Citibeats, a social trends monitoring tool for governments and businesses, wins €1.4m funding

© Citibeats/Social Coin

Citibeats tracks and analyzes what the public is saying online in any language; wants to boost its presence in LatAm and Asia 


Founded in Barcelona just two years ago, social trends monitoring startup Citibeats has already launched over 30 projects worldwide. From social impact work in Latin America, tackling natural disasters in Japan to providing information to financial entities in Europe, Citibeats helps clients manage their risk, and improve their compliance monitoring and service delivery.

The startup uses natural language processing and machine learning to collect and analyze public opinion in any language and from thousands of sources, including social media, before structuring the data for its clients and partners. This helps the organizations to better anticipate risks and respond more quickly to user needs.

The company's technology had its origins as the AI platform for Social Coin, a social movement that began in 2013 in Barcelona to enable governments and public institutions to reward citizens for community initiatives and actions with “social coins” that can be spent at local businesses.

Citibeats is already working with some of the largest banks in Spain and is eyeing more projects in Latin America. On December 11, it announced a new funding round of €1.4m from Inter-American Development Bank's IDB Lab, H&S Investment in Germany, and Bankinter, Everis, Telefónica Wayra and the IESE network of angel investors in Spain.  

CompassList interviewed Citibeats' CEO and founder Iván Caballero last month at the Smart City Expo World Congress in Barcelona.

This interview has been edited for length and clarity.

Q: How did the idea of Citibeats come about? What is its relationship with Social Coin? 

Ivan Caballero: Citibeats is the result of an investigation that started at the beginning of 2018 and one year of R&D in collaboration with the Massachusetts Institute of Technology (MIT) and ESIC Business and Marketing School, financed with grants from EU Horizon 2020.  

We had one person in-house from the MIT who helped us develop the Citibeats concept, while the pure research in the AI field was developed in conjunction with ESIC. We deploy AI to process large amounts of data based on text analysis. 

The insights we provide out of this analysis are helping governments and companies to provide a responsive and real-time reaction to people's needs in a concrete region. Social Coin was an amazing project, but we struggled a lot in monetizing it and making it sustainable in the long term. Social Coin owns 100% of Citibeats.

With Citibeats, we see an opportunity: we are not giving up our social impact side, which is the DNA and foundation of the company; and at the same time we’ve found a way of making something scalable, profitable and with a direct impact on society. 

Which technologies are deployed by and define Citibeats?  

We mainly use three technologies: data collection, data processing and delivery of insights. We developed a native technology that allows us to connect to multiple data sources, RSS, social media, blogs and platforms. We are data agnostic, which means we can collect any open data based on text from Twitter to proprietary data of our customers, such as governments and private companies. 

The data processing is based on an algorithm developed in-house, which allows customizable categorization by topic. It is powered by machine learning, based on profiling our users by basic social demographics. 

We also geolocate and synthesize text, meaning that for any given category, we can extract a concrete piece of text that is representative of all the other texts.

In the third and last part of the process, we deliver data to our clients through our API, reports, dashboard and alerts, for a given topic or sentiment.

What is your business model?  

We license the platform to companies and governments. Depending on the sources and the volume of data that needs to be processed, our pricing varies significantly.

We proved that our platform is language agnostic

With Citibeats, you moved into the B2G sector. What are the greatest differences that you have found and challenges you have faced in working with public institutions, versus the private sector?  

Public entities are pretty much conservative and tend to be limited by regulation. Risk aversion and the complex structure of these entities are the biggest differentiating aspects. Still, although we are offering our services on both B2B and B2G levels, our best market fit, based on Citibeats’ mission, is the public sector.

Which is the project that you are proudest of? Would you like to share any metrics or milestones?  

Two years ago, we won the Open Innovation Contest of NTT Data in Japan. They selected us from 1,000 startups worldwide. We started the collaboration by connecting our platform to NTT Data’s. For us, this implied a huge challenge because although our platform is language agnostic – meaning that we can work with any language from any data point – we had never tested it with the Japanese. We didn’t know what to expect. But we connected and they said it worked very well! 

That was a huge milestone for us, because not only we managed to establish a connection between our platform and NTT, which is a huge company, but also because we proved that our platform is language agnostic.  

