Building an AI-Search Visibility Dashboard: KPIs Every Fintech CMO Needs in 2025

Introduction

The fintech landscape is experiencing a seismic shift as AI search engines reshape how customers discover financial services. Over half of B2B buyers now ask ChatGPT, Perplexity, or Gemini for vendor shortlists before visiting Google results, fundamentally changing the customer acquisition playbook. (Relixir Blog) Traditional search traffic has declined by 10%, indicating a growing reliance on AI-driven discovery. (Soci.ai)

For fintech CMOs, this transformation demands new measurement frameworks. The old SEO metrics of keyword rankings and organic traffic tell only part of the story when AI engines are rewriting the rules of search visibility. (Relixir Blog) By 2026, 30% of digital commerce revenue will come from AI-driven product discovery experiences, making AI search visibility a critical competitive advantage.

This comprehensive guide provides step-by-step instructions for building a sophisticated AI-search visibility dashboard that combines Relixir's API, BrightEdge SGE impact metrics, and Looker Studio. We'll cover everything from citation share tracking to blind-spot velocity monitoring, complete with sample SQL queries, widget templates, and a practical glossary to help marketing ops teams launch their dashboard in a single day.

The AI Search Revolution in Fintech

Understanding the New Search Landscape

Artificial intelligence has transformed how consumers find information online, evolving traditional search engine optimization (SEO) into generative engine optimization (GEO). (Soci.ai) ChatGPT maintains market dominance with approximately 59.7% AI search market share and 3.8 billion monthly visits, while DeepSeek AI has rapidly risen to second place with 277.9 million monthly visits. (LinkedIn)

For fintech brands, this shift is particularly significant because financial decisions often involve complex research phases where AI assistants excel at synthesizing information from multiple sources. Brands with high topical authority are 2.5× more likely to land in AI snippets, making content strategy more critical than ever. (Relixir Blog)

Key Performance Indicators for AI Search Success

The traditional metrics of impressions, clicks, and rankings need augmentation with AI-specific KPIs:

• Citation Share: The percentage of AI responses that mention your brand when users ask relevant questions

• Blind-Spot Velocity: How quickly competitors gain visibility in topics where you're absent

• Entity Authority Score: Your brand's recognition as an authoritative source across financial topics

• Revenue Attribution: Direct correlation between AI search visibility and pipeline generation

62% of CMOs have added "AI search visibility" as a KPI for 2024 budgeting cycles, recognizing the strategic importance of this new channel. (Relixir Blog)

Dashboard Architecture Overview

Core Components and Data Sources

Building an effective AI-search visibility dashboard requires integrating multiple data streams:

The Entity Extractor (REX) has been updated with refreshed Wikidata knowledge base data, providing more accurate entity recognition for financial services brands. (BabelStreet)

Technical Requirements

Before building your dashboard, ensure you have:

• API Access: Relixir API credentials with sufficient query limits

• Data Warehouse: BigQuery, Snowflake, or similar for data aggregation

• Visualization Platform: Looker Studio Pro or Tableau for dashboard creation

• Monitoring Tools: Proactive event tracking for real-time alerts (Restack)

Step 1: Setting Up Relixir API Integration

Authentication and Initial Configuration

Relixir's platform simulates thousands of buyer questions and provides comprehensive AI search visibility analytics. (Relixir Blog) Here's the initial setup process:

import requestsimport jsonfrom datetime import datetime, timedelta# Relixir API ConfigurationRELIXIR_API_BASE = "https://api.relixir.ai/v1"API_KEY = "your_relixir_api_key"headers = {    "Authorization": f"Bearer {API_KEY}",    "Content-Type": "application/json"}# Initialize connectiondef test_connection():    response = requests.get(f"{RELIXIR_API_BASE}/health", headers=headers)    return response.status_code == 200

