As competition to invest in the best venture deals continues to increase, with total funding raised by European Venture Capital funds quadrupling in the last decade, some VCs are turning to technology to identify the fastest growing companies.
Currently, only a handful of funds are able to assess the true addressable market behind the demand for capital due to their recognisable brand and network effect, and even they are now turning to new technology to better predict which companies may inevitably become fund returners. Relying on inbounds as the primary source of dealflow is no longer sufficient.
This article draws upon insights from our recent VC roundtable which we ran in partnership with Global Shares, conversations with European investors, and their US counterparts, and a deep dive into the technologies currently on offer. The use of machine learning to identify fast growth signals, automation to keep track of company growth indicators, and outbound tools can all contribute to a more efficient investment process.
Before diving in, according to Eurostat, there are approximately 3 million companies formed each year. Although it’s likely that a large proportion of this number is made up of lifestyle businesses and holding companies rather than growth and venture-backable companies, it is still far greater than the 4,000 companies typically reviewed by VCs annually to get to their 12-15 investments. Global investors (of all shapes and sizes) are already spending $1.7bn on alternative data sources when sourcing deals, according to AlternativeData.org.
Transactional, public and open-source databases
Open source databases such as Crunchbase, now with over 650,000 companies on its platform, continues to be heavily used by earlier stage funds. Given that anyone can create an account and register their company on the platform, it also lacks appropriate qualification in assessing high-potential companies.
Transactional databases such as Dealroom and Pitchbook have been in the armoury of VCs for decades, and serve as a good first point of call for later stage funds. As information becomes more readily available in the public domain and early-stage companies turn to growth-stage companies, the Bloomberg Terminal also provides market coverage and information based on deal activity and company news, by acquiring, governing and distributing relevant data to its subscribers.
Governmental databases such as Companies House in the UK provide the first formal signal a new company has been formed. Although it is useful for sourcing very early stage deals, new share issues or other performance based indicators often exhibit a 3-6 months lag at a minimum.
Databases leveraging machine learning
Newer databases are now leveraging machine learning and signalling to collate company information through crawling online company profiles. It’s now possible to collect data from alternative sources such as the company’s site, social media platform, product libraries and news sources, that can provide growth ‘signals’, building upon transactional data, to provide a more meaningful dataset.
In the UK, transactional platforms such as Beauhurst are moving towards the signalling approach and building upon the informative data set out by the incumbents. Facilitated through the collection of a huge amount of first party data and scraping algorithms as well as a team of over 80 people to better qualify the companies on their platform, they deliver granular insight surrounding the companies, defining fast growth companies as those who have met one of their ‘trigger events’.
But this is only the beginning. The next step is to start leveraging signals to predict where the next unicorn is going to come from. This involves looking at individuals, rather than companies. For example, early-stage funds need to be first to identify talent leaving their corporate jobs or exiting an existing unicorn to start their own businesses.
New entrants such as Specter, used by Balderton and Accel, are doing just that and are adding another dimension to signalling data, taking approaches from all traditional, transactional, and vertical intelligence platforms. Using a wide variety of sources and building a proprietary company and talent scoring algorithms not only allows users to identify companies with high growth trajectories, but also enables first exposure to opportunities.
They produced some interesting insights, one year in. Utilising their talent algorithm, 352 New Role signals lead to funding rounds — resulting in $27 billion in funds raised to date. On average, the companies that these exceptional talents joined raised just 118 days after Specter featured the signal; providing additional proof points that the system works.
Behind every company success is a great team - and in today’s crowded investment arena, understanding how Talents operate and behave across the early and late investment stages of the private market is becoming a must for the modern investor.
Marco Squarci, founder of Specter
Other players such as Harmonic, used by the likes of Bain Capital, combine job posting data with transactional data to identify growth signals for fast growing companies which might be ready for investment.
Automation to track company updates
You can track website changes, such as client testimonials and new client logos of prospective companies using sites such as Wachete and VisualPing. They are both great tools to be automatically kept up-to-date with interesting companies.
You can track social media changes through plugins such as Flock, which tells you about meaningful updates from your Twitter network. Keep up-to-date with updates in biographies and individual tweets which may contain their next venture.
Historically, TechCrunch was the main platform for product launches, but companies such as Product Hunt are now on the rise. Products get submitted, upvoted then discussed by the community. Similar platforms include Steamhunt; a blockchain powered platform.
Google alerts is a simple but effective and free way of keeping track of topics that are important to you. You'll be able to track any keyword on the sources that Google has access to encompassing forums, blogs and news sites. Updates will be delivered to your inbox.
Demand for information beyond blogs and websites onto social platforms spurs demand for platforms such as Talkwalker and Awario. Tracking activity on social with points spanning location, language and sources tracks mentions and announcements.
Although very common, the Linkedin sales navigator remains one of the best ways to identify leads, making it easy to reach out to your target audience by narrowing down users via keyword filters. InMails, if used properly, can be one of the most effective LinkedIn prospecting tools you can use to engage with founders directly. Linkedin can also be used to track companies’ employee headcount, another growth signal. Personalisation should take priority when utilising this medium as founders may be inundated with such requests given the competitive landscape.
Leveraging scraping tools to identify contact details
GetProspect, Hunter.io and Aeroleads are all effective email extractors which can be used for outreach. All three platforms work by searching and indexing emails they find on company websites across the internet (in a GDPR compliant way). Collaborative features on both platforms make it easy to share information with the wider team, as well as being compatible with CRM systems such as Copper or PipeDrive.
Solutions for larger funds with multiple user accounts also exist such as Voila Norbet, which differentiates itself by enriching the quality of the data, operating in a market driven by sales-role specific solutions.
Follow-up strategy can be imperative given the busy schedule of a VCs outreach. Tools such as Woodpecker help companies directly contact prospective clients by automating personalised emails and follow-ups. PersistIQ is also a great platform in this space; send personalised emails at ease and also run A/B tests adding a different dimension to tracking analytics of success.
Moreover, if working in a larger firm, team wide solutions providing shared inbox functionality can improve response and outbound rate. Front App or Hiver are tools at the forefront of this collaborative approach.
Some VCs are already experimenting and in some cases, spending a lot of resources on building a quantitative approach to sourcing and diligencing. However, many European investors, despite being responsible for investing in and bringing to market some of the most exciting technologies, are not leveraging them as well as they can be within their own firms. The most successful investors will be those who are first to leverage technology to identify companies with the highest growth potential, combined with a human touch.
VC’s are always looking for new ways to gain insights into potentially untapped opportunities; if you don’t find them early, you can’t invest early either. Just like we’ve had to move our equity management away from spreadsheets and into a digital platform that allows you to get the most value out of that equity, the way we search for new investments requires tools that gives us a deeper understanding than ever before in a quicker time-frame.
Jason Ring, Head of Sales for Emerging Companies, Global Shares
There will always be information asymmetry. Startups will keep their cards close to their chests and will continue being protective of their data; the information gap that signalling databases are attempting to address.
However, past indicators of the fastest-growth companies used in machine learning may not always be a good measure of future performance (e.g. the strength of your personal network may have been more relevant 10 years ago). They may also reinforce bias inputted into the system.
Entrepreneurs prefer a personal touch, and are becoming more weary of automated contact. We rarely respond to automated emails sent to us if it is clear we were part of a mail merge.
Lastly, knowing which companies are growing the fastest before everyone else is certainly not enough. Without the ability to get in touch and then build a strong relationship with the founders, the data counts for nothing.
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