# How to build predictive search in Bubble

- Tool: Bubble
- Difficulty: Beginner
- Time required: 20-25 min
- Compatibility: All Bubble plans
- Last updated: March 2026

## TL;DR

Add smart predictive search to your Bubble app that shows popular searches, recent queries, fuzzy matching for typos, and Did you mean suggestions. This tutorial covers logging search queries, building an autocomplete dropdown, implementing basic fuzzy matching, and displaying search suggestions from saved query data.

## Overview: Adding Predictive Search in Bubble

Predictive search helps users find what they need faster by suggesting queries as they type. This tutorial builds a search system that shows recent searches, popular queries, and results matching partial input — making your search feel smart and responsive.

## Before you start

- A Bubble account with an app that has searchable data
- Basic understanding of Repeating Groups and searches
- Familiarity with Custom States and conditional visibility

## Step-by-step guide

### 1. Create a SearchQuery Data Type to log searches

Go to Data tab → Data types. Create SearchQuery with fields: Query (text), User (User), Searched_At (date), Result_Count (number). In your existing search workflow, add an action after the search executes: Create a new SearchQuery with the input value, current user, date, and result count. This logs every search for future suggestions.

**Expected result:** Every search is logged to the database for powering suggestions.

### 2. Build the autocomplete suggestion dropdown

On your search page, add an Input element. Below it (overlapping slightly), add a Repeating Group with Type: text, visible only when the Input is focused and has at least 2 characters. Set the data source to a merged list: (1) Do a search for SearchQueries where Query starts with Input value, grouped by Query, sorted by count descending — this gives popular matching queries. (2) The actual content search: Do a search for Products where Name contains Input value:each item's Name. Display suggestions in the dropdown. When a suggestion is clicked, set the Input value to that suggestion and trigger the search.

> Pro tip: Add a small delay (using a Do when condition is true event that fires 300ms after the input changes) to avoid querying on every keystroke.

**Expected result:** An autocomplete dropdown shows matching suggestions as the user types.

### 3. Show recent and popular searches

When the Input is focused but empty, show two sections: Recent Searches (Do a search for SearchQueries where User = Current User, sorted by date, limit 5, each item's Query) and Popular Searches (Do a search for SearchQueries grouped by Query, sorted by count descending, limit 5). Display these in the same dropdown Repeating Group with section headers. Clicking any suggestion fills the Input and triggers the search.

**Expected result:** Users see their recent searches and popular community searches when they focus the search input.

### 4. Implement basic fuzzy matching

Bubble does not have built-in fuzzy search, but you can approximate it. Create a backend workflow that runs when a search returns zero results. The workflow searches for records where the Name or Title contains each word of the query individually (splitting multi-word queries). If partial matches are found, display them with a Did you mean banner above the results. For more advanced fuzzy search, integrate an external search service like Algolia or Typesense via the API Connector — they support typo tolerance natively. For apps needing production-grade search, RapidDev can help integrate dedicated search services.

**Expected result:** When a search returns no results, partial matches and Did you mean suggestions appear.

### 5. Add search analytics to improve suggestions over time

Create an admin dashboard showing: top searched queries (SearchQueries grouped by Query, sorted by count), searches with zero results (where Result_Count = 0 — these reveal content gaps), and search frequency over time. Use this data to add missing content and improve your search suggestions. Periodically clean up the SearchQuery table by deleting entries older than 90 days to prevent database bloat.

**Expected result:** An analytics view showing search patterns that helps you improve content and search quality.

## Complete code example

File: `Workflow summary`

```text
PREDICTIVE SEARCH — WORKFLOW SUMMARY
=====================================

DATA TYPE: SearchQuery
  Query (text), User (User), Searched_At (date), Result_Count (number)

SEARCH INPUT BEHAVIOR:
  Empty + focused: Show Recent + Popular suggestions
  2+ chars + focused: Show autocomplete matches
  Not focused: Hide dropdown

AUTOCOMPLETE:
  Source: Merge of:
    1. SearchQueries (Query starts with input, grouped, sorted by count)
    2. Products (Name contains input):each item's Name
  Clicked: Set input value, trigger search

SEARCH WORKFLOW:
  1. Search Products where Name contains Input value
  2. Log SearchQuery (query, user, date, result count)
  3. If zero results: show Did you mean suggestions

DID YOU MEAN:
  Backend: Split query into words
  Search each word individually
  Show partial matches with suggestion banner

ANALYTICS:
  Top queries: grouped by Query, sorted by count
  Zero-result queries: Result_Count = 0
  Frequency: grouped by date
```

## Common mistakes

- **Querying the database on every keystroke** — Typing hello fires 5 searches in rapid succession, wasting WUs. Fix: Add a 300ms debounce using a Do when condition that checks if the input has not changed for 300ms.
- **Not cleaning up old search logs** — Millions of SearchQuery records accumulate over time, slowing searches and consuming storage. Fix: Schedule a weekly backend workflow to delete SearchQuery records older than 90 days.
- **Showing the dropdown when the input is empty** — An empty dropdown or a list of all items is not helpful and wastes queries. Fix: Add conditions: dropdown visible only when Input is focused AND Input value character count >= 2.

## Best practices

- Log every search to build suggestion data over time
- Show recent and popular searches when the input is empty and focused
- Debounce autocomplete queries to avoid firing on every keystroke
- Clean up old search logs periodically to prevent database bloat
- Track zero-result searches to identify content gaps
- Use grouped queries for popular suggestions to deduplicate results
- Consider external search services for production-grade fuzzy matching

## Frequently asked questions

### Does Bubble support full-text search?

Bubble's text matching is limited to the first 256 characters and supports contains and starts with. For full-text search, integrate Algolia or Typesense via the API Connector.

### How many search logs should I keep?

Keep 90 days of search logs. This provides enough data for suggestions and analytics without excessive database growth.

### Can I show results as the user types without pressing Enter?

Yes. Bind the Repeating Group data source directly to a search using the Input's value as a constraint. Results update automatically as the input changes.

### How do I handle searches with zero results?

Check if the search result count is 0 and display a Did you mean section with partial matches, or suggest broadening the search terms.

### Can I weight certain results higher?

Add a Relevance or Priority number field to your content. Sort search results by this field descending so promoted content appears first.

### Can RapidDev help implement advanced search?

Yes. RapidDev can integrate dedicated search services like Algolia for typo tolerance, faceted filtering, and instant search across large datasets.

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Source: https://www.rapidevelopers.com/bubble-tutorial/add-a-predictive-search-function-in-bubble
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