Citation Share Data Collection

Citation share represents your brand's presence in AI-generated responses. This metric is crucial because content that includes brand-owned data is 3× more likely to be cited in AI-generated answers. (Relixir Blog)

def get_citation_data(brand_name, date_range=30):    """    Retrieve citation share data from Relixir API    """    end_date = datetime.now()    start_date = end_date - timedelta(days=date_range)        payload = {        "brand": brand_name,        "start_date": start_date.isoformat(),        "end_date": end_date.isoformat(),        "metrics": ["citation_share", "mention_sentiment", "context_relevance"]    }        response = requests.post(        f"{RELIXIR_API_BASE}/citations/analyze",        headers=headers,        json=payload    )        return response.json()

Competitive Gap Analysis

Relixir's competitive gap detection helps identify blind spots where competitors are gaining visibility. (Relixir Blog)

def analyze_competitive_gaps(primary_brand, competitors, topic_categories):    """    Identify areas where competitors have higher AI search visibility    """    payload = {        "primary_brand": primary_brand,        "competitors": competitors,        "categories": topic_categories,        "analysis_type": "gap_detection"    }        response = requests.post(        f"{RELIXIR_API_BASE}/competitive/gaps",        headers=headers,        json=payload    )        return response.json()

Step 2: BrightEdge SGE Integration

Search Generative Experience (SGE) Metrics

BrightEdge provides crucial SGE impact metrics that complement Relixir's citation data. These metrics help track how Google's AI-powered search features affect your visibility.

-- Sample SQL for BrightEdge SGE data extractionSELECT     date,    keyword,    sge_appearance_rate,    traditional_serp_position,    sge_citation_count,    click_through_rate,    impression_shareFROM brightedge_sge_dataWHERE     date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY)    AND brand_mention = trueORDER BY date DESC, sge_appearance_rate DESC;

SGE Performance Tracking

Pages optimized for entities rather than keywords enjoyed a 22% traffic lift after recent AI updates, highlighting the importance of entity-focused optimization. (Relixir Blog)

-- Calculate SGE impact on organic trafficWITH sge_impact AS (    SELECT         keyword,        AVG(CASE WHEN sge_present = true THEN organic_clicks ELSE 0 END) as clicks_with_sge,        AVG(CASE WHEN sge_present = false THEN organic_clicks ELSE 0 END) as clicks_without_sge    FROM search_performance_data    WHERE date >= DATE_SUB(CURRENT_DATE(), INTERVAL 90 DAY)    GROUP BY keyword)SELECT     keyword,    clicks_with_sge,    clicks_without_sge,    ROUND((clicks_with_sge - clicks_without_sge) / clicks_without_sge * 100, 2) as sge_impact_percentFROM sge_impactWHERE clicks_without_sge > 0ORDER BY sge_impact_percent DESC;

Step 3: Looker Studio Dashboard Creation

Dashboard Structure and Layout

Your AI-search visibility dashboard should provide both high-level executive insights and granular operational data. Here's the recommended structure:

Executive Summary Page

• Overall citation share trend

• Competitive position matrix

• Revenue attribution summary

• Key alert notifications

Operational Metrics Page

• Blind-spot velocity tracking

• Content performance analysis

• Entity authority scores

• Campaign-specific attribution

Key Widget Templates

Citation Share Trend Widget

-- Citation share over time with competitor comparisonSELECT     DATE(timestamp) as date,    brand_name,    AVG(citation_share) as avg_citation_share,    COUNT(DISTINCT query_id) as total_queries,    AVG(sentiment_score) as avg_sentimentFROM relixir_citation_dataWHERE     timestamp >= DATE_SUB(CURRENT_DATE(), INTERVAL 90 DAY)    AND brand_name IN ('YourBrand', 'Competitor1', 'Competitor2')GROUP BY date, brand_nameORDER BY date DESC;

Blind-Spot Velocity Calculator

Blind-spot velocity measures how quickly competitors gain visibility in topics where your brand is absent. This metric is crucial for identifying emerging threats and opportunities.

