Foursquare City Guide has been the go‐to tool for discovering local gems for years, but even the most trusted platforms must adapt to meet evolving user expectations. We identified an opportunity to enhance how users refine their results—ensuring searches remain personal and purposeful—while preserving the sense of discovery that makes Foursquare so engaging.

As user behaviour shifted and personalisation became increasingly important, it became clear that filters needed to evolve to offer deeper and more intuitive refinement. This update allows users to find exactly what they are looking for and keeps the joy of exploration central to the experience.

01—Discover

Understanding the Problem

The screenshots below show that basic filtering functionality was available to users in the previous design. On the main search results view (left screenshot), users could quickly filter results by venues they had saved or liked using dedicated buttons, providing a simple way to personalise their searches. An additional button labelled "Filters" allowed users to access more advanced filtering options, and clicking this button launched a small modal overlay on top of the search results, where users could refine their search by applying up to seven different filters.

The second and third screenshots above illustrate the default state of the filters (before any selections were made) and the modal with filters selected but not yet applied. Users needed to confirm their choices by clicking "Apply" in the top-right corner of the modal for changes to take effect.

02—Define

User Research and Insights

Foursquare City Guide has always been about helping people uncover the best local experiences. Still, loyal and new users voiced a shared frustration over time: the filtering system felt limited. App Store reviews highlighted the need for more flexibility and relevance, with users wanting tools to narrow their searches more meaningfully.

This feedback drove us to take a closer look at how filtering could evolve. We pulled insights from three key sources to guide the redesign: user reviews, data on search behaviours, and an analysis of competitor strategies. These inputs revealed clear opportunities for improvement and helped us understand what users were searching for but struggling to find.

Our goal is not simply to add more filters but to create a system that elevates the experience without overcomplicating it. New filters are designed to feel intentional—helping users explore like locals while maintaining the app's ethos of discovery. We focus on enhancing flexibility while ensuring the system remains intuitive and aligned with user needs.

By reimagining the filtering experience, we can deliver a tool that balances depth and simplicity, offering users more control over their searches without sacrificing the app's hallmark sense of exploration.

03—Ideate

Filter Bar Exploration

The filter bar, positioned directly below the search bar—which housed a back arrow, search input, and map button—included three key buttons: Saved, Liked, and Filters for advanced options. While the buttons aligned neatly with the bar above, the design left significant unused white space on either side, wasting prime screen real estate.

Reimagining the Layout

This inefficiency prompted us to rethink how the filter bar could use the available space better. Our first step was to align the buttons to the left, freeing up room on the right for additional functionality. From there, we began exploring which additional filters would provide the most value to users and how to fit them into the limited space.

To guide our decisions, we ran queries to identify the most-used filters from the existing filter sheet, prioritising those for inclusion in the updated filter bar. Based on usage patterns, we selected the following filters:

• Price: To quickly sort by affordability
• Open Now: To find venues currently available
• Saved: To access user-curated lists
• Liked: To revisit favourite spots

These filters offered high utility and were intuitive for users to understand and use at a glance. However, introducing additional filters created a new challenge: they couldn't all fit into the visible space without overcrowding the bar. To address this, we introduced a scrollable carousel, allowing users to swipe horizontally to access more options. The plan was to have the filters "bleeding" off the screen's edges, signalling interactivity and encouraging users to scroll.

The scrollable carousel also required adaptive behaviours for the buttons themselves. For instance, as users scrolled, button spacing and sizing were adjusted to maintain clarity and usability. This interaction design ensured the filter bar remained functional and user-friendly, even with the expanded set of options.

The Price filter required additional consideration due to its four segments—$ (inexpensive), $$ (moderate), $$$ (expensive), and $$$$ (very expensive). To expose this granularity, we explored a mechanism allowing users to adjust the price range directly from the filter bar without navigating into the modal.

Exploring New Ways to Filter

In our previous iteration, clicking the Filters button launched a modal displaying seven additional options for refining search results. While this modal worked well for its limited scope, it quickly became clear that the design would not scale to support the expanded functionality we envisioned for the next iteration.

To kick off this evolution, we began with a team brainstorming session to explore new filter possibilities. The exercise encouraged team members to suggest anything they thought could be valuable, drawing inspiration from personal experiences, user needs, and features in competing apps. The session generated 47 filter ideas, ranging from the highly practical to the wonderfully creative.

