The realisation that a good startup idea alone does not guarantee success can be a bitter pill to swallow. You may have pulled 80-hour weeks for over a year drawing no wage, but eventually the stark reality will hit home.
Pursuing a startup is risky business.
This is why many startups choose to give up their shares to investors – to minimise risk. They’re often driven by what they believe happens in Silicon Valley – you come up with a concept, you pitch it to investors, and all of a sudden you have a million dollars, and you’re building the next big company.
It’s not so simple. Yes, investors in Australia appear to be more risk-averse. But can you really blame them for being cautious about what ideas they invest in? It’s their money, after all.
Raising investment capital is like selling high-end assets. The difference is, once you buy a house, the keys are yours straight away. Investors are paying for something they may or may not get.
As such, investors too, need to do their due diligence before handing over a significant cheque
So how exactly do Australian investors assess and monitor companies?
Danny Bhandari, Founder of Tibra Capital who no longer works at the firm though is still an investor, told Startup Daily that he looks for qualitative and quantitative measures.
“I try to get an understanding of customer engagement and behaviour as well as raw data. This applies to both companies and sectors. It is harder to obtain and assess qualitative data but the insights are necessary to provide me a rounded picture,” Bhandari said.
Ilya Frolov, Investment Director at Oxygen Ventures, told Startup Daily that the VC firm uses Crunchbase – a global dataset of startup activity that features 650,000 profiles and accessible to everyone – to seek history and growth of various tech companies worldwide. He said, “It’s high level and an overall quick way to validate business models or like-companies.”
The other tool that Oxygen Ventures uses is PitchBook, an award-winning data and technology provider for the global private equity and venture capital markets. Although it has a strong US-oriented reporting mechanism, Frolov said the depth of information is “quite impressive” because it can “immediately bring up comparative companies and valuations.”
There are certainly tools that help investors cut down the research process, but it’s still predominantly manual.
A new startup DataFox has emerged, offering what appears to be a holistic and automated solution that allows investors to make better investment decisions. Google Ventures Partner Dave Munichiello even said that DataFox “is well positioned to help foster a new era of transparency in the world of private-company data.”
The Palo Alto, California-based startup began as a class project and was incorporated in September 2013. The brains behind DataFox are four Stanford University alumni, Bastiaan Janmaat (CEO), Mike Dorsey (CPO), Ben Trombley (CTO) and Alden Timme (Architect), who all hail from top engineering programmes, and carry experience at companies like LinkedIn, Lockheed Martin, Cisco, Financial Engines, Box, and Goldman Sachs.
Together they have created a deal intelligence platform that makes access to “big data” available to anyone in real-time, allowing individuals and companies make more informed investment decisions.
“We want to build a product as powerful as a Bloomberg terminal but as easy to use as Pinterest,” Janmaat told Startup Daily.
The subscription-based software has been designed for investors and analysts from financial institutions, corporations, and governments. The technology aggregates and makes sense of millions of data points to track, score, and rank about 450,000 US-based private companies, allowing users to discover new investment opportunities, maintain a real-time understanding of prospective and current portfolio companies, and identify industry trends and patterns.
“One of the biggest problems in the field of sector analysis is that traditional sector taxonomies are broken. SIC codes don’t work, companies sometimes don’t even know in which bucket to categorise themselves, so what we’ve done is trained an algorithm to calculate the distance between companies on a multidimensional plan. We then plot those distances … on a diagram,” Dorsey said at this year’s TechCrunch Disrupt.
“We can tell you that Box is not simply a software publisher. They straddle three different sectors – file storage, consumer enterprise management, and enterprise content management.”
DataFox’s main incumbents in the market data space include Bloomberg, Thomson Reuters and S&P Capital IQ on the public company side, and Dun & Bradstreet and S&P Capital IQ on the private company side. Analysts and consulting firms are seen as alternatives to DataFox, however, their methods of data collection and analysis is manual. Whereas DataFox is the ‘automated analyst’.
