Early in November, the Data Pitch team interviewed 57 startups and SMEs over 4 days. Two panels ran concurrently, and we are excited to start working with the 18 companies that were accepted into the accelerator to start in February.  

Of course, that means that 39 companies did not make it past the interview stage. We’re sharing some of the reasons that they were not accepted in the hope that this feedback will be helpful for companies planning to apply to next year’s challenges or to other related programmes.

The Right Representatives

While we appreciate that visas, travel costs and availability can sometimes make it hard to attend the interviews, having the right people at the interview can make all the difference when convincing the panel that your company truly has the skills and capacity. Although you may be confident that your technical team can address the issue, the interview may balance on whether your solution is better than that of another start-up, and the panel needs to be convinced of this.

Companies that didn’t perform well in this aspect:

  • depended on part-time team members for their core technical skills;
  • answered ‘X, who is not here, knows all about that’ when asked about technical capacity;
  • were clear on technical aspects, but less so on the business model.

Technical Capacity

While we do not ask for details of your IP, we do need to investigate your solution in terms of the general approach taken. Therefore, Data Pitch ensures that there is at least one person with in-depth technical knowledge – at a minimum, a doctorate in computer science – in the interview, in order to ensure that we ask the right questions and understand the answers.

Companies that didn’t perform well in this aspect:

  • avoided going into technical detail even when probed;
  • referred to ‘the box where the magic happens’, ‘magic sauce’ or explained their technology as, ‘the tech team doing their magic’;
  • presented slides that used lines or arrows instead of an explanation of the technology involved.

Open Innovation Approach

Open Innovation is defined as the use of purposive inflows and outflows of knowledge that accelerate internal innovation and expand the markets for external use of innovation. In practice, this means that a good application to Data Pitch will do two things:

  1. solve a problem for the owner of the data (inflow), and also
  2. create a new, sustainable and innovative product or service for the market (outflow).

Companies that didn’t perform well in this aspect:

  • treated this as an individual, one-off project;
  • did not show any benefit to the data provider;
  • could not demonstrate that the data provider data contributed substantially to the development of a new product or service.


Data Pitch is a European project in a cross-lingual, cross-sectoral programme. Our challenges are carefully devised to be relevant across Europe. Therefore, we are looking for propositions that have the ability to cross borders. In several cases, we funded companies because they demonstrated to us that participating in Data Pitch would enable them to take a proven product or service from one geographic market into another.

Companies that didn’t perform well in this aspect:

  • were unable to convince interviewers that their product or service was relevant or applicable beyond the initial region;
  • did not convince interviewers that they had plans to expand beyond the initial region.

Survival of the Fittest

Lastly, we often talk of the ‘ecosystem’ around data. With this analogy, it’s worth noting that only one species can occupy a specific ecological niche. If two species have the same characteristics, only one can survive. In some cases, companies were not accepted into the accelerator because another company was offering a sufficiently similar product or solution, but with a stronger team, or customer proposition. A good understanding of where your company fits in the competitive landscape is vital to avoid this situation.