Auto-Complete

The Auto-Complete API provides real-time search suggestions for heavy equipment-related fields across United States markets. This specialized tool leverages MarketCheck's heavy equipment inventory database to deliver intelligent auto-completion capabilities, enabling developers to build sophisticated search interfaces with relevant term suggestions and inventory counts.

With flexible field-based matching and contextual filtering capabilities, this API enables developers, heavy equipment platforms, and search applications to implement efficient search experiences that guide users toward available inventory and popular search terms.

Overview

• Active Inventory Search: Provides suggestions based on current active heavy equipment dealer listings
• Relevance-based Sorting with prefix, substring, and case-insensitive matching
• Contextual Filtering allowing refined suggestions based on search context
• Performance Optimization with configurable count thresholds and result limits

Base Path

GET https://api.marketcheck.com/v2/search/heavy-equipment/auto-complete

The following example demonstrates how to use the Auto-Complete API to get suggestions for heavy equipment makes and models based on user input.

import axios from 'axios';

const options = {
  method: 'GET',
  url: 'https://api.marketcheck.com/v2/auto-complete/heavy-equipment',
  params: {api_key: 'YOUR_API_KEY', field: 'make', input: 'ac'},
  headers: {Accept: 'application/json'}
};

try {
  const { data } = await axios.request(options);
  console.log(data);
} catch (error) {
  console.error(error);
}

Explore the full range of parameters available for configuring auto-completion behavior in the Request section below.

Request

The Auto-Complete API provides extensive auto-completion capabilities for heavy equipment search interfaces. You can generate suggestions for heavy equipment specifications, geographic locations, and various attributes while applying contextual filters to refine results based on current search state.

Parameters

Available parameters for configuring auto-completion behavior and filtering suggestions:

Defaults

• term_counts: Defaults to false - returns simple array of matching terms
  • Use term_counts=true to include inventory counts for each suggestion
• facet_min_count: Defaults to 1 - minimum inventory count threshold for terms to appear in suggestions

Required Parameters

The following parameters are required for auto-completion requests:

• field - The field to search for auto-completion (see Available Fields below)
• input - The user input to match against

Available Fields

Auto-completion is supported for the following heavy equipment and location fields:

Contextual Filtering

Apply additional filters to refine suggestions based on current search context. Use any of the standard inventory parameters to scope suggestions to specific criteria:

• Geographic Scope: Use state, city, zip, or radius to limit suggestions to specific regions
• Vehicle Filters: Apply make, model, year, etc. to get contextual suggestions

Sorting & Matching

Auto-complete results are automatically sorted by relevance using intelligent matching algorithms:

Matching Types:

1. Prefix matches - Terms beginning with input (highest relevance)
2. Case-insensitive matches - Flexible text matching
3. Substring matches - Terms containing input anywhere

Performance Limits:

• Maximum 50 terms returned per request for optimal performance
• Results automatically ranked by relevance score
• No manual sorting parameters available

Response Schema

The Auto-Complete API returns suggestions in two possible formats depending on the term_counts parameter setting.

Default Format (term_counts=false)

Returns a simple array of matching terms, optimized for basic auto-completion:

{
  "terms": ["Caterpillar", "Caterpillar 320", "Caterpillar 330"]
}

With Counts Format (term_counts=true)

Returns detailed response with inventory counts for each suggestion:

{
  "terms": [
    { "item": "Caterpillar", "count": 1542 },
    { "item": "Caterpillar 320", "count": 324 }
  ]
}

Use Cases & Examples

Intelligent Search Suggestions

Implement intelligent search suggestions that adapt to user input, providing relevant heavy equipment and location terms that match current inventory availability.

Example:

Here we're providing auto-completion for heavy equipment makes as the user types, returning the most relevant suggestions based on current inventory:

import axios from 'axios';

const options = {
  method: 'GET',
  url: 'https://api.marketcheck.com/v2/auto-complete/heavy-equipment',
  params: {api_key: 'YOUR_API_KEY', field: 'make', input: 'Cat'},
  headers: {Accept: 'application/json'}
};

try {
  const { data } = await axios.request(options);
  console.log(data);
} catch (error) {
  console.error(error);
}

Contextual Model Suggestions

When users have already selected a make, provide contextual model suggestions that are relevant to their current search criteria and geographic location.

Example:

Here we're providing model suggestions for Caterpillar equipment in Texas, ensuring suggestions are relevant to available inventory in that region:

import axios from 'axios';

const options = {
  method: 'GET',
  url: 'https://api.marketcheck.com/v2/auto-complete/heavy-equipment',
  params: {
    api_key: 'YOUR_API_KEY',
    field: 'model',
    input: 'f',
    make: 'Stihl',
    state: 'CA',
    term_counts: true
  },
  headers: {Accept: 'application/json'}
};

try {
  const { data } = await axios.request(options);
  console.log(data);
} catch (error) {
  console.error(error);
}

Inventory Count Filtering

Filter auto-completion results to only show terms with sufficient inventory counts, reducing noise and focusing on popular or well-stocked options.

Example:

Here we're filtering suggestions to only include makes with at least 100 equipment units in inventory, ensuring users see popular and well-represented brands:

import axios from 'axios';

const options = {
  method: 'GET',
  url: 'https://api.marketcheck.com/v2/auto-complete/heavy-equipment',
  params: {
    api_key: 'YOUR_API_KEY',
    field: 'model',
    input: 'a',
    facet_min_count: 100,
    term_counts: true
  },
  headers: {Accept: 'application/json'}
};

try {
  const { data } = await axios.request(options);
  console.log(data);
} catch (error) {
  console.error(error);
}

See Also

• Inventory Search
• Heavy Equipment Listing