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<section class="hero--3way">
<div class="hero__container">
<div class="hero__eyebrow">AI-POWERED COMPARISON</div>
<h1 class="hero__title">Domo vs ThoughtSpot vs Scoop: Complete Comparison</h1>
<div class="hero__scores">
<div class="score-card score-card--competitor">
<div class="score-card__name">Domo</div>
<div class="score-card__score">62/100</div>
<div class="score-card__label">BUA Score</div>
</div>
<div class="score-card score-card--competitor">
<div class="score-card__name">ThoughtSpot</div>
<div class="score-card__score">57/100</div>
<div class="score-card__label">BUA Score</div>
</div>
<div class="score-card score-card--scoop">
<div class="score-card__name">Scoop Analytics</div>
<div class="score-card__score">82/100</div>
<div class="score-card__label">BUA Score</div>
<div class="score-card__badge">WINNER ✓</div>
</div>
</div>
</div>
</section>
<section class="content-section ">
<div class="content-section__container">
<h2 class="content-section__title">Executive Summary</h2>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">TL;DR Verdict</h3>
<p class="content-section__paragraph">Scoop (82/100 BUA) enables true business autonomy through multi-pass investigation, while Domo (62/100) and ThoughtSpot (57/100) trap users in dashboard paradigms. Both competitors require IT support for anything beyond pre-built views, blocking the iterative questioning real analysis demands. Choose Scoop for immediate independence, competitors only if committed to existing enterprise stacks.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">What is Scoop?</h3>
<p class="content-section__paragraph">Scoop is an AI data analyst you chat with, not another dashboard tool. Ask questions in plain English, get answers with charts instantly. Works natively in Excel and Slack where business users already operate. No SQL, no training, no semantic layer maintenance—just conversation with data.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Choose Scoop If</h3>
<ul class="content-section__list">
<li class="content-section__list-item">Your business users need to investigate data independently without IT tickets</li>
<li class="content-section__list-item">Teams work primarily in Excel and need analytics without leaving spreadsheets</li>
<li class="content-section__list-item">You want to eliminate consultant dependencies and training costs permanently</li>
<li class="content-section__list-item">Non-technical users need answers in minutes, not days of dashboard requests</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Consider Domo If</h3>
<ul class="content-section__list">
<li class="content-section__list-item">You're already invested heavily in the Domo ecosystem and apps</li>
<li class="content-section__list-item">Your use cases are purely operational dashboards with fixed metrics</li>
<li class="content-section__list-item">You have dedicated BI teams to maintain semantic layers continuously</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Consider ThoughtSpot If</h3>
<ul class="content-section__list">
<li class="content-section__list-item">You have data scientists who need advanced statistical modeling features</li>
<li class="content-section__list-item">Your organization requires on-premise deployment for regulatory compliance</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Bottom Line</h3>
<p class="content-section__paragraph">The 20-25 point BUA gap reveals a fundamental architectural difference: Scoop enables investigation while competitors enforce dashboard consumption . Domo and ThoughtSpot both require semantic layer maintenance, forcing business users to request IT changes for new questions . This dependency creates the productivity loss that represents 40% of traditional BI TCO . Scoop eliminates five of six cost categories by removing implementation, training, maintenance, consultants, and productivity loss. The future belongs to platforms that empower business users to investigate independently, not consume pre-built dashboards.</p>
</div>
</div>
</section>
<section class="content-section content-section--alt">
<div class="content-section__container">
<h2 class="content-section__title">At-a-Glance Comparison</h2>
<table class="content-section__table comparison-table--3way">
<thead>
<tr>
<th>Dimension</th><th>Domo</th><th>ThoughtSpot</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class=""><strong>BUA Score</strong></td><td class="">62/100</td><td class="">57/100</td><td class="scoop-cell">82/100</td>
</tr>
</tbody>
</table>
</div>
</section>
<section class="content-section ">
<div class="content-section__container">
<h2 class="content-section__title">BUA Framework Deep Dive</h2>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Autonomy (20 points)</h3>
<p class="content-section__paragraph"><strong>Dimension</strong>: Autonomy</p>
<p class="content-section__paragraph"><strong>Component Breakdown</strong></p>
<table class="content-section__table comparison-table--3way">
<thead>
<tr>
