Date mining and heuristics of finding places in restaurants: almost the same problem as with free parking

Red dots - no tables, green - there are places

The problem with getting to restaurants in Moscow at peak times is well known : you can not sit at a table at lunch for a business lunch or simply do not find a place on Friday evening.

At the same time, as you probably know, many well-known and constantly loaded establishments are inferior in quality to less promoted counterparts. The main problem is that visitors simply do not have the opportunity to learn about such places, if they are not specifically interested in them. At the same time, there is usually no time to choose a place, the choice is already on the street. Traditional restaurant mechanics - the reservation system - fails here.
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I continue to talk about crowdinvesting projects that are on the Smartmarket (I remind you - we are a kickstarter-type platform, only in the Russian Federation and with the purchase of a share in the company's profits). The solution to the problem described is the essence of the bocco startup. The idea of ​​the project is to display the workload of restaurants in real time. A resident of a large city simply pulls out a smartphone and says to his companions: “But behind this house there is a free cafe in which it is quiet and cozy. Let's go there!". They go around the line and go to a place where they can sit quietly.

About service

The first question is the suitability of the idea. The team develops the project for a long time, and during this time extensive feedback was received on the need for such a service. As we see this situation, we are: the key question of success in the quality of implementation is that information about the workload must fairly accurately reflect reality.

So, the solution is free mobile applications for different OS and website. The service shows the loading of nearby establishments and helps to find a table. To keep it “yours”, you can book it right at the touch of a button from the app.

The most difficult moment is getting load data. There are four vectors here:

• From restaurant software that can say how many tables are occupied.
• From restaurateurs themselves through a software solution from the service.
• From users of mobile applications (as in Yandex. Traffic jams: you solve your problem and share data with others). Beta, by the way, is already working.
• From open sources, for example, from social security checkers.

Plus there is another vector - the service constantly trains the expert system, which allows to evaluate the workload. It includes various external publicly available parameters, a load history (beta testers are already collecting it) and data from restaurants. As a result, the main gap is closed - the lack of data on points that do not know about bocco. Loading them is calculated algorithmically, and the accuracy of the algorithm is constantly increasing.

As mentioned above, for the user, life is quite simple: he sees a free restaurant and just goes there. If he chooses an institution in advance, he can book a table by button. The application itself will do everything that is needed. But in restaurants, booking now is not a gift, and requires quite complex operations. The team also makes a piece of software that allows you to automate the reception of armor, which greatly simplifies the work of the staff. This part of the service will be integrated with restaurant CRM systems and their software.

Now there are agreements with manufacturers of restaurant software, with restaurants (more than 10 large ones) and several partner sites. The team completes legal formalities, after which it will be able to sign official agreements with partners and name them openly.

Why crowdinvesting?

The team decided that this is the best way to raise funds for the current stage of the project. There is already a fully functional beta, many parts of the product are in the final stages of development. Sowing is no longer relevant, and the service is not running, so there are no sales, so the team is not ready for the round yet. Smartmarket is a great opportunity to bridge this gap.

Plus, given the need for active feedback, crowdinvesting will provide an opportunity to get at least a hundred invested activists who will help improve the algorithm for determining workload, as well as do feature requests and write about bugs.

What kind of team?

In the field of IT, each member of the team has serious experience. Participants worked in mail.ru, ABBYY, wildberries, CMX.

Threats

Evaluating the competitiveness of the project, we immediately asked what would happen if 4sq or Altergeo screwed the functionality literally at the moment after the service’s release. Everything is interesting here:

• For the correct display of workload by security officers, it is necessary that a substantial percentage of visitors to the restaurant check in. Now this situation is very, very far. Checks from 4sq are used as one of the algorithm's parameters - in the overwhelming majority of establishments the number of people at the same time based on chekins does not exceed a dozen during the day. Therefore, even as one of the parameters, the chekins are only suitable for a small number of institutions that are popular among the relevant audiences. As the only criterion in the foreseeable future, the chekins will be irrelevant.
• The load display service is a very local product. In the current algorithm, there are more than 20 parameters, most of which are unique for Moscow and specifically for restaurants — in other cities or for other infrastructure objects, completely different parameters will be required, other hypotheses will be applied, etc. 4sq is a global product, such an approach is impossible for them. Altergeo can theoretically repeat this work, but for them it would mean the need to catch up, so the team is not scared.

Interestingly, bocco has no plans to sell the service of one of the social networks.

The next question was about the relevance of the data . It was important to understand how the owners of the institution are objectively interested in providing data on the workload, because the excitement with the queue can be beneficial. In practice, it turned out that this is a fairly common misconception. The benefits of the service for underutilized establishments are obvious to everyone. Of course, to popular institutions, full loading is beneficial, but not a rush. Excessive loading reduces the level of loyalty to the restaurant: if a customer is denied, the establishment loses the location of such a visitor, because next time when choosing a place, he will remember that you can not sit there. Therefore, in the long run, fair display of workload is the most profitable strategy for a restaurant.

At the same time, of course, not everyone will faithfully give the data on full load. Accordingly, the task of the algorithm is to correctly predict a surplus of people in large restaurants and to give actual data from sources in restaurants with less traffic.

The critical mass of users, which is necessary for up-to-date data, will be typed for about six months after launch. At the same time, since user feedback is not the only factor, in the aggregate it will take only a couple of months to get started - and this is exactly the beta test period.

To recruit an audience, it is planned to promote applications in the stores, as well as to receive traffic from partners with whom there are already preliminary agreements.

Concrete readiness

• The server part - implemented all the functionality.
• Site - designed by, implemented static layout.
• Application for Android - implemented all the basic functionality, except for booking.
• Application for iOS - a design is developed, a prototype with the main screens is implemented.
• Product for restaurateurs - a working prototype has been implemented.
• Already collected 990 thousand rubles of the required 2.4 million, that is slightly less than half of the funds.

More details on the investment side of the project are on the Smartmarket page , plus there is also data on the team, details and a link to the site where you can subscribe to the beta.