
Data-as-a-Service: Running DaaS Companies - hunglee2
https://blog.safegraph.com/data-as-a-service-bible-everything-you-wanted-to-know-about-running-daas-companies-d4cf4c15c038
======
garyjob
It took me two years of collecting and cleaning data before the model I have
been training it with started becoming useful for my own specific needs.

[https://trends.getdata.io](https://trends.getdata.io)

The first challenge I see with data as a service is that not all features you
need for your model will be made available by the vendor.

The second is their frequency of update might not be at the cadence that you
need.

------
AznHisoka
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.

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

~~~
cosmie
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.

------
andrewljohnson
This is one of those companies that will pay you to bug your app so they can
spy on your users. They also emailed me at least 8 times without any sort of
opt-in.

~~~
jonahbenton
Absolutely, but the author is not wrong in general about DAAS, and that there
are many, many DAAS opportunities that have nothing to do with violating
individual people's privacy.

~~~
akudha
Can you give a couple of examples of such DAAS opportunities?

~~~
jonahbenton
I would suggest a way to look at DAAS is through the lens of what has long
been called "Decision Support", and apply it to what might now be called
"microdecisions."

So- think about the personal microdecisions you make on a daily basis,
especially the small ones- shopping/cooking/eating; cleaning; dressing;
commuting; etc- and appreciate how many of those are not data-driven, are
rather just based on assumption, habit, history, etc. Appreciate how many
things one wonders about, idly, throughout the day, in regard to those
microdecisions.

With some reflection it's easy to see that having various kinds of data would
lead to your making different micro decisions. Some of those microdecisions
can substantively impact things that are important- health, wealth, happiness-
so will become business opportunities. Apply that to microdecisions made in
the course of work...

------
usgroup
This is my space broadly speaking and personally I think the treatment in the
article is unnecessarily idealised and elaborate.

People will buy data when it has a clear use which means most people don’t
sell just data, they sell “leads” or “clicks” or “followers”: something
actionable.

I think this is unlikely to change because having an internal data team
producing leads typically doesn’t make sense as a core focus.

There are a relatively small number of companies which do sell data and a
slightly bigger number of companies that actually buy data. In the UK it’s
easy to quantify because they all end up buying some of exactly the same
thing.

~~~
AznHisoka
"buying some of exactly the same thing."

What exactly is this thing?

You are right though. People don't buy data, just like they don't buy a SaaS
product. They buy something if it solves a direct need, saves them money, or
helps them generate more revenue. And like all things, it does need to have a
clear, understandable story and value proposition.

