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A Comparison of Early Stage Private Company Startup Databases

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Startup Database

If you are an early stage investor (Venture Capitalist, Angel investor or other Seed fund), there are now a host of databases which claim to have the information required to scout, identify and track startups. There are 2 open data sources – Crunchbase and AngelList and 5 known new age companies – Datafox, CB Insights, Mattermark, Tracxn, Rocket Companies and Owler.

Crunchbase and AngelList have proprietary data (which they have open sourced) that’s entered by the startup founders and “followers” of the company.

The rest of the systems have either used public API’s or crawling to build their database of startups from sources such as Crunchbase, AngelList and LinkedIn etc.

All of these systems have almost identical pricing ($399) for a single seat per month. Owler claims to have a free tier and CBInsights has priced themselves even more than these solutions.

All except Datafox have given me some form of limited access to their data for evaluation purposes.

All these solutions are looking to replace the expensive Venture Intelligence reports or Reuters data or other private databases from yesteryear’s or become the “Bloomberg” terminal for private companies similar to what’s being used by traders and investors for publicly listed companies.

The mega trend that’s important for the story: The benchmark for a good stock to buy was a “ten bagger”. A company that if you invested $1 would return $10 in relatively short period of time (2-5 years) as initially quoted by Peter Lynch.

What’s happening in the private markets is that due to the onerous regulations, Sarbanes Oxley law and other paperwork associated with being public, tech companies are staying private longer.

So they are becoming multi-ten baggers before they go public. Companies like Facebook, Twitter, Uber and AirBnB, may do well as a public company, will no longer be a 10 bagger post IPO (or highly unlikely) but are obtaining large valuations from seed rounds to Series D or E.

So, many investors are looking to invest earlier into these companies. Data from companies listed above will be very useful for these investors, to make decisions on investing.

All these systems have a fairly similar UI and have almost identical data. for the 3 sectors I wanted to track – Internet of Things, Consumer Internet companies and B2B Enterprise software companies.

I am sure you will have better value for the arcane categories. There is not much of a difference in their data since they all seem to obtain data from the same sources. Except Tracxn, I dont think the others use manually curation to track or manage their database.

There are 3 top things I looked for when evaluating these systems:

1. Comprehensive nature of their data: Most are fairly similar and you may get a 10% variation in companies from one system versus another.

2. Capability to export and do analysis manually: There’s not much of a difference here as well.

3. Their analysis, reporting and intelligence platform:All of them are in version 1 of their analysis modules, so right now there is a tremendous lack of sophistication on their data analysis.

Most peers in other companies and a few Venture firms I know, use more than 1 system and pull that data into their own CRM system.

I wont be able to really recommend one system over the other. They all do the job for a beta / version 1 system pretty well and right now, Datafox has a good visualization engine as does CB Insights.

CB Insights has the most robust system, but in all 3 cases had the least # of companies of the other 4. Tracxn claims to have analysts that are curating their data, but I dont see the impact of that on their database.

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Creating Artificial Constraints as a Means to Innovation

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Artificial Constraints

Many of the entrepreneurs I know have created new innovative startups thanks to real constraints they had. For example, I was hearing AirBnB’s Brian Chesky, on the Corner Office podcast and he mentioned that when he and his cofounder were trying to get some money to get started and the only way to keep afloat was to “rent” their air bed they had in their room. That, then led to Air Bed and Breakfast, which is now AirBnB.

This was a real constraint they had – no money to “eat” so they had to make it happen somehow.

I have heard of many stories of innovation where in the protagonists had real constraints of either financial, technology, supply, demand, economic, social or any number of other characteristics.

The interesting story that I have also recently heard of how Facebook has “pivoted” from being a desktop offering to getting a significant part of their revenue from mobile is how they were given the arbitrary constraint of only accessing Facebook via the mobile phone.

So there are ways that you can create “artificial” constraints to force innovation to happen.

Most larger companies and some smaller ones as well, have to constantly find ways to create artificial constraints – to find a way to innovate and be more be a pioneer.

While some constraints are good – lack of funds at the early stage for example and lack of resources, there are entrepreneurs that are stymied by these constraints and those that will find  a way to seek a path to go forward.

