Unicorn or donkey? How accelerators and venture builders identify the best tech startups

Most startups fail. We examine the secrets of the ones that survive and thrive

Tech startups are ten a penny, sprouting up in response to advances in technologies such as Blockchain and AI. Many vanish as quickly as they arrived leaving nothing but a hastily written white paper and a flashy website to show for their brief existence.

To sustain a tech startup you need to be possessed of strong conviction and self-belief, with perhaps a hint of obsession; you need the resilience to to take the inevitable knocks on the chin and move on. After all, nurturing a startup can be a great way of alienating friends and family and burning through piles of cash.

But turning a startup into a successful business hinges on a lot more than the personalities of the founders. There are a whole host of other factors too - including blind luck. In the early days in particular, attracting support from accelerators, incubators and venture builders is one thing that can make a big difference.

Startup accelerators are public or private bodies that offer mentoring, support and funding to selected startups over a fixed period of time, whereas venture builders are more hands-on, bringing together resources, infrastructure, networks and experience to help entrepreneurs take their ideas from conception to scale, maturity and sometimes exit. In return, the venture builder takes a share of the business.

Clearly, successful accelerators and venture builders must develop ways of weeding out the blaggers, the hopeless dreamers and the misguided, identifying those startups that have a fighting chance of creating a self-sustaining business.

Computing asked an accelerator and a venture builder about the magic ingredients the best tech startups have in common.

The idea

All businesses start somewhere. Most begin as an idea about how to do some task better, or how to exploit a particular niche that few have yet spotted.

"The first question we ask is 'what's the value proposition?'", said Orsola De Marco, head of startups at the Open Data Institute (ODI).

"It's crucial they have identified a problem to solve. If it's just a nice-to-have you'll struggle to market it."

De Marco is UK leader of Data Pitch, a European Commission-funded accelerator programme designed to nurture an ecosystem of data startups. It also seeks to match corporations looking to build on their data with start-ups having the correct expertise.

Visor.ai, one of 18 startups selected by Data Pitch for support, has started working with MASAI a pan-European project to link travel scheduling, reservation and ticket information. The startup noticed that hop-on-hop-off buses in popular tourist destinations are a frequent source of complaints, with buses failing to show up or arriving already full and a general lack of information as to their whereabouts.

Their idea for this particular pitch was a simple one: to use chatbots

and real-time geolocation data to notify tourists about the whereabouts of the buses over Facebook Messenger. With an early focus on chatbots in Spain and Portugal "where natural language processing is not so advanced as in English-speaking countries", according to business development director Gianluca Pereyra, the company has customers in other sectors too including a telco and drinks maker Heineken.

"We don't just focus on one sector which means we're sustainable," Pereyra explained. "If we see a problem we can fix then we will do so."

We were trying to impose our solution but the customer didn't want it, we got a lot of learning from that experience

Underlining De Marco's point about there needing to be a real problem to solve, Pereyra admitted that Visor.ai's first attempt was not a success. "We were trying to impose our solution but [the customer] didn't want it. But we got a lot of learning from that experience," he said.

The USP

Originality is a tough call in the internet age where ideas go global in hours, even in the field of cutting-edge technology and data. An idea does not need to be original to be worthwhile, of course, but the presence of an established competitor is a definite danger sign.

"There are always competitors," said De Marco. "The important thing is that there is not a star competitor doing the same thing".

Certainly, there are a lot of tech companies involved in the smart cities movement, but there is room for many specialisations, said Ricardo Vitorino, R&I manager of analytics specialist Ubiwhere, which has been working on transport analytics in smart city projects overseen by Cisco.

"Typically the big multinationals have lots of money to invest but in the end, the companies that put things in the field, do the integration and the tweaking, solve problems or answer specific questions are startups or SMEs that are focused on that area and that's where we're positioning ourselves," he said.

The money

While there may be a few Nathan Barley-esque startups around, apparently with more money than sense, for most new businesses the opposite is true. Seeing a good idea through to fruition requires a lot of financial support.

The funds required will depend on a number of variables including the sector the startup is operating in, the need for infrastructure, hiring skills, marketing and the rest, but at some point those lacking wealthy benefactors or substantial trust funds will need to seek out investment from banks, investors or accelerators. At this stage the most important thing is to be able to show that they have done their homework, De Marco said. While there may be too many unknown unknowns to produce a reliable growth projection, that doesn't mean startups shouldn't try.

Even if you're very early stage it's important to have some understanding of the market and your potential for growth

"Even if you're very early stage it's important to have some understanding of the market and your potential for growth. You need to show there are customers out there willing to buy your product or service. In order to know this you must have done a lot of research and talked to people who could be potential customers or partners, and you need to have engaged with potential investors. This shows you're doing things in the right order."

