
Mattermark (YC S12) raises a $6.5M Series A to keep VCs in the know - dmor
http://pando.com/2014/12/16/got-startup-data-mattermark-raises-a-6-5m-series-a-to-keep-vcs-in-the-know/
======
tapp
@dmor:

First - congratulations to you and your team on the raise.

Second - a question: your last post on the topic from June 28th announcing
your 2M second seed funding said that after 27 consecutive months spent
pursuing some kind of funding, it was time for you to take a break from
fundraising mode.

Given that was less than 6 months ago, it doesn't seem like you took much of a
break after all :) Would you be willing to provide more insight and details
re: what exactly changed?

[https://medium.com/mattermark-daily/mattermark-has-
raised-2m...](https://medium.com/mattermark-daily/mattermark-has-raised-2m-in-
our-second-seed-round-e93b20dc59b0)

~~~
dmor
Thank you.

After we announced the 2nd seed round the interest in us increased and we
ended up raising more, and then when Brad Feld (at Foundry Group) offered to
do the FG Angels syndicate on AngelList I figured "why not?" and I was curious
to see the internal mechanics of doing one of those. So basically we raised
because we've always be fans of "take money when you can".

By this point we had a ton of momentum in sales, had clarified our vision a
ton in our month-long company retreat in August, and were not in a position of
desperation for once. I felt like I should take heed of the old advice that
"the best time to raise is when you don't need the money" so we did some
analysis, had some coffees, and picked 6 firms to pitch. We committed to
testing the market again.

This time, it worked.

This stuff is just messy.

------
dmritard96
So is this just an aggregator of crunchbase/angellist/linkedin or some
combination of scrapers and other sources?

~~~
maxpain
yes basically.

i worked at a firm that used mattermark, datafox, etc. the amount of
inaccurate, duplicate, and missing data was very high. all of these services
are like a mashup of data sources that are not very good.

there's a reason bloomberg, thomson, etc. focus on public companies.

~~~
birken
It is comical how often sources like crunchbase (and even the press) are
wrong. Though it makes sense, private companies basically have no incentive to
release any sort of data unless it plays to some narrative they are trying to
create.

For example, the date the company was founded is often wrong in Crunchbase (it
is reported as more recent than it actually was). Many companies raise money
and don't disclose it for months (staying under the radar). Many acquisitions
never publicly release the price (so the founders can claim it was a "success"
regardless of whether it was).

It is just a tough space to be in to try to make something of the data that is
available. Public companies are of course _much_ easier.

~~~
zeeshanm
Data accuracy is important but sometimes the bigger problems to solve are
discovery, advanced filtering, and readability. I've played around with
Mattermark a little bit and I think it does a fantastic job in solving the
later problems.

From a hacker's perspective you can do curl/wget, awk, etc to aggregate and
filter data from various sources yourself. But to make the same tooling
available to a wider audience is what gets you to the market. Dropbox is a
solid example, for instance, that made rsync super simple to use for anyone.

~~~
7Figures2Commas
> Data accuracy is important but sometimes the bigger problems to solve are
> discovery, advanced filtering, and readability.

Discovery, advanced filtering and visualization are increasingly solved
problems. Open source solutions like Elasticsearch Kibana[1] make it
incredibly easy to analyze and visualize large amounts of data, and to do it
better than many paid services.

For high-value commercial use cases, like those in financial services, data
accuracy and completeness is all-important because your ability to identify
the best opportunities and make good decisions is almost always proportional
to your knowledge of the market.

Take a seemingly simple venture capital use case: I want to identify pre-
Series A fintech companies in California and New York founded in the past 3
years that have raised between $100,000 and $1 million and last raised funds
4-8 months ago. If funding data and corporate information is incomplete or
inaccurate, and/or funding events have not been properly categorized, the list
of companies surfaced will likely exclude companies that meet the criteria,
and include companies that don't meet the criteria.

For many use cases, it doesn't take many false positives or false negatives to
render a data set effectively useless.

[1]
[http://www.elasticsearch.org/overview/kibana](http://www.elasticsearch.org/overview/kibana)

------
pbreit
The VC industry seems like a tiny niche. But I feel like I've heard them talk
about being a more general lead identification tool which has far more upside
(ie, "show me all the companies in Seattle with at least 5 salespeople and at
least $5m in funds raised").

~~~
dmritard96
A lot of the advice I have seen though is too take a niche industry and own
it, then generalize. Its much easier to grab traction when you really know you
exact sales targets.

~~~
notahacker
The ironic thing about the niche in question is that it's arguably one that
can be tackled quite happily without VC money (tech-savvy, relatively easy-to-
reach B2B market, decent margin on an individual sale, small total market size
but acquirer-friendly and can organically grow into other areas of finance
intel driven by customer development).

Raising $11.5M in total commits them to generalising though, and there's no
shortage of competent competition in the market-data aggregation space.

~~~
larrys
"The ironic thing about the niche in question is that it's arguably one that
can be tackled quite happily without VC money"

At what scale and how long would that take? The VC/angel money allows you to
move faster, take more chances and perhaps hire better and faster. And lose
money. Important point.

Look at their pricing:

[http://mattermark.com/#pricing](http://mattermark.com/#pricing)

Then this:

"Today, Morrill’s curiosity and her 27-person team’s"

Imagine the payroll for those 27 people and how many subscriptions they have
to sell with what is (for now) a niche product.

What are the figures on fully loaded labor costs for a 27 person team?

~~~
dchuk
> What are the figures on fully loaded labor costs for a 27 person team?

Probably somewhere around $2mn - $4mn/year. That's a pretty big team for the
amount of money raised to this point, they must be doing ok subscription-wise.

------
andymoe
Congratulations Danielle and team, really enjoy following along with your
adventures via twitter and enjoy the daily newsletter from Mattermark. You're
openness and candor is refreshing as well.

~~~
eriksie
Congrats Danielle!

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benhamner
Congratulations! Y'all have had a wild ride so far, for being among the
coolest and most practical companies in the data space

------
philjackson
Danielle seems like a great founder.

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benoits
congrats Danielle and Kevin (and team!), you guys are awesome :-)

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jfornear
Congrats!

