{"id":2968594,"date":"2026-06-15T14:56:38","date_gmt":"2026-06-15T21:56:38","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2968594"},"modified":"2026-06-18T11:18:33","modified_gmt":"2026-06-18T18:18:33","slug":"how-people-decide-designing-results-for-nearby-searches","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/instant-apps\/decision-support\/how-people-decide-designing-results-for-nearby-searches","title":{"rendered":"How People Decide: Designing Results for Nearby Searches"},"author":425640,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[37141,22841,22941],"tags":[313412,780442,773722,480102,33131],"industry":[],"product":[760042],"class_list":["post-2968594","blog","type-blog","status-publish","format-standard","hentry","category-decision-support","category-local-government","category-mapping","tag-arcgis-solutions","tag-data-design","tag-improve-workflows","tag-nearby","tag-tips-and-tricks","product-instant-apps"],"acf":{"authors":[{"ID":425640,"user_firstname":"Mav","user_lastname":"Tucker","nickname":"Mav Tucker","user_nicename":"mtuckeresri-com_esriinc","display_name":"Mav Tucker","user_email":"mtucker@esri.com","user_url":"","user_registered":"2025-12-03 14:42:36","user_description":"Mav is an Esri Solution Engineer on the State and Local Government team. Mav has over a decade of experience with ArcGIS with a lot of time logged optimizing Enterprise workflows and debugging python.","user_avatar":""}],"short_description":"Explore a pattern for rethinking what an ArcGIS Instant Apps Nearby result represents \u2014 matching how real users make decisions.","flexible_content":[{"acf_fc_layout":"content","content":"

The <\/span>ArcGIS Instant Apps Nearby template<\/span><\/a>\u00a0is a powerful, ready-to-use tool.\u00a0It\u2019s\u00a0fast and effective at helping people understand what exists around a location, making it\u00a0a good choice\u00a0for\u00a0providing\u00a0public-facing search capabilities.<\/span>\u00a0<\/span><\/p>\n

In many cases, that’s exactly what users need.\u00a0In others, like\u00a0feature-dense environments,\u00a0interpreting the results can become difficult.\u00a0Often in these\u00a0situations\u00a0users\u00a0aren’t\u00a0really trying to\u00a0explore,\u00a0they’re\u00a0trying to decide. That distinction turns out to matter quite a lot for how Nearby results should be built and shown.<\/span>\u00a0<\/span><\/p>\n

I ran into\u00a0precisely\u00a0this while deploying the Public Parking solution for the City of Columbia, Missouri<\/a>.<\/span><\/p>\n"},{"acf_fc_layout":"content","content":"

Nearby as a starting point in downtown Columbia<\/span>\u00a0<\/span><\/h2>\n

Columbia is a city of about 130,000 with an active downtown bordered by two colleges and the University of Missouri, whose SEC football program draws large numbers of visitors on game days. Significantly more than in similar-sized downtowns, the people navigating Columbia are unfamiliar with the area, and even less familiar with how parking works here.<\/span>\u00a0<\/span><\/p>\n

On-street parking can play\u00a0a big role\u00a0in the downtown visitor experience. There are over 1,500 metered parking spaces clustered along downtown blocks, each governed by a traditional parking meter. As we deployed\u00a0<\/span>Esri’s Public Parking solution<\/span><\/a> and began working with our data in the public-facing app, our assumption was that those meters would be the features returned in a search. That would keep us from having to\u00a0maintain\u00a0additional\u00a0individual parking space features, which would require a relationship\u00a0to\u00a0their governing meters, or duplicate (and\u00a0maintain!)\u00a0many\u00a0attributes.<\/span>\u00a0<\/span><\/p>\n

When we tested our parking space proxy theory,\u00a0Nearby\u00a0did exactly what\u00a0it’s\u00a0designed to do. When a user searched near a destination, even when zoomed into just a few blocks, the app returned\u00a0accurate, proximity-based results for every nearby meter. Hundreds of them. From a data perspective,\u00a0it\u00a0was\u00a0accurate, but from\u00a0a\u00a0user perspective\u00a0it was\u00a0way too much!<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2968680,"id":2968680,"title":"Meter Nearby Results","filename":"Picture5-1.png","filesize":190995,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture5-1.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/instant-apps\/decision-support\/how-people-decide-designing-results-for-nearby-searches\/picture5-71","alt":"Nearby search results using individual meters as the search features, returning 83 results \u2014 2 Lots and Garages and 81 Meter Times \u2014 shown as a long, repetitive list of 1 Hour and 3 Hours entries differentiated only by distance.","author":"425640","description":"","caption":"","name":"picture5-71","status":"inherit","uploaded_to":2968594,"date":"2026-06-02 19:41:10","modified":"2026-06-02 19:42:54","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1329,"height":858,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture5-1-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture5-1.png","medium-width":404,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture5-1.png","medium_large-width":768,"medium_large-height":496,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture5-1.png","large-width":1329,"large-height":858,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture5-1.png","1536x1536-width":1329,"1536x1536-height":858,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture5-1.png","2048x2048-width":1329,"2048x2048-height":858,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture5-1-720x465.png","card_image-width":720,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture5-1.png","wide_image-width":1329,"wide_image-height":858}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture5-1.png"},{"acf_fc_layout":"content","content":"