The Data Pitch accelerator offers the startups it selects funding of up to up to €100,000. "There's no equity involved, so there's no dilution in shares," De Marco said. "It gives a good runway of cash to be able to focus on developing the technology."

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Unicorn or donkey? How accelerators and venture builders identify the best tech startups

Most startups fail. We examine the secrets of the ones that survive and thrive

The team

"Cash is king. Without cash, there's nothing to pay the bills", said Mark Ridley, CTO of venture builder Blenheim Chalcot. That may be so but after that the right mix of people is the most important ingredient he went on.

"Most investors I've spoken to value the team first. It carries huge weight" Ridley said, offering a quote from Marc Andreessen:

"When a great team meets a lousy market, market wins. When a lousy team meets a great market, market wins. When a great team meets a great market, something special happens."

So what makes a great team in a tech startup? Well, first the efforts of its members must combine to meet the primary needs of the product or service: that it is desirable, technologically feasible and economically viable.

This is a topic of great interest to Ridley, who recently wrote a blog post on the topic, drawn from his experience of running hack days.

Cross-functional teams outperformed teams of close friends

"We'd hit upon an important realisation ," he writes. "Cross-functional teams outperformed teams of close friends, even though they were created in the moment. The challenge of the project created teamwork, but the skills allowed success."

The best teams are made up of four or five archetypes he theorises: dreamers, hackers, designers, hustlers and analysts.

Image credit: Mark Ridley

"The dreamer is often the chief customer evangelist and brings the original idea, inspiring staff and investors alike," Ridley says.

"Dreamers are positive and sometimes unrealistic; their challenge is that they are often not grounded or operational."

To tether the vision to planet Earth startups also need a hacker, a hands-on coder, engineer or process designer who can deliver on the dream.

A designer is also likely to be a feature of a successful team. This is someone who can add polish to a website, create marketing materials, write copy and so on.

Tech can be an insular business, but you won't get far without a hustler, says Ridley.

"The hustler is pure extrovert. Unafraid to pick up a phone and make cold calls, the hustler opens doors. While it might seem unnecessary to have a sales executive without a product, the hustler will help you decide how to take your product to market, and if it will even sell."

Finally, possibly keeping his or her distance from the hustler, is the analyst.

"Sales projections, cash burn rates, unit economics. The analyst will work on your customer acquisition costs, lifetime value and turn their hands at your finances," Ridley writes.

Sona Mnatsakanyan is an analyst, having done a masters in data modelling and analytics, but as a partner in predictive maintenance startup Zevit, she is clearly comfortable playing the hustler role too, presenting at the culmination of the first Data Pitch cohort earlier this month.

"We're planning to expand," she said of the dashboards the company is working on to advise field engineers of the need to make repairs.

"We will build out our software to operationalise predictive analytics, to make it easier for companies to make use of analytical models. At the same time, we want to integrate more universities and business institutions who would like to contribute using their models, using the shared data coming from our providers. So building an open platform and infrastructure where data providers and model providers can collaborate."

The credibility

For a corporation to share its data with a startup there must be a high degree of trust. In Zenit's case, that credibility comes in a large part from its background in the wind energy business. The startup was spun out of turbine manufacturer Vesta and the CEO remains a well-known figure in the industry.

The credibility gap can be a massive blocker

However, for many others the credibility gap can be a "massive blocker", De Marco said.

"In the case of internal data shared within the organisation, the perception of risk in sharing that data with anyone is huge. So it's very unlikely they'd trust some startup they don't know. Data Pitch provides the infrastructure and legal expertise. We have lawyers in the programme that look at all the different aspects."

From the startup's point of view, they get access to early-stage data so they can validate their solutions and grow more quickly.

"They don't often have those connections so often having a third party really helps provide credibility."

Surviving and thriving

These are not the only requirements for startups to survive and thrive, but they are among the most important. Others factors will depend on what stage the startup is at - early stage, growth stage or mature. Location may play a role too. One of Blenheim Chalcot's ventures, Avado, has had to work around a lack of Moodle developers in its native London.

Some will always prefer to go their own way, but there's no doubt that the mentoring, expertise and funding that an accelerator or venture builder can offer can make a big difference.

Startups involved in the EC-funded ODINE programme can expect a very respectable 74 per cent survival rate according to a recent IDC study (two of the current Data Pitch partners were involved in the delivery of ODINE, the ODI and the University of Southampton). Meanwhile Ridley estimates a rate of success of about 50 per cent more. Then again, these are startups that have been through the vetting process.

"We take a majority stake and look for solid growth rather than unicorns," he said, contrasting this approach with the venture capital model. "A VC model props up its portfolio with big bets - they look for one unicorn in 100 to carry the fund."