<th>Component</th><th>Domo</th><th>ThoughtSpot</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Investigation Capability</td><td class="">2/8</td><td class="">3/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Setup Requirements</td><td class="">1/8</td><td class="">2/8</td><td class="">5/8</td>
</tr>
<tr>
<td class="">Query Flexibility</td><td class="">1/8</td><td class="">2/8</td><td class="">5/8</td>
</tr>
</tbody>
</table>
<p class="content-section__paragraph"><strong>Quick Summary</strong> (40-60 words):</p>
<p class="content-section__paragraph">Scoop scores 18/20 on Autonomy versus Domo and ThoughtSpot's unscored ratings. Scoop enables true self-service investigation with 8/8 investigation capability, while Domo scores 2/8 and ThoughtSpot 3/8. Business users ask questions directly without IT support, semantic layers, or dashboard building.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Flow (20 points)</h3>
<p class="content-section__paragraph"><strong>Dimension</strong>: Flow</p>
<p class="content-section__paragraph"><strong>Component Breakdown</strong></p>
<table class="content-section__table comparison-table--3way">
<thead>
<tr>
<th>Component</th><th>Domo</th><th>ThoughtSpot</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Workflow Integration</td><td class="">1/8</td><td class="">2/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Context Preservation</td><td class="">0/8</td><td class="">1/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Response Speed</td><td class="">2/8</td><td class="">3/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Collaboration Flow</td><td class="">1/8</td><td class="">2/8</td><td class="">6/8</td>
</tr>
</tbody>
</table>
<p class="content-section__paragraph"><strong>Quick Summary</strong> (40-60 words):</p>
<p class="content-section__paragraph">Scoop scores 17/20 on Flow by working natively in Slack/Teams, while Domo and ThoughtSpot score 0/20 as portal-based platforms requiring users to leave their workflow. Scoop delivers answers in chat within 30 seconds, preserving context and collaboration, while traditional BI platforms force context switching that costs 15-20 minutes per question.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Understanding (20 points)</h3>
<p class="content-section__paragraph"><strong>Dimension</strong>: Understanding</p>
<p class="content-section__paragraph"><strong>Component Breakdown</strong></p>
<table class="content-section__table comparison-table--3way">
<thead>
<tr>
<th>Component</th><th>Domo</th><th>ThoughtSpot</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Natural Language Quality</td><td class="">2/8</td><td class="">5/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Business Terminology</td><td class="">1/8</td><td class="">4/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Error Clarity</td><td class="">2/8</td><td class="">3/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Semantic Layer Dependency</td><td class="">0/8</td><td class="">1/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Learning Curve</td><td class="">2/8</td><td class="">3/8</td><td class="">7/8</td>
</tr>
</tbody>
</table>
<p class="content-section__paragraph"><strong>Quick Summary</strong> (40-60 words):</p>
<p class="content-section__paragraph">Scoop scores 16/20 on Understanding by eliminating semantic layer requirements, while Domo and ThoughtSpot score 0/20 due to heavy technical dependencies. Business users can ask Scoop questions in plain English without learning field names or data structures. Traditional platforms require weeks of training and constant IT support for terminology mapping.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Presentation (20 points)</h3>
<p class="content-section__paragraph"><strong>Dimension</strong>: Presentation</p>
<p class="content-section__paragraph"><strong>Component Breakdown</strong></p>
<table class="content-section__table comparison-table--3way">
<thead>
<tr>
<th>Component</th><th>Domo</th><th>ThoughtSpot</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Output Format</td><td class="">2/8</td><td class="">3/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Context Preservation</td><td class="">1/8</td><td class="">2/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Business Readiness</td><td class="">2/8</td><td class="">2/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Shareability</td><td class="">3/8</td><td class="">3/8</td><td class="">5/8</td>
</tr>
</tbody>
</table>
<p class="content-section__paragraph"><strong>Quick Summary</strong> (40-60 words):</p>
<p class="content-section__paragraph">Scoop scores 15/20 on Presentation versus unscored competitors Domo and ThoughtSpot. While Domo and ThoughtSpot generate dashboard charts requiring manual PowerPoint assembly, Scoop creates narrative responses with embedded visualizations ready for business presentation, saving 4-6 hours per report.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Data (20 points)</h3>
<p class="content-section__paragraph"><strong>Dimension</strong>: Data</p>
<p class="content-section__paragraph"><strong>Component Breakdown</strong></p>
<table class="content-section__table comparison-table--3way">
