Personalized Online Marketing Service

We conduct analyses of people on the internet and figure out what each person would like to watch, listen to, read, and buy

P — Personalisation

Wherever the user is lurking on the web, whether that be on your service, in a social network, or a third-party website, we are able to determine who he or she is, where they’re from, and what they do.

Thanks to this information, we have the ability to promote to them only content or products that they would actually like.

How it works

Data collection from various sources

Formation of a unique recommendation algorithm

Set-up recommendation display

Achieve API

“If recommendation systems are meant to do real business, then what they need to do is go full-throttle with their customer operations and operate like a channel. That’s the way Bookmate operates with E-Contenta.”
Konstantin Savenkov
Bookmate
«I would be happy to act as reference for you with potential partners. Already at our first meeting I was struck by entrepreneurial drive and grasp of what was needed for your startup to get its first traction. I think you have assembled a talented team of engineers well suited to the business you plan to build and have a clear vision for where you want to go with E-Contenta»
Simon Dunlop
Founder and CEO at Bookmate
“Considering that we are selling a service, the most important thing we build around is how the customer feels and how comfortable they are. If it is a choice or service, then we must keep it quick and efficient. If it is reading, then we most keep it convenient and cozy. That’s why the majority of our effort is directed toward usability”
Maxim Gurets
MyBook
“We monetize at the expense of the video ad. The more relevant the videos that we recommend are, the bigger the chances we have of increasing profit. For this reason, it is very important to have a reliable partner ensuring the stable operation of real time recommendations.”
Igor Shipilov
Rutube
“Technology is being tailored to what shows subscribers watch at what time. Next time, all I’ll have to do is launch the app on my smartphone and enjoy a TV show or series that now I won’t have to seek out in a sea of TV information.”
Denis Martyntsev
TvizTV
“It is surprising that the personalized film recommendations section based on the E-Contenta algorithm is opened 2.5 times more often than the same section with a selection of the most popular films.”
Yan Sloka
Vidimax
“It is very important for stores focused on customers of top clothing brands to demonstrate a high level of service. This extends to internet stores as well. A personalized approach to each customer along with personalized recommendations is all but obligatory attributes for front-running online sales companies.”
Konstantin Sinyushin
the Untitled

About Us

When I was in the 10th grade, I decided to go to the journalism school that existed on the TV channel and radio of the city of Suma located in Eastern Ukraine
When there’s a new release of Dom 2 or Tantsy, people flock to watch it. The video has a “viral” nature to it. A recommendations system comes in handy for helping to track and display these videos to other users
We didn’t have startup capital per se. We used our own funds instead. The numbers indicated to us that launching the company, including business trips and salaries cost about 40 thousand dollars. Then we got an investor.
Venture fund Untitled Retail Lab has invested $250,000 into the Russian recommendation service E-Contenta
In the Summer of last year, Facebook began keeping statistics on the length of time people spend looking at posts and viewing video content
When we first start working with a company, we offer them to try E-Contenta technology for free. We do a pilot project and we record the metrics before using our algorithm and after. According to those numbers, we are able to see how well our recommendations are working
At the moment, the market is in a state of transition: people already realize that they can’t persist operating the same way they did before
E-Contenta recommendations service, based on an analysis of people’s conduct on the internet, predicts what they will want to read, listen to, watch, and buy
At E-Contenta, we made the first version of the recommendations system for Rutube in May 2015. It entailed the following: item-based collaborative filtration recalculating the recommendations every n time, where n is a number from the Fibonacci series
When I was in the 10th grade, I decided to go to the journalism school that existed on the TV channel and radio of the city of Suma located in Eastern Ukraine
When there’s a new release of Dom 2 or Tantsy, people flock to watch it. The video has a “viral” nature to it. A recommendations system comes in handy for helping to track and display these videos to other users
We didn’t have startup capital per se. We used our own funds instead. The numbers indicated to us that launching the company, including business trips and salaries cost about 40 thousand dollars. Then we got an investor.
Venture fund Untitled Retail Lab has invested $250,000 into the Russian recommendation service E-Contenta
In the Summer of last year, Facebook began keeping statistics on the length of time people spend looking at posts and viewing video content
When we first start working with a company, we offer them to try E-Contenta technology for free. We do a pilot project and we record the metrics before using our algorithm and after. According to those numbers, we are able to see how well our recommendations are working

Interesting Side Note

The Untitled Retail Lab venture company has invested USD 250000 into the E-Contenta personal recommendations service. The transaction took place in December 2015.
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Switching over to personalized marketing is easy!