How to evaluate a startup quickly

Author: Andrew Miroshnichenko, Head of Experts, Rocket DAO


Present-day scales of the startup activities are excelling the power of the startup infrastructure significantly. A significant number of stakeholders of the investing process are making an enormous number of actions and operations. Startups send applications to the investment funds; investment funds spend their resources on forming pipelines. Angels are trying to find decent startups in the early stages of development, accelerators and incubators are struggling to build customised projects for the funds and scouts are there to do their job as well. Venture and startup infrastructures are waiting for the new infrastructural tools and experiments, which will technically improve the effectiveness of the given field.


For example, our Rocket DAO project takes the responsibility of evaluating startups. Open expert community creates a generally accepted evaluation standard and then evaluates startups following it. The results of the evaluation are accessible for the investors’ and startups’ use to enlarge their selling funnels.


Currently, Rocket DAO expert community masterminded and tested 2 evaluation formats: full and deep Due Diligence and short preliminary evaluation. In this article, we would like to share with you our conclusions and results of the short startup evaluation testings.


The aim of the full and deep Due Diligence is in the overall startup evaluation. An example of the full evaluation you can find via the link below: 


These are the aspects that are checked for Due Diligence:

  • The reliability of the project’s data in all aspects. In such a way, we cut off scum-projects as well as different embellishments, amplifications or concealment of the project's drawbacks.

  • Startup correspondence to the investment round’s requirements and validity of the claimed sum of the investments.

  • Startup potential from the point of view of the key factors, which influence the success by 10 criteria: team, market, business model, product, financial model, risks, assets and resources, legal model, PR and promotion, technologies.

  • A list of startup assets, which can be combined when realising pivots for the new business model.

  • Startup valuation.

  • Full list of documentarily proven data about a startup and a market, based on which it is possible to generate new business models for the startup.


As a result, we have not only a document with a quantitatively evaluated project, but also, an overall digital startup twin-copy, which can be used to make decisions relating to investments and management.


The crucial point in evaluating a startup is that, on the one hand, the experts, who conduct the evaluations, must strictly adhere to the evaluation procedure adopted by the Expert сommunity and, due to this, form an evaluation from the entire Community, which will be obtained by any competent expert, using the following procedure. On the other hand, this evaluation implies the possibility of expressing the уxpert point of view about the ways of startup improvement.


At first, Rocket DAO didn’t set the aim of providing the startup evaluation services, because evaluation is only one of the investment process elements, which has to be automated on the platform. However, when we provided evaluation of the Multy startup, several startups asked us to make evaluation of their projects. The interaction experience with these startups gave us a lot to think about.


We made the following observations:

  • In most cases the startups that order evaluation are the ones that are confident in themselves, whose founders have a vast background and existing businesses.

  • The primary reason why startup asks for the evaluation is feedback from international experts about the created startup configuration and the understanding of the possible reactions of the invest funds on the startup itself. Lastly, in case of positive reaction, the startup hopes that Rocket DAO will send the Due Diligence evaluation through info channels to their partner funds and angels; and they will find interest in the startup.

  • Filling in the questionnaire and regarding the question content, startup understands that their product can become more valuable and attractive to the investors by changing the way of startup development. Therefore, filling out the questionnaire is accompanied by startup transformation - demand is tested in a new market, the product is technically brought up, the team is supplemented by partners with missing competencies, legal issues are resolved, etc.


What conclusions have we made?

  • First of all, attempts to answer a Rocket DAO Due Diligence questionnaire eventually turns in acceleration of a startup.

  • Secondly, those startups who are ready to complete the Due Diligence are already formed and have self-confidence. More likely that they do have already tested business model and they actually need the evaluation to show their willingness to receive investments.


What must those startups do, whose business model is not perfect yet, and they want to receive Expert and Investment communities' feedback about their hypotheses of how they want to generate income?


Right for these purposes, Rocket DAO prepared a short evaluation based on the Due Diligence, so just before the start for a final assessment in the Due Diligence framework, a startup would be able to discuss its business model and product with experts. The startup has to answer 16 questions in such sections as “team”, “product” and “market”. There is no need for startups to represent documented data, proving their hypotheses. Also, there is no rigid evaluation criterion in the expert evaluation forms; experts have to choose between marks, and the main thing - they(experts) have to answer 3 additional questions: what are the startup strengths? What are the startup weaknesses? What is needed to be done so a startup would receive higher evaluation marks?


Here you can see the example of short evaluation report 


The experience of evaluating 3 startups using this format has shown the following results:

  • We had doubts that startups would understand the questions which they needed to answer in the evaluation form. Usually, open questions baffle the respondent as he doesn’t understand what kind of answer he has to give. Moreover, each question implies a specific theory, in the framework of which, evaluation takes place. For instance, when it concerns such a notion as “value proposition”, what is this about? Usually, we need to explain to the startup what is this all about. However, it is impossible to appoint a personal consultant to each startup if we scale the evaluation process and increase the number of evaluated startups. So, to avoid this problem, we elaborated on each question we ask a startup and gave a set of examples of the startup answers, which has already received the evaluation. As a result, all the startups, which were questioned, fully and clearly answered the questions.

  • Many startups greatly or not very embellish their project. Mainly, this concerns technical data and tracking data. Often this happens under the guise of extremely short and concise answers. Experts reveal these facts and evaluate the project using not the given information, but using factual data, available on the open sources or statistics of similar projects. Startups start to answer more seriously after they read the Expert evaluation about previous startups. They work on the answers longer and more responsibly. Finally, we begin to muse about the startup information verity, which is easily accessible on the famous startup marketplaces, where no verification of startup information is carried out. Surely, it becomes apparent, when startup understands that somebody is going to learn and check its data, a principle of facilitation takes place - startup more responsibly answers the questions and gives less of unchecked and incomplete information about itself.

  • The experts, who conduct the evaluation, state that they need more information than startup gives to perform a full evaluation (and we ask startups to elaborate on the answers). However, the experience of expert participation in the projects, similar to those, startups present, allows them (experts) to see the pitfalls in the project.

  • As it turned out, it is hard enough to surprise experts. It is not once that they face up projects, similar to those startups present; they similise project with the analogue, pointing out the weaknesses and the strengths of the project. Mostly, startups already know about these projects, but not all of them sufficiently estimate their technical and market decisions relating to already existing ones. Experts pinpoint how these decisions will influence the future of a startup. Such evaluations will be useful not only for the startups but also to investors who are not so well versed in the industry that startups represent.


The evaluation structure itself requires a separate analysis (what we will do in the next article), it gives to the investor more food for thought, one very interesting effect of a short start-up assessment came about in connection with the definition of a product’s life cycle. It made it possible to more clearly determine the investing round of a startup and adjust the number of investments that a startup can count on attracting.


If we summarise the analysis of the first short evaluation, the main conclusion is that the proposed evaluation format provides more detailed and contextual information (the source of which is experts) than it can be observed in typical systems of public or non-public venture evaluation of startups. This makes the evaluation more recommendatory, provides more information for the development of a startup. The value, a startup and investor receives, goes far beyond the limits of setting the numerical value of the rating to a project on the platform. It also gives more information to the investor for making investment decisions.


We are looking for experts to cooperate with, who will be interested in startup evaluation. Drop me a line on - 


Translated by: Dmytro Basok.

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