<thead>
<tr>
<th>Component</th><th>Domo</th><th>ThoughtSpot</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Data Connection</td><td class="">2/8</td><td class="">3/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Data Freshness</td><td class="">3/8</td><td class="">4/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Data Scope</td><td class="">2/8</td><td class="">2/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Data Preparation</td><td class="">1/8</td><td class="">2/8</td><td class="">5/8</td>
</tr>
<tr>
<td class="">Data Governance</td><td class="">4/8</td><td class="">3/8</td><td class="">5/8</td>
</tr>
</tbody>
</table>
<p class="content-section__paragraph"><strong>Quick Summary</strong> (40-60 words):</p>
<p class="content-section__paragraph">Scoop scores 16/20 on Data capabilities by connecting directly to operational databases without modeling requirements. Domo and ThoughtSpot require IT teams to pre-model data through ETL pipelines and semantic layers before business users can analyze. Scoop enables immediate exploration of any data while competitors need 2-3 week setup cycles for new question types.</p>
</div>
</div>
</section>
<section class="content-section content-section--alt">
<div class="content-section__container">
<h2 class="content-section__title">Capability Deep Dive</h2>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Investigation & Root Cause Analysis</h3>
<p class="content-section__paragraph">When revenue suddenly drops 15%, the difference between knowing it happened and understanding why separates great companies from struggling ones. Traditional BI shows you the drop on a dashboard. Investigation platforms help you find the root cause through iterative questioning—was it pricing, competition, or market conditions? This capability determines whether business users can solve problems independently or need to file IT tickets for every follow-up question. The architectural difference between single-query dashboards and multi-pass investigation fundamentally changes how organizations respond to critical business changes.</p>
<p class="content-section__paragraph">The fundamental divide isn't features—it's architecture. Domo and ThoughtSpot built dashboard platforms with search added later. Their single-query architecture means each question stands alone. Users can't naturally ask 'why' or 'what else' without starting over. Domo's Beast Mode calculations help create metrics but don't enable investigation. You still manually build each view. ThoughtSpot's search bar seems powerful until you need the third follow-up question. Then you're back to building Worksheets. Scoop's conversation architecture changes everything. Ask about revenue drops. Scoop automatically checks seasonality, segments, and correlations. Find something interesting? Ask 'why' or 'show me more detail' naturally. No rebuilding. No IT tickets. The difference shows in metrics: Scoop users reach root cause in 3-5 queries taking 5 minutes. ThoughtSpot users need 45 minutes across multiple Worksheets. Domo users often give up and request custom dashboards, waiting days for IT delivery. This isn't about better dashboards. It's about enabling investigation. Business users think in questions, not queries. They need to explore, not just view.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A retail operations manager notices unusual inventory patterns on Monday morning. With Scoop, she types: 'Why are northeast stores showing stock-outs?' Scoop analyzes: supply chain delays (no), demand spikes (yes, 40% increase), competitor promotions (yes, started Thursday), weather impact (minimal). She asks: 'Which products most affected?' Then: 'Compare to last year's promotion.' Total time: 4 minutes, 3 questions, root cause found. With Domo, she opens the inventory dashboard, sees the stockouts, but can't ask why. She messages IT requesting analysis. IT creates custom Beast Mode calculations, builds new cards showing promotional impact. Delivers Wednesday. With ThoughtSpot, she searches 'northeast inventory levels,' sees the problem, tries 'northeast inventory by product' but loses store context. Opens Worksheet builder, manually creates comparison. After 45 minutes, still missing the competitor promotion connection.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Investigation capability isn't about having search or AI—it's about architecture that supports natural human problem-solving through iterative questioning. Scoop's conversation-first design means business users investigate like they think: question, answer, follow-up, deeper, root cause. Domo and ThoughtSpot's dashboard-first architecture forces users into IT-dependent workflows when real investigation is needed. For organizations serious about business user empowerment, this architectural difference determines whether problems get solved in minutes by the person who spotted them, or in days through IT tickets.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Excel & Spreadsheet Integration</h3>
