What Do Your Residents Think About Your City’s Brand And Why Keyword Searches Can’t Help You Answer That Question

Introduction

Searching for information has become intuitive, easy, and mundane. All you have to do is open your preferred search engine, type in what you’re looking for, and hit enter. That’s it. What might have taken people hours, days, or even weeks in decades past can easily be achieved within seconds in the palm of your hand with your mobile phone. Still, even with all of the technological advancements that have been made, not everything is perfect when you search online, and this is especially the case with cities and their citizens’ sentiment towards them.

Want to Know What Consumers Want? Go Online

It’s easy to connect consumer sentiment to consumer goods. Some brands, like Coca-Cola, are old and established from the days before the shift to digital, while others, like Amazon, built their reputation thanks to the digital age. For big brands, keeping their finger on the pulse of consumer sentiment is vital to brand success, and they spend a great deal of money to know what people are thinking about them, both offline and online. The digital world has become a primary resource for gathering data on what people like and dislike, and companies rely on a host of digital tools to help them aggregate this data to understand consumer behavior and preferences. Digital tools for big brands rely on keyword searches – like “Coca-Cola” – to aggregate and analyze all brand mentions. However, unlike for private entities, these tools are weaker when it comes to providing the same type of results and information for local governments.

Why Can’t Cities Use the Same Tools?

Several factors prevent existing B2B and B2C tools, such as those used for social media management and aggregating data from those channels, from giving cities the right and relevant info needed to connect with resident preferences and feedback but a lot of it boils down to how existing digital tools and platforms use keyword searches:  

• Many general keyword searches won’t provide relevant information for city administrators because other cities or products share the same name. Instead, they’ll overwhelm the city user with an avalanche of irrelevant information that refers to anything-but-that-particular-city. For example, Springfield exists in multiple states, and in the world of TV as home to The Simpsons. A keyword search for Corona (California), competes with the brand of beer.
• Additionally, there are many more city-related mentions online that connect to local businesses, real-estate listings, or other organizations other than to topics or issues important for city management. Sifting through all of that data manually to pull out what’s relevant is virtually impossible in the big data age.
• In addition to competing names and name-duplicates, another reason it’s hard for general keyword searches to pull useful information for city management is that cities have a small audience size online in proportion to the private sector, usually just consisting of the local population that resides there and perhaps on the regional level as well, so its hard for cities to compete online.
• City websites and social media channels may not have many sites linking to them, or people actively referencing them on social media, as a consumer brand would – all things which ensure that a keyword search of a city name is unlikely to serve a city’s needs.
• Other digital resources will most likely outrank city-specific comments and information, including a Wikipedia entry on the city itself.

So what’s the bottom line? The aggregate tools out there today that use keyword-based searches to help cities understand how they’re being spoken about in the online and social media worlds are simply not tailored for cities and their algorithms for data gathering are not city-specific. They just won’t provide the same level of information and resident feedback as a city needs. Instead, they’ll cast a wide net that returns all of the types of city mentions and discussions listed above – parallel names, competing brands, and info irrelevant to city management like Craiglist postings. The majority of this data will not be relevant for city management, and the onus will lie on city staff to dig into the data overload and figure out what actually is relevant.

Getting the Right Tools

So how can a city understand its brand presence and relevance to its residents? Local governments need a different way to be able to search and analyze data to understand what people think. This is where a city-specific platform, like Zencity, can provide a city with an understanding of its online presence and outreach, and help fill the gap for cities about resident sentiment towards their local government. Using AI technology tailored for cities, Zencity can cast a wide-net but then narrow down the data more appropriately to provide the city only relevant information for city management. For example, the algorithms can automatically differentiate someone tagging a city in a photo about a pothole versus just a selfie with their friends (both mention the city but only the first is relevant to city management). Additionally, rather than relying on keyword searches, Zencity’s team of expert data analysts knows how to identify the channels where residents are most likely discussing their city – resident groups and pages, 311 hotlines, local news sources, and more – to ensure data is being aggregated from these channels, not just from the entire social media world. Zencity’s city-specific AI algorithms are able to quickly dissect, tag, and organize all the various small pieces of information into one ‘big picture’ of what residents are saying about a city, which, in turn, helps provide local governments with the ability to pursue data-driven decisions and policies based on their residents’ real needs and priorities.

Zencity’s City-Specific AI Algorithm

Conclusion

Though cities do not have the same kind of presence online as a familiar brand in the private sector, there is still a wealth of invaluable information out there that a city normally has limited resources to collect and analyze without technology. By using the power of an AI-driven, city-specific platform that provides the right information for city officials, a city can hone in, at the click of a button, on the relevant online feedback information it can use to better serve its residents, which it would not otherwise be able to do with a platform that just relies on general keyword searches.