Reframing\u00a0our\u00a0driving\u00a0question<\/span>\u00a0<\/span><\/h2>\n

It was clear that\u00a0the issue wasn’t\u00a0accuracy\u00a0or performance.\u00a0Nearby was answering the question it knew how to\u00a0answer,\u00a0it just\u00a0wasn\u2019t the one our users were\u00a0actually\u00a0going\u00a0to ask.\u00a0Downtown visitors\u00a0want to know “where should\u00a0<\/span>I<\/span><\/i>\u00a0try parking near my destination?” not exactly where every parking space or meter lives.<\/span>\u00a0<\/span><\/p>\n

In this shift, distance still matters, but it\u00a0isn’t\u00a0the\u00a0entire decision. Once someone\u00a0identifies\u00a0a place to park, other questions\u00a0immediately\u00a0follow. How long can I leave my car there? Do the rules change after business hours? Presented with hundreds of\u00a0nearly identical\u00a0meters, users had all the information, but less clarity about what they should do.\u00a0The challenge\u00a0wasn’t\u00a0helping people find\u00a0any and all\u00a0parking,\u00a0it\u00a0was helping\u00a0them\u00a0identify\u00a0an option\u00a0that would meet their needs.<\/span><\/p>\n"},{"acf_fc_layout":"content","content":"

From inventory to options<\/span>\u00a0<\/span><\/h2>\n

Facing this\u00a0reality, it was necessary to step back again and ask what a single search result should\u00a0represent\u00a0when someone is researching downtown parking.<\/span>\u00a0<\/span><\/p>\n

Answering this question required us to rethink the role our features were playing in the search experience.\u00a0While individual meters and spaces were essential for internal operations, they\u00a0weren’t\u00a0the right unit for people looking for parking. What we needed was a different kind of feature, one whose primary purpose was not to\u00a0represent\u00a0an asset, but to\u00a0represent\u00a0an option. We needed “decision features.”<\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"content","content":"

Building decision features from assets<\/span>\u00a0<\/span><\/h2>\n

1. Define the decision unit<\/span><\/h3>\n

Before touching schema, we focused on defining a decision unit. A good decision unit is something a person can\u00a0reasonably compare\u00a0to another option and say, “I’ll try this one instead.” In downtown Columbia, that unit turned out to be a\u00a0block\u00a0face: one side of one block on a street.<\/span>\u00a0<\/span><\/p>\n

Technical work: we created another feature sub-type of “On-Street Aggregated” in the Public Parking layer\u00a0along-side\u00a0sub-types of “lots” and “garages” for our decision feature, since this layer already had the\u00a0attributes\u00a0someone looking for parking would care about<\/span><\/i>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"content","content":"

2. Grouping assets<\/span><\/h3>\n

In Columbia, block-level descriptions were already part of how parking was discussed. Street name, block number, and side of the street appeared in parking department spreadsheets, and in everyday conversations about where someone might try to park. These concepts became the attributes we used to define our parking decision features.<\/span>\u00a0<\/span><\/p>\n

Technical work: we added “Block” “Street Name” and “Street Side” fields (with domains) to the features involved to act as a compound key relating the pieces together<\/span><\/i>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2968682,"id":2968682,"title":"Compound Key Fields","filename":"Picture1-1.png","filesize":59763,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture1-1.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/instant-apps\/decision-support\/how-people-decide-designing-results-for-nearby-searches\/picture1-174","alt":"Three string fields \u2014 Block, Street Name, and Street Side \u2014 added to create a compound key. Street Name and Street Side use coded value domains with 40 and 4 values respectively.","author":"425640","description":"","caption":"","name":"picture1-174","status":"inherit","uploaded_to":2968594,"date":"2026-06-02 19:45:18","modified":"2026-06-02 19:46:00","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1281,"height":238,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture1-1-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture1-1.png","medium-width":464,"medium-height":86,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture1-1.png","medium_large-width":768,"medium_large-height":143,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture1-1.png","large-width":1281,"large-height":238,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture1-1.png","1536x1536-width":1281,"1536x1536-height":238,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture1-1.png","2048x2048-width":1281,"2048x2048-height":238,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture1-1-826x153.png","card_image-width":826,"card_image-height":153,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture1-1.png","wide_image-width":1281,"wide_image-height":238}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture1-1.png"},{"acf_fc_layout":"content","content":"

