Google SERP Analyzer for SEO

This workflow analyzes Google’s search results for a given keyword, extracting insights about search intent, competitor strategies, and content opportunities to help you outrank top results. Ideal for marketers and SEO professionals aiming to improve their website’s visibility and performance.

Flows

How the AI Flow works

User provides a keyword.: The user enters a target keyword into the chat interface.
Query Expansion.: The input keyword is paraphrased into multiple alternative queries to enhance the search and analysis.
Google Search Results Retrieval.: The workflow searches Google for the expanded queries and retrieves the top-ranking URLs and their content.
SERP and Competitor Analysis.: An AI agent analyzes the search results, identifying searcher intent, competitor strategies, content uniqueness, and ranking factors.
Actionable Insights Output.: The workflow generates and displays actionable recommendations for improving content and outranking competitors.

Prompts used in this flow

SERP Searcher's Intent and Content Analysis

Analyzes the searcher's personality, sentiment, SERP content positioning, authority, UGC, freshness, and provides an overview of ranking potential and content s...

You're tasked with finding information people are trying to find from {input} and {context}. Find out what the searcher's personality is. Analyze what websites on top positions rank and what makes their content unique. Analyze the sentiment of SERP - negative, neutral, or positive. Where is the main content about {input} located on the pages - is it on top, middle, or at the bottom? Is there any Experience in the SERP (Hint: reviews, first-hand experience)? Is there any well-known website with considerable authority on the topic (Hint: Forbes for entrepreneurial content)? Does Google prefer UGC (user-generated content)? Is freshness needed (Hint: Most results are from 2024)? Additionally, provide an overview of what content to write and assess whether there is a chance to rank for the keyword. Consider any previous discussion in {chat_history} and use {context} to enhance your analysis. Answer in English and format the answer with markdown. Additionally, assist the user in answering related questions as requested.

*** CONTEXT START ***
{context}
*** CONTEXT END ***

*** CHAT HISTORY ***
{chat_history}
*** CHAT HISTORY END ***

*** INPUT ***
{input}
*** INPUT END ***

SEARCHER'S INTENT ANALYSIS:

Components used in this flow

Below is a complete list of all components used in this flow to achieve its functionality. Components are the building blocks of every AI Flow. They allow you to create complex interactions and automate tasks by connecting various functionalities. Each component serves a specific purpose, such as handling user input, processing data, or integrating with external services.

ChatInput

The Chat Input component in FlowHunt initiates user interactions by capturing messages from the Playground. It serves as the starting point for flows, enabling the workflow to process both text and file-based inputs.

See ChatInput

Query Expansion

Query Expansion in FlowHunt enhances chatbot understanding by finding synonyms, fixing spelling errors, and ensuring consistent, accurate responses for user queries.

See Query Expansion

GoogleSearch Component

FlowHunt's GoogleSearch component enhances chatbot accuracy using Retrieval-Augmented Generation (RAG) to access up-to-date knowledge from Google. Control results with options like language, country, and query prefixes for precise and relevant outputs.

See GoogleSearch Component

Prompt Component in FlowHunt

Learn how FlowHunt's Prompt component lets you define your AI bot’s role and behavior, ensuring relevant, personalized responses. Customize prompts and templates for effective, context-aware chatbot flows.

See Prompt Component in FlowHunt

Generator

Explore the Generator component in FlowHunt—powerful AI-driven text generation using your chosen LLM model. Effortlessly create dynamic chatbot responses by combining prompts, optional system instructions, and even images as input, making it a core tool for building intelligent, conversational workflows.

See Generator

Chat Output

Discover the Chat Output component in FlowHunt—finalize chatbot responses with flexible, multi-part outputs. Essential for seamless flow completion and creating advanced, interactive AI chatbots.

See Chat Output

Chat History Component

The Chat History component in FlowHunt enables chatbots to remember previous messages, ensuring coherent conversations and improved customer experience while optimizing memory and token usage.