At TechCrunch Disrupt, Dorsey explained that they “saw first-hand how arduous it is to crawl the web, search on google, copy and paste data into spreadsheets.” Then once the spreadsheet is created, it becomes “stale” and analysts have to constantly update it – making the entire process tedious and repetitive.
DataFox’s algorithms specifically looks for data points that correlate with company outcomes (success or failure). Indications of growth such as revenue, headcount, user numbers, as well as qualitative success factors like hiring talent, support from impactful board members and investors, are are the types of insights that analysts currently try to garner manually, which DataFox delivers automatically.
“Because private company data is so sparsely distributed along a long tail of data sources, it’s especially bad. Analysts open 20 different tabs, there’s reading to the 19th page of Google results, hunting around for a little data point to fill into excel,” Dorsey said at TechCrunch Disrupt.
“We knew there had to be a better way. Not surprisingly, Silicon Valley, not Wall Street, was the first to come to this better solution. Venture Firms on Sand Hill Road in Mountain View began using algorithms and … data science to mine the public web to identify data points that could help give them signals about the growth of the companies in their portfolio and sectors that they cover.”
“Hence, DataFox. It’s an automated analyst.”
Dorsey joked at TechCrunch Disrupt that best of all, their analyst (DataFox) “doesn’t sleep, it doesn’t eat, [and] it doesn’t complain about getting bonuses”.
He added that the startup has built “the world’s best company search engine”. Users can filter by company, sector, and other keywords, as well as funding amount, investor portfolio, among many other criteria. For instance, if the user is interested in ‘ridesharing’, they can enter that into the search bar. DataFox will ask the user whether they are also interested in “carpooling” and other related keywords. The user may also want to know about ridesharing and related companies that have been founded within the past few years. DataFox’s algorithm will then force rank all the companies that the user wants to learn about based on their exact query.
If they want to learn about, say, Uber, in particular, they can click on the company, and there will be one page that contains all the critical information about the company – like the approximate headcount for that company, the sector it operates in, funding details, etc. DataFox will also show the user the top 10 companies that are similar to Uber, though they may not necessarily be related to ridesharing.
In the TechCrunch Disrupt demo, Instacart showed up as a related company to Uber. Although it offers a grocery delivery service, Instacart, like Uber, is an on-demand service. The user can add related companies to their list and DataFox will automatically generate a sector report. In the case of ‘on-demand’ service companies, Uber shows up as the leader in the segment, topping the list. At the same time, DataFox shows the user that there are some other up-and-comers that are on the growth curve, that can be added to the list.
Dorsey says the ‘data table’ their software delivers is “magical” – “it’s like a spreadsheet on the web that’s backed by a database, but it populates itself”.
In the TechCrunch Disrupt demo, he adds TaskRabbit to the list and DataFox automatically fills in the spreadsheet with up to 50 columns of data that the software automatically pulls from the web, and ranks the company based on DataFox’s quality score.
When users follow companies, DataFox automatically sends them email updates about those companies, as well as related ones, when something significant happens – like a major capital raise or acquisition.
Although the level of automation DataFox offers is impressive, an important question is: how reliable is this data? Dorsey explained at TechCrunch Disrupt that DataFox crawls company websites, as well as SEC filings, and news sources. All the data is audited to identify interesting signals. The startup has developed algorithms that help the team compare data across sources and identify incongruencies.
“The main source is consumer generated. Our users can alert us to incorrect data, or can ask to build profiles that don’t already exist,” Dorsey said.
The startup also has API relationships with 12 data partners who provide data to and retrieve data from DataFox.
Fifteen months ago, DataFox had no proprietary data. At the moment, they consider their company scores and sector clustering to be proprietary.
“The data that we pull from unstructured data sources and then [structure] it, it’s not strictly proprietary, but it was inaccessible initially. By making it accessible, in a way, we’ve created value on top it,” Dorsey said.
The startup told The Dish Daily, that “It is imperative that a [democratised] source of real-time information on those sectors and companies be available – not just for well-resourced financial institutions, but also for the millions of other knowledge workers who rely on the types of insights that DataFox is able to generate.”
