Product and Market Research with Google Suggest and AI Agents

People don’t search for products the way marketers think they do. They search “best crm for small business”, “hubspot alternative cheaper”, and “do I need a crm”. Google autocomplete captures these real query patterns. The Google Suggest tool on AgentPatch gives your AI agent access to those suggestions, turning a product name or category into a map of how users actually think about it.

Why This Matters

Survey data tells you what people say they want. Search data tells you what they actually look for. Google autocomplete sits between the two — it reflects the most common ways real people phrase their questions, comparisons, and buying decisions about a product category.

The patterns are specific and revealing. “X vs Y” queries tell you who users consider your competitors. “X alternative” queries tell you people are leaving. “Best X for Y” queries tell you which use cases drive purchase decisions. “Is X worth it” queries tell you where trust is thin. An agent that can pull autocomplete data for a category and systematically explore these patterns gives you a market research layer that updates in real time and costs almost nothing to run.

Setup

Alternatively, you can install the AgentPatch plugin for Claude Code:

/plugin marketplace add fullthom/agentpatch-claude-skill
/plugin install agentpatch@agentpatch

This teaches Claude Code how to discover and use AgentPatch tools automatically.

Example

You’re doing competitive research for a CRM product. You want to understand how potential customers think about the category and where the opportunities are. You start broad:

“Use the Google Suggest tool to get autocomplete suggestions for each of these queries: ‘best crm for’, ‘crm vs’, ‘crm alternative’, and ‘do i need a crm’. I want to map out user intent across the CRM category.”

The agent runs four calls and returns the raw suggestions:

"best crm for" →
  best crm for small business, best crm for real estate,
  best crm for startups, best crm for freelancers,
  best crm for nonprofits, best crm for sales teams

"crm vs" →
  crm vs spreadsheet, crm vs erp, crm vs marketing automation,
  crm vs project management, crm vs database

"crm alternative" →
  crm alternative free, crm alternative to salesforce,
  crm alternative for small business, crm alternative open source

"do i need a crm" →
  do i need a crm for my small business,
  do i need a crm as a freelancer,
  do i need a crm if i use excel

That’s already useful. You can see the segments (small business, real estate, freelancers), the competitive landscape (Salesforce as the default to replace), and the objections (spreadsheets as the main alternative). You dig deeper:

“Take the top competitor mentioned — Salesforce — and run Google Suggest for ‘salesforce alternative’, ‘salesforce too expensive’, ‘salesforce vs’, and ‘switch from salesforce to’. I want to understand the pain points driving people away.”

The agent runs the queries:

"salesforce alternative" →
  salesforce alternative for small business,
  salesforce alternative open source,
  salesforce alternative 2026, salesforce alternative cheaper

"salesforce too expensive" →
  salesforce too expensive for small business,
  salesforce too expensive reddit,
  salesforce too expensive alternatives

"salesforce vs" →
  salesforce vs hubspot, salesforce vs zoho,
  salesforce vs pipedrive, salesforce vs monday crm,
  salesforce vs notion

"switch from salesforce to" →
  switch from salesforce to hubspot,
  switch from salesforce to zoho,
  switch from salesforce to pipedrive

Now you have a competitive map. You know which products users are considering as replacements, and you know price is the primary pain point. You ask the agent to synthesize:

“Based on all of these suggestions, summarize: (1) the top user segments by frequency, (2) the main competitors being compared, (3) the primary objections or pain points, and (4) any underserved niches where autocomplete suggestions are very specific but the market seems thin.”

The agent analyzes the full set:

User segments (by frequency in suggestions):
1. Small business — appears in nearly every category
2. Freelancers / solopreneurs — recurring in "best for" and "do I need"
3. Real estate — specific vertical with dedicated queries
4. Nonprofits — specific vertical, likely underserved

Competitive landscape:
- Salesforce is the default enterprise option (and the most common "switch from")
- HubSpot is the most common alternative mentioned
- Zoho and Pipedrive appear as mid-market options
- Notion appearing in "vs" suggests users exploring non-traditional CRM approaches

Primary pain points:
- Price ("too expensive" is a standalone autocomplete pattern)
- Complexity (implied by "crm vs spreadsheet", "do I need a crm if I use excel")
- Overkill for small teams (small business qualifier on almost everything)

Underserved niches:
- CRM for nonprofits (specific but few dominant products)
- CRM for freelancers (high search intent, most tools are team-focused)
- Open source CRM (appears in multiple query types, growing interest)

That’s a competitive brief built entirely from autocomplete data. No paid tools, no survey panels, no manual research across multiple sites. The agent pulled live Google Suggest data and synthesized it into actionable market intelligence.

Wrapping Up

Google Suggest reflects how real users think about a product category — the comparisons they make, the problems they have, and the alternatives they consider. An agent with access to this tool can map an entire competitive landscape in minutes. The Google Suggest tool is on the AgentPatch marketplace alongside search, trends, news, and more. Check out agentpatch.ai to see what’s available.