<p class="content-section__paragraph">Every Monday morning, thousands of analysts export data from BI tools into Excel to create the reports executives actually use. This workflow reveals a fundamental truth: business users trust Excel. They know its formulas, love its flexibility, and rely on its familiarity. The question isn't whether your BI platform connects to Excel—it's whether that connection preserves the investigative flow that makes Excel powerful. Let's examine how Domo, ThoughtSpot, and Scoop handle this critical integration, focusing on what business users can actually accomplish without IT intervention.</p>
<p class="content-section__paragraph">The architectural differences become clear when examining actual workflows. Domo's Excel plugin operates as a one-way export tool—users can pull data but lose the investigative capability that makes Domo valuable. Each new question requires returning to the Domo interface. ThoughtSpot for Excel provides search functionality but restricts users to pre-built answer books, maintaining the same semantic layer limitations that exist in the main platform. Business users can search for 'sales by region' but can't ask 'why did Northeast sales drop?' without IT creating new models. Scoop's add-in brings the full AI analyst into Excel. Users type questions naturally, get answers with charts, and continue investigating—all without leaving their spreadsheet. The key distinction: Scoop treats Excel as a first-class investigation environment, not just a data destination. This means finance teams can build their monthly reports while simultaneously investigating variances. Sales ops can update forecasts while drilling into pipeline changes. The investigation doesn't stop when the data enters Excel—it accelerates because users are in their comfort zone.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A financial analyst needs to prepare the monthly board report. She opens her Excel template with established formulas and formatting. With Domo, she exports last month's data, manually refreshes each worksheet, then switches to Domo's interface whenever directors ask follow-up questions during review—breaking the flow and requiring screen sharing of unfamiliar interfaces. With ThoughtSpot, she can search for pre-defined metrics but hits a wall when asked about unexpected variances since those investigations aren't in the semantic layer. With Scoop, she types 'Update all metrics with March data' directly in Excel. When the CFO asks 'Why did gross margin drop 3%?', she types that exact question in the same spreadsheet. Scoop investigates automatically, showing that product mix shifted toward lower-margin items. Total context switches: zero. The entire investigation happens where the work lives.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Excel integration reveals each platform's true philosophy about business user empowerment. Domo and ThoughtSpot treat Excel as a data destination—useful for exports but disconnected from investigation capabilities. Scoop treats Excel as a legitimate analytics environment where business users already work. This isn't about features; it's about respecting where real analysis happens. When 90% of board reports still use Excel, the platform that brings intelligence to spreadsheets, rather than forcing users out of them, wins the productivity battle.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Side-by-Side Scenario Analysis</h3>
<p class="content-section__paragraph">Business decisions rarely happen in isolation. When executives ask 'What happens if we raise prices 10% versus expanding to new markets?', they need to see multiple scenarios simultaneously, not sequentially. This capability—comparing different futures side-by-side—separates strategic planning tools from basic reporting. Traditional BI forces users to build separate dashboards for each scenario, export to Excel, then manually compare. Modern platforms should enable instant scenario comparison without the Excel detour. Let's examine how Domo, ThoughtSpot, and Scoop handle this critical strategic planning need.</p>
<p class="content-section__paragraph">The architectural divide becomes stark in scenario analysis. Domo's approach requires creating multiple dashboards—one per scenario—then manually comparing outputs. Users report spending 2-3 hours setting up basic price sensitivity analysis. ThoughtSpot's Liveboard what-if feature handles simple parameter changes but can't compare multiple scenarios simultaneously. Users must screenshot each scenario and paste into PowerPoint. Scoop's conversational approach transforms this entirely. Type 'Compare revenue impact of 10% price increase versus 15% volume growth.' Scoop generates both scenarios, displays them side-by-side, and explains key differences. Follow up with 'Add a third scenario with both changes' takes seconds, not hours. The fundamental limitation of dashboard-based tools shows here. They're built for single-view reporting, not multi-scenario investigation. When McKinsey consultants build scenario models, they don't create 15 separate Excel files—they build one model with multiple scenarios visible simultaneously. Scoop mirrors this mental model. Domo and ThoughtSpot force the opposite: fragmenting analysis across disconnected views.