Parsers is the first startup to have undertaken preliminary evaluation on the Rocket DAO platform conducted by Rocket DAO experts.
This evaluation is conducted for 4 crucial parameters:
As for Parsers, the results of the evaluation are as follows (note, that evaluation is conducted in 10-points scale):
Via this link you can get a detailed insight about the project and expert opinion about it based on the Preliminary evaluation results:
To understand better what actually influenced such good results of the evaluation, we decided to take an interview with the founders of Parsers for our media Startup Jedi.
Here we are to share it with you!
People will stop clicking the links from the search results. Here is the “contributor” to the crisis.
“Google is like Stalin — you give him a word, he gives you a transportation (meaning — link)”. The joke has been topical for a quarter-century and it is time to reform the concept. New-generation searching method will give specific information instead of links to the user. A Belarus-born startup Parsers is one of the those who change the approach to the web-search.
Today, the team offers a browser extension that allows to extract and visualize unstructured data from web pages without programming skills.
It is enough to select the relevant data on one page. The service will automatically find similar ones by a given pattern. Do you need to collect 100 thousand News Banners? Parsers will find them and present in a structured single-fashioned table.
The algorithm can collect links, images, texts, tables and scripts. The structured data in the form of tables or charts can be downloaded in different forms — from the website or by API. An automatic parsing can be configured on a schedule. This may be convenient for comparing the prices, as an example.
The service sells on subscription. The price depends on the amount of collecting information. The free subscription allows to process up to a thousand pages on one site. The most expensive subscription plan allows perfecting 100 thousand pages for the cost of $199 per month.
Microsoft, Cisco, eBay and other big companies use the Parsers product, but the company does not intent upon to stop on a simple parsing on a request. Their agenda is much loftier. Evgeniy Gurinovich, a founder of the company, has a detailed story hereinafter.
We are moving towards creating a new search model when a person receives an answer to his question immediately and does not spend plenty of time on extending the information from the multiple links in a search engine. Practically, all search engines are engaged in parsing. The word parsing is usually replaced by the indexing, still, the essence remains the same. Search engines parse everything, and it is unstructured information.
There is the form of the requests’ result that users get. Browsers give a link to a page where something similar to the query exist. If you ask “How much does the iPhone cost?”, the search engine won’t show an answer on the page, it will send you searching the sites yourself. Search engines do not know where the price is on the site, and especially, if there is any.
They cannot determine what gets in their base. Website structures are so diverse, that it is impossible to use the technical solution to distinguish the price of goods, their weight, color and other parameters. Only a human is capable for it, in spot even not all of them. Yet, it is possible to automate the process partially.
Google and Yandex are far too big to change the search model at short notice. Nevertheless, in small steps, they move to establish a search on structured data and launching SERP (Search Engine Result Page) features as “searchster”, “Goodies”, “instant answers”. Yet, it remains on the basis of the individual sites, not the entire Internet as a whole.
The unmentioned cases show that this approach works. Users feel convenient getting answers immediately, without any extra clicks. That much convenient, that Avito, CIAN, “2ГИС” recently complained about Yandex “searchsters” that take up to half of the overall traffic from them.
We are following the way of creating the structured data output based on the unstructured data collection. We already have a search engine for companies. This is a beta version. We collected data from the internet on 130 thousand businesses and continue seeding the database now.
For user, it is enough to open one webpage in order to see all the necessary information. It solves the problem of opening dozens of tabs in the browser. Voice assistants also work with structured facts.
This January we entered the Product Hunt and were ranked the 2nd in the top. The high rank on Product Hunt allowed to almost double the number of active users. This result hinges not only on the direct transactions from the Product Hunt site itself but also on the numerous articles on the foreign websites during the next few weeks.
The first month, the number of users increase reached 30% per week. By the second month, after Product Hunt launch, the growth naturally decreased to less than 10% per week. In sober fact, an absolute figure of users has noticeably increased. Even now, users come from Product Hunt and website reviews that came out after we entered the platform.
From the very beginning and still, the main users’ attraction channel is an organic growth at the Google Chrome Store. The Google Chrome Store promotion methodology is very similar to Apple and Android stores. We optimize pictures, descriptions and other elements.
We significantly increased the number of users from the search engines to the website. We constantly test the new channels and see the great progress of others that will give a sizable influx in the future.
Everything connected with the Internet search, intercrosses with big companies’ interests, such as Google and Yandex. However, our archrival is the Diffbot company.
This company collected the database of more than 3 trillion structured facts. At the same time, a similar Knowledge Graph from Google contains one order less. Diffbot focuses on B2B sales, its clients are Cisco, Amazon and U.S. government.
Diffbot has attracted $10 million in round A, being estimated over 100 million. Analogous startups preferred to exit. Software developer Palantir Technologies went off to Kimono Labs and technical giant IBM bought AlchemyAPI.
At the beginning of July, we launched the companies search. We will keep a close eye on the users’ feedback, expand the data and add new data types. There is just the initial version of the search engine that would work for B2C and look different in the future. Although, even now it is much easier to find some information about the companies. If you are making a list of investors, just choose the Venture category and get the list that may be segmented by countries and other criteria.
We will add the search by product, real estate, events and other sections. After all, all sections will be combined with the simple search engine interface.
As for today, we develop the product for personal resources, negotiate with investors and already have a potential one. It is important for now to choose the investor that will help us improve the USA and East European market positions. For us, it is more important to modify the product that is easy to scale and develop in the future, than to get one-minute profit now.
Teams that plan to work with data structuring should understand that they need huge amounts of data. Think through how you will collect, store and process it. You must have a unique solution to at least one of these questions. Otherwise, the project’s economy will not converge.
The high rank on Project Hunt Top-day is closer if you follow certain rules. Most of them are described in details in the relevant recommendations. We add some obvious ones.
The rest depends on your product, the commentators’ approof and luck. Launching of other cool products on the same day can do bad favor to you.
Author: Valentin Mihaltsev.
Translated by: Dmitro Basok.