty incredibly deals from these companies, as their sales teams basically used the transaction as a form of market discovery and saw the relationship as a way to feel out a particular market segment they hadn't been going after previously.

johnrgrace 7y ago

As someone in a fortune 50 company working in a data internal startup this guide has been one of the first that really gets the unique aspects of data.