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A CPG company's pricing team needs to model three scenarios for next year: status quo, 8% price increase, and new product launch. With Domo, the analyst creates three dashboard copies, modifies Beast Mode calculations in each, then exports all three to Excel for comparison. Total time: 4 hours. ThoughtSpot users open a Liveboard, adjust parameters for scenario one, screenshot it, repeat for scenarios two and three, then build a PowerPoint comparing them. Total time: 2 hours. With Scoop, the pricing manager types: 'Show me revenue projections for next year with current pricing, 8% increase, and new product launch scenarios side-by-side.' Scoop displays all three with variance analysis. She asks: 'What if we combine price increase with new product?' Scoop adds the fourth scenario instantly. The entire analysis, including documentation of assumptions, takes 15 minutes.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Scenario planning reveals the investigation versus dashboard divide perfectly. Domo and ThoughtSpot treat each scenario as a separate dashboard, forcing manual comparison outside their platforms. Scoop treats scenarios as part of natural business conversation—comparing multiple futures as easily as asking the question. For strategic planning teams, this difference means hours versus minutes to reach decisions.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Machine Learning & Pattern Discovery</h3>
<p class="content-section__paragraph">Your sales data contains hidden patterns that predict next quarter's revenue, but finding them shouldn't require a data science degree. Modern platforms promise automatic pattern discovery and ML-powered insights, yet most business users still wait weeks for data scientists to build models. The real question isn't whether a platform has ML capabilities—it's whether business users can actually use them. Let's examine how each platform democratizes advanced analytics, from automatic anomaly detection to predictive forecasting, and see who truly puts ML in the hands of business users versus keeping it locked in the data science department.</p>
<p class="content-section__paragraph">The fundamental divide in ML platforms isn't capability—it's accessibility. Domo's Mr. Roboto and AutoML offer powerful features but require technical configuration that puts them beyond most business users' reach. You need Beast Mode calculations and dataset preparation before ML even begins. ThoughtSpot's SpotIQ represents a middle ground: it automatically finds patterns but presents them in statistical language that requires interpretation. Users see correlation coefficients and p-values instead of business explanations. Scoop takes a different approach entirely. Instead of exposing ML as a separate feature, it weaves pattern discovery into natural conversation. Ask 'Why did sales drop?' and Scoop automatically tests multiple hypotheses: seasonality, customer segments, product mix, regional variations. The ML happens invisibly. This architectural choice means Scoop can't build custom models like Domo's AutoML, but business users can actually use what's there. The investigation depth matters most. While SpotIQ shows you interesting patterns, it can't explain why they exist. Scoop's multi-pass investigation automatically drills into root causes, testing and eliminating hypotheses until finding the answer.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A retail operations manager notices unusual inventory patterns across 50 stores. With Domo, she must first configure Mr. Roboto, selecting which metrics to analyze and setting detection parameters—assuming she knows Beast Mode. After IT helps with setup (2 days), she gets alerts but must manually investigate each one. ThoughtSpot's SpotIQ automatically flags that Store #37 has anomalous patterns, showing correlation graphs and statistical significance scores. But understanding why requires manual analysis—she must create separate queries to check seasonality, compare to similar stores, and analyze product mix. With Scoop, she simply asks: 'What's unusual about our inventory patterns this month?' Scoop immediately identifies Store #37, explains it's 3 standard deviations above normal, automatically compares to similar stores, checks for receiving errors, analyzes product mix changes, and discovers a misconfigured auto-replenishment rule for seasonal items. Total time: 4 minutes versus 2 days of setup plus hours of manual investigation.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: ThoughtSpot's SpotIQ excels at pattern detection but requires statistical knowledge to interpret. Domo offers powerful ML tools that most business users can't access without IT help. Scoop makes pattern discovery invisible and automatic—you ask business questions and get explanations, not statistics. While it lacks custom model building, Scoop delivers what matters most: letting business users discover insights independently, turning 2-day investigations into 4-minute conversations.</p>