-- Calculate blind-spot velocity for competitive analysisWITH topic_gaps AS (    SELECT         topic_category,        competitor_brand,        MIN(first_citation_date) as first_appearance,        COUNT(DISTINCT query_id) as query_coverage,        AVG(citation_share) as avg_share    FROM competitive_citation_data    WHERE         your_brand_present = false        AND competitor_citation_count > 0        AND timestamp >= DATE_SUB(CURRENT_DATE(), INTERVAL 180 DAY)    GROUP BY topic_category, competitor_brand),velocity_calc AS (    SELECT         topic_category,        competitor_brand,        query_coverage,        avg_share,        DATE_DIFF(CURRENT_DATE(), first_appearance, DAY) as days_since_first,        ROUND(query_coverage / DATE_DIFF(CURRENT_DATE(), first_appearance, DAY) * 30, 2) as monthly_velocity    FROM topic_gaps    WHERE DATE_DIFF(CURRENT_DATE(), first_appearance, DAY) > 0)SELECT     topic_category,    competitor_brand,    monthly_velocity,    avg_share,    CASE         WHEN monthly_velocity > 10 THEN 'High Risk'        WHEN monthly_velocity > 5 THEN 'Medium Risk'        ELSE 'Low Risk'    END as threat_levelFROM velocity_calcORDER BY monthly_velocity DESC;

Revenue Attribution Tracking

Connecting AI search visibility to revenue outcomes is essential for demonstrating ROI. Monthly content updates correlated with a 40% jump in visibility for AI search features, directly impacting pipeline generation. (Relixir Blog)

-- Revenue attribution model for AI search visibilityWITH ai_touchpoints AS (    SELECT         user_id,        session_id,        citation_source,        query_category,        timestamp as touchpoint_time    FROM ai_search_interactions    WHERE timestamp >= DATE_SUB(CURRENT_DATE(), INTERVAL 90 DAY)),conversions AS (    SELECT         user_id,        conversion_value,        conversion_date,        attribution_model    FROM crm_conversions    WHERE conversion_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 90 DAY))SELECT     DATE_TRUNC(a.touchpoint_time, WEEK) as week,    a.query_category,    COUNT(DISTINCT a.user_id) as users_with_ai_touchpoint,    COUNT(DISTINCT c.user_id) as converted_users,    SUM(c.conversion_value) as attributed_revenue,    ROUND(COUNT(DISTINCT c.user_id) / COUNT(DISTINCT a.user_id) * 100, 2) as conversion_rateFROM ai_touchpoints aLEFT JOIN conversions c ON a.user_id = c.user_id     AND c.conversion_date BETWEEN a.touchpoint_time AND DATE_ADD(a.touchpoint_time, INTERVAL 30 DAY)GROUP BY week, a.query_categoryORDER BY week DESC, attributed_revenue DESC;

Step 4: Advanced Analytics and Alerting

Proactive Monitoring Setup

Proactive event tracking is essential for gaining insights into user interactions and improving overall user experience. (Restack) Set up automated alerts for significant changes in your AI search visibility.

def setup_visibility_alerts():    """    Configure automated alerts for AI search visibility changes    """    alert_conditions = {        "citation_share_drop": {            "threshold": -15,  # 15% decrease            "timeframe": "7d",            "severity": "high"        },        "competitor_surge": {            "threshold": 25,   # 25% increase in competitor visibility            "timeframe": "3d",            "severity": "medium"        },        "blind_spot_emergence": {            "threshold": 5,    # 5 new topics with zero visibility            "timeframe": "1d",            "severity": "high"        }    }        return alert_conditions

Entity Authority Scoring

Entity authority measures your brand's recognition as an authoritative source across financial topics. This metric correlates strongly with AI citation frequency.