We’ve been working on very unique projects. For example, Japan is a region that is affected by many natural disasters, especially in the rural areas. The country’s Ministry of Infrastructure has problems detecting which infrastructures are damaged from natural disasters, such as flooding. 

In this case, our technology helped monitor what tourists traveling throughout the country were saying across channels. We provided the information to the Ministry of Infrastructure with a list of prioritized actions that had to be performed. That’s beautiful because we were using humans as sensors, with a positive impact.

In winning the NTT Open Innovation contest, you proved the scalability of your technology. How did you manage to achieve this in such a short period of time?

We were born international by default. Since the very beginning, our technology has been designed based on two pillars. First, it should be an ethical AI, and secondly, we wanted to understand what people need in real time and to be able to understand everyone means understanding every language.  

One Wednesday, one of our investors, Everis [an NTT Data company headquartered in Madrid], called me and asked me to pitch in a contest that very Friday. Pitching is part of my job, so I said yes. It turned out that we were selected to pitch together with 10 other startups from all over the world. 

We went to Japan to pitch at the NTT Open Innovation Contest and we won. This gave us the opportunity to work and develop a project with NTT Data. Japan was the least obvious market for us, but the project helped prove that our technology is ready to scale internationally and we can do business at the highest level. 

What projects have you carried out with NTT Data to date?

We developed a project in the surrounding area of Fukuoka, checking what people’s needs immediately after the earthquake. From the information we gathered you can use data to create predictive models for future cases. Our technology is embedded in NTT Data solutions so that they can work completely autonomously. By now they have good knowledge of our technology and have already started to offer our solutions to their clients.  

The point for us is to help our clients quantify subjective SDGs

And what about projects that Citibeats is carrying out in the public sector?

We are currently working quite actively with Dublin. We also started to collaborate with IDB Lab in Latin America, analyzing immigration from Venezuela to nearby countries and social problems in Chile. 

In Spain, we work with the region of Catalonia, and currently we are working with Telefonica to cross and compare their telco data with our data to produce a report that will help to improve the way flooding in Valencia is managed. This is a very interesting project because it mixes qualitative and quantitative data, whereas we usually transform qualitative data into quantitative ones.

What milestones are you looking to achieve in 2020 in term of expansion and projects? Are you looking to open offices abroad?

In 2020, we are mainly expecting to close between 30 and 50 projects in Europe in the public and private sectors. We will also be exploring retail solutions mainly in Asia through NTT Data and in Latin America with public institutions.  

Right now, we are a team of 14 people. We will be looking to reach a total of 30 people by the end of 2020, with new hires in the areas of IT and business development.  

What about partnerships? Have you established any?

We normally expand and work through partnerships. We can sell directly via a pure B2B model, but since our technology can be embedded in complex architecture we tend to work with big consultancy firms, data companies and system integrators.

To date, we have worked with firms like Accenture, PwC, Everis and Telefonica. So in our expansion plan, we are going to hire local talents; but we will be also looking for local partners that understand well the markets we want to enter.

Talking about smart cities, what is, according to your experience, the governments or municipalities that are doing their best to meet Sustainable Development Goals (SDGs)?

Here in Spain, cities like Barcelona, Madrid and Valencia are very active. Malaga is currently injecting a lot of money in Smart Cities projects but that doesn’t necessary mean being aligned on SDGs. 

In Europe, cities like Amsterdam and London are doing amazing jobs when it comes to Smart Cities. The city of Dublin is comparing its GDP with an index they created, thanks to our report; they call it a social index. This is an approach we like because GDP has been always used as an indicator of wealth but can actually be about many other things. All the information we collect puts GDP into context, especially when it comes to social well-being.

I think that everybody is doing what they can based on their level of understanding of SDGs and also as every city has its own value propositions. If a city’s value proposition is mobility, the city will certainly work toward this direction. 

The point for us is to help them quantify subjective SDGs. There are some goals that are not easily measurable and this is where we try to help. 

We seek to empower a responsive society, which means we collect the data and quantify these data sets in order to provide accurate answers to citizens´ questions.

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Edited by S. Mani

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