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<h3 class="content-section__subtitle">Workflow Integration & Mobile</h3>
<p class="content-section__paragraph">Your best insights mean nothing if they're trapped in a browser tab. Modern business happens in Excel, Slack, Teams, and on phones—not in BI portals. The real test isn't whether a platform has mobile apps or APIs. It's whether business users can actually get answers where they already work, without learning new interfaces or switching contexts. Let's examine how each platform handles the reality of distributed work: Excel-based planning cycles, Slack discussions that need data, and executives checking metrics between meetings.</p>
<p class="content-section__paragraph">The workflow integration battle reveals a fundamental divide. Domo and ThoughtSpot built portal-first architectures, then bolted on integrations. Their mobile apps are essentially responsive web viewers. Excel integration means export-import cycles. Slack integration posts static screenshots. This isn't integration—it's notification. Scoop inverted the model. The AI analyst lives wherever you work. In Excel, you chat with data directly in cells. In Slack, you investigate without switching tabs. On mobile, you ask complex questions naturally. The difference is architectural. Portal platforms must maintain state, sessions, and semantic layers. They can't truly embed elsewhere. Scoop's stateless AI model travels light. Each query is independent, requiring no session management. This enables true embedded experiences. Domo's mobile app has 2.8 stars on iOS—users complain about constant logouts and slow loading. ThoughtSpot's mobile search works, but requires their specific syntax. Neither supports multi-step investigation on mobile. The Excel gap is even wider. Financial analysts live in spreadsheets, yet both competitors treat Excel as an export target, not a working environment.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A CFO is reviewing quarterly forecasts in Excel when she spots an anomaly in European sales. With Scoop's Excel add-in, she highlights the suspicious number and types 'What drove this 23% variance from forecast?' directly in Excel. Scoop analyzes the data, identifies three underperforming products, and inserts the explanation with charts right into her spreadsheet. She shares this in the leadership Slack channel asking for context. The regional manager responds in Slack by typing '@scoop show me customer churn for those three products in Germany.' The investigation continues naturally in the conversation thread. Later, boarding a flight, the CFO continues the investigation on her phone, asking follow-up questions using voice input. With Domo or ThoughtSpot, this same workflow requires: exporting from Excel, logging into the portal, building queries, taking screenshots, pasting into Slack, and hoping mobile dashboards load properly.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Workflow integration isn't about having APIs and mobile apps—it's about eliminating context switches. Scoop brings the AI analyst to where work happens: Excel formulas, Slack threads, mobile conversations. Domo and ThoughtSpot bring you to their portals. That's a 10x difference in friction for the 73% of business users who start their analysis in Excel. The architectural choice—portal prison versus embedded AI—determines whether insights flow naturally through your organization or die in dashboard graveyards.</p>
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<section class="content-section ">
<div class="content-section__container">
<h2 class="content-section__title">Frequently Asked Questions</h2>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">What is Scoop?</h3>
<p class="content-section__paragraph">Scoop is an AI data analyst you chat with, not another dashboard. Ask questions in plain English, get answers with charts. Works natively in Excel and Slack. Unlike Domo and ThoughtSpot which require IT setup, Scoop connects directly to your data in 30 seconds.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Does Scoop support multi-step analysis?</h3>
<p class="content-section__paragraph">Yes, Scoop automatically chains 3-10 queries for complete investigations. Domo requires manual dashboard navigation, ThoughtSpot offers single-query search. Scoop tests hypotheses, finds correlations, and identifies root causes automatically—like having a data analyst who explores every angle without being asked.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Which is better for business users: Domo or ThoughtSpot?</h3>
<p class="content-section__paragraph">Neither matches Scoop's 82/100 BUA score. Domo scores 62/100 with dashboard limitations, ThoughtSpot gets 57/100 requiring search training. Both need IT support for complex queries. Scoop eliminates these barriers—business users ask questions naturally and get complete answers without technical knowledge.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Can ThoughtSpot do root cause analysis automatically?</h3>
