The Center for Data Innovation spoke with Eyal Feder-Levy, chief executive officer and co-founder of Zencity, a company based in Israel, which uses AI to collect feedback from citizens and generate insights for city governments. Feder-Levy discussed how cities are using Zencity’s technology to gather information from their constituents, incorporate it into decision-making processes, prioritize resources, and improve services.
Eline Chivot: How did the idea of Zencity come about, and what do you think makes it stand out?
Eyal Feder-Levy: The main goal of what we do is to help local governments make better decisions. The way we’re looking at it is that we believe good decisions are those based on residents’ feedback on the one hand, and decisions that are data-driven on the other. We want to bring those two elements together in a way that is usable and comfortable for local government organizations. The idea came from the experience my co-founder and I had working with local governments. We saw that they collected residents’ feedback using tools such as surveys and town hall meetings. We were surprised at how these tools were very anecdotal, limited in scope, and not data-driven, despite the fact that important decisions had to be made based on these tools.
Zencity is different than other systems in that we bring a very wide scale of input and engagement from people because we analyze data that is already out there, and do not create new datasets, we can actually reach a much higher volume of engagement than any other existing solution. For example, in a city like Houston has 4.2 million inhabitants, we manage to engage about one million of them every month.
Today we work with 75 cities in four different countries—mostly in the United States where we work with the cities like Houston, Chicago, and Fort Worth. We also have a presence in Eastern Europe and in Israel, in Jerusalem and Eilat, which was the first city to adopt Zencity.
Chivot: Monitoring social media to understand people’s opinions and sentiments is common practice for many businesses, but much less so among local governments. How can Zencity play a role in changing that?
Feder-Levy: I think it’s mostly a matter of transition. The reason why a lot of private sector organizations have already gravitated towards becoming more data-driven holds to what is now expected from businesses. For instance, looking at my day-to-day, if I don’t show the data to my investors on how much revenue we’re generating, our spending in marketing, etc., I would probably lose my job. That is the standard our sector is used to, while nobody has been holding government organizations to it so far, so there has been no pressure to move. But the new generation of people in government—they’re younger, or have another state of mind—is really pushing forward in raising awareness about the value and use of data-driven approach. That is a very interesting trend that coincides with the fact that the public—that is, governments’ clients—is becoming more demanding, asking governments to justify its actions, spending, and priorities.
This transformation is happening across the board: We see it in Latin America, in Europe, in Israel, in North America. Although overall, the desire to be data-driven is becoming more and more apparent, there are cultural differences of course, for example the emphasis on privacy, which is huge in Europe and is picking up in other regions. Because of those sensitivities, we have designed our platform to be very privacy-aware from the start and anonymize all the data we collect. We do not keep personally identifiable information (PII) in our database so data could be purely used to identify trends, changes, and the collective sentiment and not personal issues.
Another cultural difference is one that’s in terms of political accountability and the type of regime, which makes the U.S. market different than China’s. We see ourselves working mostly in the markets of those countries that are democracies and have free speech. Their system makes us more effective, and ensures our data is used for a good purpose, to provide better services to residents. Markets that are less appealing are those carrying the weight of our data being used in ways that we wouldn’t want it to be used.
Chivot: I’ve read that Zencity wants to be “the Google Analytics for cities.” What does that mean? Can you give an example of how a city has successfully used your solution to address a concrete issue?
Feder-Levy: Our main goal is to provide insights and scores that decision-makers need when making different types of decisions, whether it’s going to the city counsel to support a project, building a budget, and deciding on spending. We provide relevant information through a dashboard, which different people, including citizens, can access through a mobile app or an alert system that sends information in real-time. It is used for performance management, to see a cause and effect relationship between actions that happen and the city took, and the impact that had on sentiment. The metaphor for Google Analytics works this way: If you were to change the design of your website, more people will be clicking on a button or visiting your website, and we want to give that same experience to the city management. For example, when the city launches a new bike path, we tell them how sentiment has changed because of that particular event. Our tool allows to assess that on a very wide scale—across the city.
One of my favorite examples is our work with Cary, North Carolina, where city managers have used our platform to inform their policy before deciding on it, and used it again to track whether their decisions proved successful and impactful. When electric scooters began operating, unannounced, Zencity helped Cary in its strategic approach to manage this. The city wanted its recommendations to the town council to be supported by data about the benefits of e-scooters for the community, as well as the operational and safety challenges they posed. Neighboring cities had been heavily regulating e-scooters, but Cary did not just want to look at anecdotal experiences of others. Cary also wanted to gather their own citizens’ feedback. The city opted for a so-called “wait and see” approach, and used Zencity over a span of three months to track sentiment and discourse around e-scooters, to better understand perceptions of its residents. Our platform aggregated city-wide resident-generated data points from sources such as local news sources and social media. We used advanced AI to categorize and sort the data, and to automatically identify and filter comments. We tagged and scored those as either negative, positive, or neutral. We quantified citizens’ sentiment towards e-scooters, and visualized the data on the platform. We used this data to show how the public responded to the city’s decision, but also the long-term impact of e-scooters. This approach was well received, and gave the city’s council the confidence to make a choice to allow e-scooters to operate.
Chivot: One particular challenge we see includes obstacles that cities face in collecting and sharing data to improve their services. How does Zencity help in overcoming that?
Feder-Levy: To empower processes in government organizations, we started off by looking for data that could really power interoperability, or work across different departments and areas of the same organization. This is why we chose sentiment, as it needs to be taken into account across different teams—the same way revenue needs to be, in a private sector company. There are many challenges to sharing and exchanging data, but there are more and more off-the-shelf tools that allow to do that easily, and more and more datasets that could ultimately power all types of decisions. Most of the data we analyze isn’t owned by the city, it is automatically gathered from multiple open-data sources where residents interact, such as social media for instance. This diversity of sources allows to create interesting use cases. A lot of that data has been previously unexplored. The world is very rich in data. Somewhere out there in the public domain, there is probably a dataset that is relevant to any question we want answered.
Chivot: How do you plan to improve and expand Zencity in the future?
Feder-Levy: Our goal is to become a standard of how local governments, big and small, make decisions. We want to help as many organizations as possible, to accompany them in their transition towards implementing data-driven processes. We will add more types of data into our analysis to cross-reference with sentiment, so we can really power different types of decisions—whether it’s data about mobility, waste management, spending, economic activity, etc.—which would make our tool ever more useful to more stakeholders across a city organization.