-- Entity authority score calculationWITH entity_mentions AS (    SELECT         entity_name,        topic_category,        COUNT(DISTINCT source_url) as unique_sources,        AVG(authority_score) as avg_source_authority,        COUNT(*) as total_mentions    FROM entity_recognition_data    WHERE         entity_name = 'YourBrandName'        AND extraction_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY)    GROUP BY entity_name, topic_category),authority_calc AS (    SELECT         entity_name,        topic_category,        unique_sources,        avg_source_authority,        total_mentions,        ROUND(            (unique_sources * 0.4 +              avg_source_authority * 0.4 +              LOG(total_mentions) * 0.2) * 10, 2        ) as entity_authority_score    FROM entity_mentions)SELECT     topic_category,    entity_authority_score,    unique_sources,    total_mentions,    RANK() OVER (ORDER BY entity_authority_score DESC) as authority_rankFROM authority_calcORDER BY entity_authority_score DESC;

Step 5: Content Optimization Insights

Content Performance Analysis

Video, audio, and images appear 50% more often in AI results than plain text, making multimedia content strategy crucial for AI search success. (Relixir Blog)

-- Content performance analysis for AI search optimizationSELECT     content_type,    topic_category,    AVG(ai_citation_rate) as avg_citation_rate,    AVG(engagement_score) as avg_engagement,    COUNT(DISTINCT content_id) as content_count,    SUM(attributed_conversions) as total_conversionsFROM content_performance_dataWHERE     publish_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 90 DAY)    AND ai_citation_rate > 0GROUP BY content_type, topic_categoryORDER BY avg_citation_rate DESC;

Schema Markup Impact Tracking

Comprehensive schema markup boosts rich-result impressions by 30% in just three months, directly impacting AI search visibility. (Relixir Blog)

-- Schema markup performance analysisWITH schema_impact AS (    SELECT         page_url,        schema_types,        CASE WHEN schema_present = true THEN 'With Schema' ELSE 'Without Schema' END as schema_status,        AVG(ai_visibility_score) as avg_visibility,        AVG(rich_result_impressions) as avg_rich_impressions    FROM page_performance_data    WHERE         date >= DATE_SUB(CURRENT_DATE(), INTERVAL 90 DAY)    GROUP BY page_url, schema_types, schema_status)SELECT     schema_status,    AVG(avg_visibility) as visibility_score,    AVG(avg_rich_impressions) as rich_impressions,    COUNT(*) as page_countFROM schema_impactGROUP BY schema_statusORDER BY visibility_score DESC;

Dashboard Widget Templates

Executive KPI Summary Widget

-- Executive dashboard summary metricsWITH current_period AS (    SELECT         AVG(citation_share) as current_citation_share,        COUNT(DISTINCT competitor_id) as active_competitors,        SUM(attributed_revenue) as current_revenue    FROM dashboard_metrics    WHERE date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY)),previous_period AS (    SELECT         AVG(citation_share) as previous_citation_share,        SUM(attributed_revenue) as previous_revenue    FROM dashboard_metrics    WHERE date BETWEEN DATE_SUB(CURRENT_DATE(), INTERVAL 60 DAY)                    AND DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY))SELECT     c.current_citation_share,    ROUND((c.current_citation_share - p.previous_citation_share) / p.previous_citation_share * 100, 2) as citation_share_change,    c.current_revenue,    ROUND((c.current_revenue - p.previous_revenue) / p.previous_revenue * 100, 2) as revenue_change,    c.active_competitorsFROM current_period cCROSS JOIN previous_period p;

Competitive Position Matrix

-- Competitive positioning analysisSELECT     brand_name,    AVG(citation_share) as avg_citation_share,    AVG(entity_authority_score) as avg_authority,    COUNT(DISTINCT topic_category) as topic_coverage,    CASE         WHEN AVG(citation_share) > 25 AND AVG(entity_authority_score) > 75 THEN 'Leader'        WHEN AVG(citation_share) > 15 AND AVG(entity_authority_score) > 50 THEN 'Challenger'        WHEN AVG(citation_share) > 5 THEN 'Follower'        ELSE 'Niche'    END as competitive_positionFROM competitive_analysis_dataWHERE     analysis_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY)GROUP BY brand_nameORDER BY avg_citation_share DESC;