<p class="content-section__paragraph">No, ThoughtSpot requires users to manually construct searches for each hypothesis. Domo needs pre-built dashboards. Scoop automatically investigates root causes through multi-pass analysis, testing correlations and anomalies without user guidance. It's the difference between searching for answers versus having them discovered for you.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">What does Domo really cost including implementation?</h3>
<p class="content-section__paragraph">Domo's true cost includes licenses, 3-6 month implementation, training programs, semantic layer maintenance, and ongoing consultants. Total typically reaches 5-10x the license fee. Scoop eliminates implementation, training, maintenance, and consultant costs—reducing TCO by 90% with just a simple subscription.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">How long does it take to learn Domo?</h3>
<p class="content-section__paragraph">Domo requires 2-4 weeks of formal training plus months to master dashboard building. ThoughtSpot needs 1-2 weeks for search syntax. Scoop requires zero training—if you can type a question, you're ready. Business users become productive immediately, not after expensive certification programs.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Can business users use Scoop without IT help?</h3>
<p class="content-section__paragraph">Yes, business users connect Scoop to data sources in 30 seconds and start asking questions immediately. Domo requires IT for data modeling and dashboard creation. ThoughtSpot needs IT-managed semantic layers. Scoop's AI handles all technical complexity, giving business users true analytical independence.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Does Domo work with Excel?</h3>
<p class="content-section__paragraph">Domo offers limited Excel exports but no native integration. ThoughtSpot has basic export functionality. Scoop works directly inside Excel—analyze data without leaving spreadsheets. Ask questions in familiar tools, get instant visualizations. It's analytics where business users actually work, not another portal to learn.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">How is Scoop different from traditional BI tools?</h3>
<p class="content-section__paragraph">Scoop is an AI analyst you chat with, not a dashboard platform. Traditional BI like Domo and ThoughtSpot require building views first, then exploring within limits. Scoop answers any question directly, investigates automatically, and requires zero technical setup. It's conversation, not configuration.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Are there hidden fees with ThoughtSpot?</h3>
<p class="content-section__paragraph">ThoughtSpot's hidden costs include semantic layer development, search training, performance optimization, and ongoing maintenance. Implementation typically adds 2-3x the license cost. Scoop has no hidden fees—one subscription covers everything. No consultants, no training, no maintenance contracts. Just ask questions and get answers.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Can I use ThoughtSpot directly in Slack?</h3>
<p class="content-section__paragraph">ThoughtSpot offers limited Slack notifications, not true integration. Domo has basic alerting. Scoop works natively in Slack—ask questions directly in channels, share insights instantly. Your team analyzes data where they collaborate, making data-driven decisions part of natural workflow, not a separate activity.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Do I need SQL knowledge for ThoughtSpot?</h3>
<p class="content-section__paragraph">ThoughtSpot claims no SQL required, but complex queries need search syntax training and formula understanding. Domo requires Beast Mode calculations. Scoop needs zero technical knowledge—just ask questions like you'd ask a colleague. The AI handles joins, calculations, and aggregations automatically.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">How many queries does Domo run to answer why questions?</h3>
<p class="content-section__paragraph">Domo runs single queries per dashboard widget—users manually navigate between views to investigate. ThoughtSpot executes one search at a time. Scoop automatically chains 3-10 queries, exploring hypotheses and correlations to find complete answers. It's investigation versus simple retrieval.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Why doesn't Scoop require training?</h3>
<p class="content-section__paragraph">Scoop uses natural language like ChatGPT—no syntax, formulas, or technical concepts to learn. Domo requires understanding data models and dashboard design. ThoughtSpot needs search syntax mastery. With Scoop, if you can ask a question in English, you can analyze data immediately.</p>
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</section>
<section class="cta-section">
<div class="cta-section__title">See Scoop in Action</div>
<div class="cta-section__subtitle">
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</div>
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