Every idea was documented and grouped into relevant categories to identify recurring themes and patterns. This process helped us prioritise filters that would provide the most value to users while defining the scope of the next iteration. While not all 47 filters would make it into the final design, the brainstorming session was instrumental in shaping the direction of the new filtering system and laying the groundwork for a more scalable solution.

Evolution of the Modal

As we began to explore how these expanded filtering options could work, it became clear that the modal was no longer the right solution. At the time, modals were starting to age out as a preferred mobile UI pattern, and in addition to their aesthetic limitations, modals also presented practical usability challenges. Scrolling content within a modal on mobile devices could be cumbersome, as users risked accidentally tapping outside the modal and closing the entire experience.

This realisation led us to explore a new design paradigm: a dedicated content area pinned to the bottom of the screen. Recently, we implemented a similar UI element for our error correction flow on the history page—the most recent feature to be pushed live—which gave us confidence in its capability to handle other layouts. The success of this implementation reinforced our belief in its ability to house a wide assortment of filters and content, making it an ideal solution for the next iteration of our filtering experience.

We explored a three-quarter vertical height for the content area to balance increased space for options with the need to maintain a connection to the filter bar. This approach allowed us to expose more filters upfront while reducing the need for excessive scrolling. Keeping the filter bar visible above also gave users a clear visual indicator of how many filters they had applied in real-time.

Grouping and Organising Filters

While the new content area provided more space, we still had to think critically about how to group and display the filters. The goal was to make the system more intuitive by ensuring filters were easy to scan, logically organised, and visually apparent. To achieve this, we explored several iterations of grouping content, focusing on three key considerations:

• Visibility and Scannability: To minimise user effort, filters needed to be quickly identifiable at a glance.
• Logical Organisation: Related filters were grouped to create a sense of hierarchy and flow, reducing cognitive load.
• Headings and Icons: Visual treatments, such as subheadings and accompanying icons, were tested to enhance clarity and improve aesthetics.

We experimented with different ways of structuring filter groups through sketches and wireframes, testing layouts, and prioritising usability and readability. This process allowed us to refine the design until we arrived at a cohesive, functional, and scalable solution.

Inline Suggestions for Smarter Search

Starting a search can often feel overwhelming, especially when users aren't sure what they're looking for. This can be particularly true for broad terms like lunch or dinner. While the filter bar and sheet offered general refinements, we wanted the app to continue to guide users towards more specific results without requiring extra effort on their part.

The idea behind Just Show Me was to introduce an inline category filter to provide users with an easy way to refine their search and discover tailored results quickly. For instance, a user searching for lunch might see suggestions for cuisines like Southern Soul Food, Italian, Mexican, or Vegan.

By dynamically funnelling users into specific paths, Just Show Me could simplify their decision-making and transform broad, ambiguous searches into more focused and actionable ones. The feature would inspire users who weren't sure what they wanted while making the search process intuitive and approachable.

04—Test

Testing and Feedback

We started with low-fidelity prototypes to focus solely on functionality, using black-and-white wireframes to test the core interactions. These prototypes were shared internally with employees, who provided quick and actionable feedback during team reviews. This process helped us refine the design early on and address usability challenges before progressing to more polished iterations.

Once the core functionality was solidified, we expanded testing to include our Superuser community. By leveraging their expertise, we gathered detailed feedback on how the inline suggestions performed in real-world scenarios. Superusers submitted feedback via Slack, sharing annotated screenshots, recordings, and written insights that helped us uncover edge cases and improve the overall experience.

This feedback loop, starting with internal reviews and expanding to external input, allowed us to iterate quickly and ensure the feature struck the right balance between guiding users and maintaining a seamless search experience.

Design Revisions

05—Release

Room for Improvement

One potential improvement could involve accommodating recently used filters directly on the filter sheet. By surfacing filters users frequently interact with, the experience would become faster and more intuitive, especially for repeat searches. This section could dynamically populate with the last 2–3 filters applied, saving users time by eliminating the need to scroll or search through the complete list again.

Another opportunity could be providing more context within the Just Show Me feature for ambiguous searches. Inline suggestions could include subtle explanations for why specific categories are recommended. For example, if Mexican food appears as a suggestion under lunch, a small line of text such as "Popular in your area" or "Based on your search history" could provide additional transparency and confidence.