It seems democratisation or accessibility is well-reflected in DataFox’s subscription tiers – $49 per month for personal use, $399 per month for professional use, and “call us” for a custom plan. That’s not to say that DataFox wants to make analysts redundant; rather, “they’ll be supercharged with [DataFox’s] tool”, according to Dorsey.
To date, DataFox has raised $1.78 million in seed funds from Google Ventures, Sherpalo Ventures, Jawed Karim (YouTube founder), Social Leverage, Green Visor, Leo Polovets, and the Stanford-StartX Fund. The startup intends to raise more funds in a Series A round next year.
DataFox told TechCrunch earlier this year, that it is focusing on professional investors, publishers and VC firms. Janmaat told Startup Daily that the company has been able to attract more than 25 high-profile paying corporate clients, as well as a slew of individual analysts. Based on various report, publisher customers include VentureBeat, The Wall Street Journal, Strictly VC and The Information, comprising around 5 to 10 percent of its total customer base. Investors and VCs account for another 45 percent, and include Accel Partners, Intuit, Google Ventures and interestingly Bloomberg Beta. Tech companies like Twitter and Box are also customers, according to various news reports, as well as Samsung.
Judging from these clients, it appears DataFox is gaining significant traction in the US market, though Janmaat told Startup Daily they have clients in other countries as well. DataFox plans on including international company profiles into their database and subsequently expand into international markets.
“We have subscribers all over the world, but most of the companies in our database are in the US. We plan to expand to global coverage later next year. The US continues to be such a leader in innovation that many of our international subscribers rely on DataFox to keep their fingers on the pulse of innovation in their respective sectors,” said Janmaat.
Given the startup is still in its early stages, it is constantly improving itself based on customer feedback. Thus, prioritisation is DataFox’s biggest challenge, according to Janmaat.
“We have over 130 pages of customer feedback, and are constantly readjusting our roadmap to solve the hard problems that our customers are clamoring about,” he said.
That said, he said that it’s been exciting to see how fast DataFox’s engineering team can move, not only in delivering on their original product roadmap, but also delivering customer requests in a matter of weeks if not days.
“We’re excited to have found product-market fit so quickly and now want to continue to build out our platform to keep up with customers’ requests,” said Janmaat.
“We pride ourselves on our very tight feedback loop with our customers.”
Given Australia’s investment culture has been deemed to be ‘risk-averse’, it will be interesting to see whether DataFox will alter that.
Although Ruwan Weerasooriya, Founder of Rewardle and Huge Capital, admits to not being close to the DataFox story, he said that “quality data delivered in a timely manner is critical to decision making.”
“There are so many sources of content and information that it is challenging to stay across it all and filter signals from noise. A service like DataFox may be an interesting tool to streamline the information flow,” he said.
Frolov from Oxygen Ventures told Startup Daily that the usefulness of tools like Crunchbase, PitchBook and DataFox depends on the stage that a company is in, in its lifecycle. “[The ] later the stage company we’re analysing, the more useful the tools I mentioned above (Crunchbase and Pitchbook) have for valuations and where Datafox can provide value.”
He added that when it comes to early-stage companies, it’s more the team and current traction that the firm is focused on when creating risk profiles for investments.
“Generally, information for investment in the tech startup scene locally is quite fragmented. Datafox may provide a means to consolidate that information into a more cohesive platform,“ said Frolov.
Bhandari, who is now the Co-Founder of Centre Wicket, and Founder of Ninyo, believes the commoditisation of data provides huge opportunities for investors and startups. He acknowledged two aspects to data – the first being, collection and storage, which he admits is becoming cheaper, more efficient and highly accessible. The second relates to customisation, configuration and analysis. Bhandari said DataFox’s utility in the local market will “depend somewhat on its ability to be customised for specific applications and also the end user’s knowledge on how to slice up and interpret large amounts of raw data, and form valuable conclusions from it.”
Although he believes that companies like DataFox have a big opportunity to be a provider of powerful but cost-effective tools, the market “may not yet have the skills and experience to take full advantage of the possibilities presented.”
“[It] may take some time and a process of education before the full benefits to customers are seen and pursued,” Bhandari added.