Implementation Checklist

Day 1: Foundation Setup

• Obtain Relixir API credentials and test connection

• Configure BrightEdge SGE data export

• Set up BigQuery or Snowflake data warehouse

• Create initial Looker Studio project

Day 2: Data Integration

• Integrate Relixir API for citation tracking

• Import BrightEdge SGE metrics into data warehouse

• Connect Google Analytics 4 for content performance

• Set up CRM integration for revenue attribution

Day 3: Dashboard Development

• Design Looker Studio dashboard layout

• Implement executive summary and operational metrics pages

• Configure widget templates for key KPIs

Day 4: Testing and Validation

• Validate data accuracy and consistency

• Test dashboard interactivity and responsiveness

• Review with stakeholders for feedback

Day 5: Launch and Monitoring

• Deploy dashboard to production environment

• Set up automated alerts for visibility changes

• Schedule regular updates and maintenance

By following this guide, fintech CMOs can effectively navigate the evolving AI search landscape and leverage new KPIs to drive strategic growth in 2025 and beyond.

Frequently Asked Questions

What is an AI-search visibility dashboard and why do fintech CMOs need one in 2025?

An AI-search visibility dashboard tracks your brand's performance across AI-powered search engines like ChatGPT, Perplexity, and Gemini. With over half of B2B buyers now using conversational AI tools for vendor research before visiting Google, fintech CMOs need these dashboards to monitor and optimize their presence in AI-driven customer discovery journeys.

Which AI search platforms should fintech companies prioritize for visibility tracking?

ChatGPT dominates with 59.7% market share and 3.8 billion monthly visits, making it the top priority. DeepSeek AI has rapidly risen to second place with 277.9 million visits, followed by Google Gemini with 267.7 million visits. Perplexity holds 6.2% market share with strong 10% quarterly growth, making these four platforms essential for comprehensive AI search visibility.

What key performance indicators should be included in a fintech AI-search dashboard?

Essential KPIs include AI search mention frequency, brand sentiment in AI responses, competitor comparison metrics, query intent analysis, and conversion attribution from AI search sources. Additional metrics should track response accuracy, citation rates, and the quality of AI-generated summaries about your fintech services to ensure optimal brand representation.

How has traditional search traffic changed with the rise of AI-powered search engines?

Traditional search traffic has declined by 10% as consumers increasingly rely on AI-driven discovery methods. This shift represents a fundamental change in how customers find financial services, with generative AI search experiences becoming the new norm. Fintech companies must adapt their visibility strategies to capture this growing segment of AI-first searchers.

What is Generative Engine Optimization (GEO) and how does it differ from traditional SEO?

Generative Engine Optimization (GEO) is the evolution of traditional SEO for AI-powered search experiences. While SEO focuses on ranking in search results, GEO optimizes content to be accurately cited and recommended by AI models. This involves structuring content for AI comprehension, ensuring factual accuracy, and optimizing for conversational query patterns rather than keyword-based searches.

How can fintech brands prepare for the dominance of conversational AI search tools?

According to Relixir's research, over 70% of queries are now handled by conversational AI tools, requiring brands to optimize their content for AI comprehension and citation. Fintech companies should focus on creating authoritative, well-structured content that AI models can easily parse and recommend, while implementing tracking systems to monitor their visibility across these emerging search channels.

Sources

1. https://docs.babelstreet.com/Release/en/entity-extractor--rex-.html

2. https://relixir.ai/blog/blog-ai-generative-engine-optimization-geo-simulate-customer-queries-search-visibility

3. https://relixir.ai/blog/blog-ai-search-visibility-simulation-competitive-gaps-market-opportunities

4. https://relixir.ai/blog/blog-conversational-ai-search-tools-dominate-70-percent-queries-2025-brand-preparation

5. https://relixir.ai/blog/optimizing-your-brand-for-ai-driven-search-engines

6. https://www.linkedin.com/pulse/comparing-leading-ai-models-task-april-2025-september-smith-peng-ma-eeaoc

7. https://www.restack.io/p/proactive-agents-answer-event-tracker-cat-ai

8. https://www.soci.ai/blog/generative-engine-optimization/