3. Where do they live?<\/h3>\n

Another important choice was where these higher-level features should appear on the map. Rather than allowing decision features to inherit the coordinates of a single meter, we introduced a small set of block-level anchor points, one per block face. These anchor points define where a parking option appears in search results, and remain stable even as individual meters are added, updated, or removed. This consistency is a small detail, but limiting unnecessary change helps maintain user confidence and makes it easier to compare parking data over time.<\/p>\n

Technical work: we created another feature sub-type in the Public Parking layer for our block anchors, and placed and attributed (including our compound key attributes) one per block face<\/em><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2968683,"id":2968683,"title":"Block Anchor Form","filename":"Picture2-1.png","filesize":64729,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture2-1.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/instant-apps\/decision-support\/how-people-decide-designing-results-for-nearby-searches\/picture2-110","alt":"Edit form for a block anchor point in the Public Parking layer, with Type set to Blocks and the three compound key fields shown in the Location group. Street Name uses a dropdown populated by a coded domain (set to Cherry), Block is a text input (set to 700), and Street Side uses radio buttons for North, East, South, and West (set to North).","author":"425640","description":"","caption":"","name":"picture2-110","status":"inherit","uploaded_to":2968594,"date":"2026-06-02 19:46:26","modified":"2026-06-02 19:47:05","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":529,"height":839,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture2-1-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture2-1.png","medium-width":165,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture2-1.png","medium_large-width":529,"medium_large-height":839,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture2-1.png","large-width":529,"large-height":839,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture2-1.png","1536x1536-width":529,"1536x1536-height":839,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture2-1.png","2048x2048-width":529,"2048x2048-height":839,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture2-1-293x465.png","card_image-width":293,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture2-1.png","wide_image-width":529,"wide_image-height":839}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture2-1.png"},{"acf_fc_layout":"content","content":"

4. Aggregate thoughtfully<\/h3>\n

To build the decision features themselves, we aggregated the underlying meter inventory that participated in each block face. Crucially, aggregation stopped where differences mattered. Time limits, for example, directly affect whether a parking option will work for someone’s visit, so meters with different maximum time limits were not forced together into a single result. The focus was on organizing information without burying important distinctions.<\/p>\n

Technical work: we built a Python script that iterated on the block anchors, queried the “related” meters, and built the aggregated decision features. bonus: we had additional feature types not otherwise discussed here that were added to these decision features, via the same compound key, so we could add information to blocks that had other attributes like a ride-share stand that would mean spaces on that block were unavailable during certain hours<\/em><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2968684,"id":2968684,"title":"Block Point Search Result","filename":"Picture3-1.png","filesize":143457,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture3-1.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/instant-apps\/decision-support\/how-people-decide-designing-results-for-nearby-searches\/picture3-95","alt":"A single Nearby search result for a decision feature: 3 Hours, 300 block of S Ninth, West side. The expanded pop-up shows aggregated details including meter bank, space count, accessible space availability, location, rates, accepted payment methods, enforcement hours, and block-level restrictions from a taxi stand affecting four spaces.","author":"425640","description":"","caption":"","name":"picture3-95","status":"inherit","uploaded_to":2968594,"date":"2026-06-02 19:47:37","modified":"2026-06-02 19:48:15","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":442,"height":1076,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture3-1-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture3-1.png","medium-width":107,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture3-1.png","medium_large-width":442,"medium_large-height":1076,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture3-1.png","large-width":442,"large-height":1076,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture3-1.png","1536x1536-width":442,"1536x1536-height":1076,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture3-1.png","2048x2048-width":442,"2048x2048-height":1076,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture3-1-191x465.png","card_image-width":191,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture3-1.png","wide_image-width":442,"wide_image-height":1076}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture3-1.png"},{"acf_fc_layout":"content","content":"

5. Keeping decision features in sync<\/h3>\n

Of course, this couldn’t be a one-time transformation. Meter inventory changes regularly as construction projects temporarily remove or occupy spaces, timing rules are adjusted to optimize usage, or long-term rentals are negotiated for hotel valet and other business uses. To keep our decision features in sync with our authoritative inventory, we built a zero-input, lightweight Python web tool. Every time parking staff makes meter changes, they use an inventory management Experience Builder<\/a> app to record it. Just one more button click sets off the aggregated feature update process, so editors continue to work only directly with individual meters, and the public-facing Nearby app reliably reflects those changes without additional work.<\/p>\n