See Chat History Component

Flow description

Purpose and benefits

This workflow is designed to automate and scale the process of analyzing Google’s search engine results pages (SERPs) for any given keyword. It provides users with actionable insights into the searcher’s intent, personality, competitor strategies, and content opportunities, making it a powerful tool for SEO professionals, content creators, and digital marketers.

User Interaction and Onboarding

When a user opens the chat interface, a welcome message is displayed, introducing the “Google Results Analyzer.” The introduction explains that the tool will help analyze the top Google results for any keyword and provide insights to help the user outrank competitors. The chat interface also presents clickable buttons for exploring related AI topics such as “AI tools,” “AI automation,” and “AI for E-commerce,” each accompanied by its respective output message.

Input Handling and Query Expansion

The workflow captures the user’s keyword input via a chat input node. To enhance the robustness and coverage of the analysis, the keyword is fed into a Query Expansion module, which paraphrases the input into multiple alternative queries. This step ensures that the subsequent Google search covers a broader semantic range, improving the quality and depth of the retrieved SERP data.

Chat Input: User submits a keyword or question.
Query Expansion: The keyword is paraphrased into multiple alternative queries for a comprehensive search.

Google Search and Context Gathering

The expanded set of queries is then sent to a Google Search node, which retrieves the top search results (URLs and their content). The context from these results is compiled to form the basis for deeper analysis.

Google Search: Performs live search using the paraphrased queries.
Context: Collects URLs and content from the top results.

Prompt Generation and Analysis

A sophisticated prompt template is used to guide an AI language model (LLM) in analyzing the SERP data. The prompt instructs the model to:

Determine what information people are seeking with the keyword.
Analyze the searcher’s personality and intent.
Assess the uniqueness and sentiment of top-ranking competitors’ content.
Identify where the main content is located on ranking pages.
Look for experience signals (e.g., reviews, first-hand experiences).
Detect authoritative domains and user-generated content preference.
Assess freshness requirements (e.g., if recent content is favored).
Provide actionable recommendations on content strategy and ranking potential.

The template also incorporates prior chat history, ensuring context-aware and coherent responses.

AI Generation and Output

The AI generator processes the prompt and outputs a comprehensive, markdown-formatted analysis. The findings are displayed to the user in the chat interface, providing clear, actionable insights.

Workflow Structure Overview

Step	Node Type	Purpose
Welcome/Buttons	Button Widget	Onboard user, offer topic exploration
Keyword Input	Chat Input	Capture user keyword
Query Expansion	Query Expansion	Paraphrase keyword for broad search
Google Search	Google Search	Retrieve top SERP results and content
Collect Chat History	Chat History	Retain previous user interactions for context
Prompt Construction	Prompt Template	Create detailed prompt for AI analysis
AI Analysis	Generator	Generate insights and recommendations using LLM
Display Output	Chat Output	Show results and insights to the user

Why This Workflow is Useful

Scalability: Automates a complex, multi-step SERP analysis that would be time-consuming if done manually.
Comprehensiveness: Leverages advanced query expansion and live Google search to capture the full competitive landscape.
Actionable Insights: Goes beyond basic ranking data, providing deep analysis of searcher intent, competitor strategy, SERP sentiment, authority signals, and content gaps.
Interactivity: User-friendly chat interface and topic buttons make exploration accessible even for non-technical users.
Context-Aware: Incorporates chat history for more relevant and personalized recommendations.
Automation for Teams: Enables rapid, repeatable analysis for multiple keywords, making it ideal for agencies, content teams, and SEO professionals seeking to scale their research efforts.

Potential Applications

SEO and Content Strategy: Identify ranking opportunities, content gaps, and competitor strengths.
E-commerce Optimization: Analyze product search intent and SERP dynamics for better conversion.
Market Research: Understand what users are seeking and how top sites are satisfying these needs.
AI-Powered Campaigns: Integrate with other AI tools for end-to-end marketing automation.

With this workflow, users can efficiently and intelligently analyze Google SERPs, gain a competitive edge, and make data-driven decisions to improve their online visibility and content performance.

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