I think this is a great way for you to think about innovating in a new space. If you have constraints, find a way to use it to your advantage.

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The Great Mobile App Migration of March 2020

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Mobile App Migration

Over the last few weeks as many in the world have been in lockdown, there has been a temporary “mobile app migration” happening. There are new apps downloaded and they replaced existing apps on the “home screen”.

While some of these apps are likely temporary use, for e.g. I have 6 “conferencing apps” – Zoom, Uber Conference, Webex, Google Hangouts, Blue Jeans and Goto Meeting. That is because of the many people I have conference calls with – each company seems to have chosen a different web conference solution.

Other apps seem like they will have staying power – Houseparty, for e.g. which has games, networking and video conferencing all built into one app to keep in touch with friends and relatives.

Houseparty

The apps that have moved away from my “home” screen, which I expect will come back once the crisis will be behind us include – Uber, Lyft and all the airline apps from Delta, Alaska and United.

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Perseverance with the Ability to Pivot on Data: 21 Traits We Look for in Entrepreneurs

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Perseverance with the Ability to Pivot

There are 5 key inflection points I have noticed which makes founders question their startup, to either make a call to continue working on their startup, pivot to a new problem or quit their startup altogether.

It is at these points that you really get to know the startup founder and their hunger and drive to be successful. I don’t think I can characterize those that choose to quit as “losers” or “quitters” because of many extraneous circumstances, but there is a lot of value that most investors see in entrepreneurs who face an uphill part of their journey to come out on the other side more confident and stronger.

These five inflection points are:

  1. When you have to get the first customers to use and pay for the product you have built after you have “shipped” an alpha / beta / first version. Entrepreneurs quit because they have not found the product-market-fit – because the customer don’t care about the product, there is no market need, or the product is really poorly built, or a host of other reasons.
  2. When you have to start to raise the first external round of financing from people you are not familiar with at all. Entrepreneurs quit because while it is hard to get customers and hire people, it is much more harder to get a smaller set of investors to part with their money, if you do not have “traction”, or “the right management team” or a “killer product”.
  3. When you have to push to break even (financially) and sustain the company to path of being self sufficient. Entrepreneurs quit at this stage because they have now the ability to do multiple things at the same time – grow revenues and manage costs, and many of them like to do one but realize it is hard to do that without affecting the other. So, rather than feel stuck they decide to quit.
  4. When you have to scale and grow faster that the competition – which might mean to hire faster, to get more customers, to drive more sales, or to completely rethink their problem statement and devise new ways to grow faster. Entrepreneurs quit at this point because they are consumed by the magnitude of the problem. They overassess the impact the competition will have on their company, give them too much credit or focus way too much on the competitors, thereby driving their company to the ground.
  5. At any point in the journey, when the founders lose the passion, vision or the drive to succeed. Entrepreneurs quit a these points because they have challenges with their co founder, they don’t agree with the direction they have to take, or encounter the “grass is greener on the other side” syndrome.

While I have observed many entrepreneurs at these stages at  discrete points in time, I have also had the opportunity to observe some entrepreneurs in the continuum, and I am going to give you my observations on 3 of the many folks I have known, who, have quit.

Perseverance separates great entrepreneurs from good ones
Perseverance separates great entrepreneurs from good ones

One went back to college to finish his MBA after getting a running business to a point of near breakeven, another found the business much harder than he originally thought he would and got a job at a larger company and the third was just unable to have the drive to go past 11 “no’s”‘ from angel investors.

Over the last 8 years, if I look at my deeper interactions with over 90 entrepreneurs, who I would have spent at least 100+ hours each, I would say that of the 24 people that are not longer in their startup, the one thing that stands out among the ones that persevere is that it is not “passion” or “vision” at all.

It is the inherent belief that they are solving a problem that they believe is their “calling”. They also don’t believe that there is any other problem that’s worth solving as much, even though there may be easier ways to make money.

So most of my questions of entrepreneurs to test whether they will pivot or quit are around why they want to solve this problem (which I am looking to see if they know enough about in the first place) versus any other one.

The answer to that question is the best indicator I have found to be the difference between the pivots, the leavers and the rest.

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