Technical work: we turned the Python script into a notebook and published it to a web-tool, and used the analysis widget in the inventory management Experience Builder app to give access to parking employees. The tool has no inputs and runs on the standard Python runtime. bonus: we added some data validation checks to the tool, and if any of the conditions were triggered we wrote them out to a separate feature layer, then displayed the validation text to the user in a list widget underneath the web tool results<\/em><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2968685,"id":2968685,"title":"Web Tool in Experience Builder","filename":"Picture4-1.png","filesize":46336,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture4-1.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/instant-apps\/decision-support\/how-people-decide-designing-results-for-nearby-searches\/picture4-90","alt":"The Integrate Edits web tool in the Experience Builder analysis widget, showing no configurable parameters and a single Run button. Below, a list widget displays the tool result: \"Edits integrated successfully\" with no validation issues requiring action.","author":"425640","description":"","caption":"","name":"picture4-90","status":"inherit","uploaded_to":2968594,"date":"2026-06-02 19:48:41","modified":"2026-06-02 19:49:20","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":555,"height":688,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture4-1-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture4-1.png","medium-width":211,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture4-1.png","medium_large-width":555,"medium_large-height":688,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture4-1.png","large-width":555,"large-height":688,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture4-1.png","1536x1536-width":555,"1536x1536-height":688,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture4-1.png","2048x2048-width":555,"2048x2048-height":688,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture4-1-375x465.png","card_image-width":375,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture4-1.png","wide_image-width":555,"wide_image-height":688}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture4-1.png"},{"acf_fc_layout":"content","content":"

6. Configure<\/h3>\n

With the decision features built and maintained via automation, the last step was to configure pretty pop-ups and the Nearby app to return them when a search is performed. The result is a user experience that surfaces fewer, but far more meaningful, results. Instead of scrolling through long lists of nearly identical meters, users are presented with clear, block-level options that can be evaluated quickly.<\/p>\n

Technical work: we used arcade to make easy-to-read pop-ups for our decision features, and then in the Nearby app settings we changed which map layers showed up in the results<\/em><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2968686,"id":2968686,"title":"Block Point Nearby Results","filename":"Picture6-1.png","filesize":255933,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture6-1.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/instant-apps\/decision-support\/how-people-decide-designing-results-for-nearby-searches\/picture6-65","alt":"The same Nearby search using decision features instead, returning 16 results \u2014 14 Metered Parking options \u2014 each identified by time limit, block, street name, and side, such as \"3 Hours: 700 block of Broadway, North side.\"","author":"425640","description":"","caption":"","name":"picture6-65","status":"inherit","uploaded_to":2968594,"date":"2026-06-02 19:49:42","modified":"2026-06-02 19:50:23","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1483,"height":958,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture6-1-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture6-1.png","medium-width":404,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture6-1.png","medium_large-width":768,"medium_large-height":496,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture6-1.png","large-width":1483,"large-height":958,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture6-1.png","1536x1536-width":1483,"1536x1536-height":958,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture6-1.png","2048x2048-width":1483,"2048x2048-height":958,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture6-1-720x465.png","card_image-width":720,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture6-1.png","wide_image-width":1483,"wide_image-height":958}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Picture6-1.png"},{"acf_fc_layout":"content","content":"

Applying decision features beyond parking<\/h2>\n

This same approach can be used for countless other contexts. For example, consider a park with multiple trailheads, intersecting trails, and destinations like overlooks or waterfalls. In this setting, users aren’t exactly asking where each destination or trailhead is, they’re asking what they could reasonably see if they start from a particular access point.<\/p>\n

Here, trail segments and destinations are the inventory features, while trailheads become the decision features. Aggregated attributes might include reachable destinations, difficulty ranges, or time estimates rather than simple counts. We don’t have to collapse complexity, but building useful search results often means organizing complexity around a meaningful choice.<\/p>\n"},{"acf_fc_layout":"content","content":"

Designing what a Nearby result represents<\/h2>\n

The Nearby Instant App is an effective tool for spatial discovery. In dense or rule-driven environments, its usefulness depends on what each result stands for. If Nearby results feel noisy or overwhelming, it’s worth stepping back and asking a simple question: Is this result representing an option?<\/p>\n

By keeping authoritative inventory data intact and configuring Nearby to return decision features instead, Nearby is better able to support how people actually make choices.<\/p>\n"}],"related_articles":"","show_article_image":true,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/clarity_card.png","wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/clarity.png"},"yoast_head":"\nHow People Decide: Designing Results for Nearby Searches<\/title>\n<meta name=\"description\" content=\"Rethink what an ArcGIS Instant Apps Nearby result represents \u2014 a design pattern for surfacing decision-ready options instead of raw assets.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/instant-apps\/decision-support\/how-people-decide-designing-results-for-nearby-searches\" \/>\n<meta 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