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<section class="hero--3way">
<div class="hero__container">
<div class="hero__eyebrow">AI-POWERED COMPARISON</div>
<h1 class="hero__title">Qlik Sense vs Zenlytic vs Scoop: Complete Comparison</h1>
<div class="hero__scores">
<div class="score-card score-card--competitor">
<div class="score-card__name">Qlik Sense</div>
<div class="score-card__score">47/100</div>
<div class="score-card__label">BUA Score</div>
</div>
<div class="score-card score-card--competitor">
<div class="score-card__name">Zenlytic</div>
<div class="score-card__score">42/100</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 Qlik Sense (47/100) and Zenlytic (42/100) 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 already invested in their ecosystems.</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 work. No SQL, no training, no semantic layer maintenance ever required.</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">You need multi-pass investigation (3-10 follow-up questions) without IT involvement</li>
<li class="content-section__list-item">Business users work primarily in Excel and need embedded analytics there</li>
<li class="content-section__list-item">You want to eliminate consultant dependencies and training costs permanently</li>
<li class="content-section__list-item">Teams need answers in minutes, not weeks of dashboard development</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Consider Qlik Sense If</h3>
<ul class="content-section__list">
<li class="content-section__list-item">You're already invested in the Qlik ecosystem with existing QVDs and apps</li>
<li class="content-section__list-item">Your use cases are purely operational dashboards with no investigation needs</li>
<li class="content-section__list-item">You have dedicated Qlik developers and accept ongoing maintenance costs</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Consider Zenlytic If</h3>
<ul class="content-section__list">
<li class="content-section__list-item">You specifically need SQL-based semantic layer for technical users</li>
<li class="content-section__list-item">Your team prefers writing code over natural language queries</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Bottom Line</h3>
<p class="content-section__paragraph">The 35-40 point BUA gap reveals a fundamental architectural divide. Scoop's investigation-first design eliminates five of six traditional BI cost categories - no consultants, minimal training, zero semantic layer maintenance, no implementation delays, and no productivity loss from waiting. Qlik Sense and Zenlytic's dashboard-centric architectures require continuous IT support for new questions, creating permanent dependencies. While both competitors offer capable visualization platforms, neither enables the iterative questioning pattern that defines real analysis. For organizations serious about business user empowerment, Scoop represents the shift from requesting reports to conducting investigations independently.</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>Qlik Sense</th><th>Zenlytic</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class=""><strong>BUA Score</strong></td><td class="">47/100</td><td class="">42/100</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>Qlik Sense</th><th>Zenlytic</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Investigation Depth</td><td class="">2/8</td><td class="">3/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Query Building</td><td class="">0/8</td><td class="">1/8</td><td class="">4/8</td>
</tr>
<tr>
<td class="">Setup Requirements</td><td class="">0/8</td><td class="">1/8</td><td class="">3/8</td>
</tr>
<tr>
<td class="">Learning Curve</td><td class="">0/8</td><td class="">1/8</td><td class="">3/8</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 Qlik Sense and Zenlytic's unscored status, enabling business users to investigate data through natural conversation without IT help. While Qlik requires dashboard creation and Zenlytic needs semantic layer setup, Scoop users start asking questions immediately with no technical knowledge required.</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>Qlik Sense</th><th>Zenlytic</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Workflow Integration</td><td class="">0/8</td><td class="">0/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Context Preservation</td><td class="">0/8</td><td class="">0/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Response Delivery</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Collaboration Flow</td><td class="">0/8</td><td class="">0/8</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 embedding analytics directly in Slack and Teams, while Qlik Sense and Zenlytic score 0/20 as portal-based tools requiring context switching. Scoop delivers answers where conversations happen; traditional BI platforms force users to leave their workflow for separate dashboards.</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>Qlik Sense</th><th>Zenlytic</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Natural Language Quality</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Business Terminology</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Error Handling</td><td class="">0/8</td><td class="">0/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Learning Curve</td><td class="">0/8</td><td class="">0/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Context Awareness</td><td class="">0/8</td><td class="">0/8</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 versus 0/20 for both Qlik Sense and Zenlytic. While Qlik Sense requires learning proprietary expression syntax and Zenlytic depends on semantic layer vocabulary, Scoop accepts natural business language immediately. Business users ask questions in plain English and get answers they understand without any training.</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>Qlik Sense</th><th>Zenlytic</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Output Format Flexibility</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="">Shareability</td><td class="">2/8</td><td class="">2/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Business Readiness</td><td class="">1/8</td><td class="">1/8</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 15/20 on Presentation by generating context-aware, business-ready outputs that include questions, answers, and insights together. Qlik Sense and Zenlytic require manual formatting and context addition for sharing. Scoop's conversational outputs work natively in Slack and email without recipient licenses.</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>Qlik Sense</th><th>Zenlytic</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Connection Setup</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Data Preparation</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Multi-Source Joins</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Data Freshness</td><td class="">0/8</td><td class="">0/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Governance Overhead</td><td class="">0/8</td><td class="">0/8</td><td class="">0/8</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, while Qlik Sense and Zenlytic weren't scored. Scoop lets business users connect any data source directly without IT help. Traditional BI platforms require weeks of data modeling and semantic layer setup before analysis can begin.</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 drops 15% unexpectedly, the difference between platforms isn't who can show you the drop—it's who can tell you why. Traditional BI excels at the 'what' through dashboards, but struggles with the 'why' that requires multiple investigative queries. Modern platforms promise AI-powered root cause analysis, but their architectural foundations determine whether business users can actually investigate independently or still need IT support. This capability separates true analytical autonomy from dashboard dependency.</p>
<p class="content-section__paragraph">Qlik Sense's associative model revolutionized data exploration when it launched, letting users click through relationships. But it still requires users to manually navigate connections and form their own hypotheses. You see the data relationships but must interpret them yourself. Zenlytic brings AI to the investigation process, automatically running statistical analyses and suggesting correlations. Users ask 'why did sales drop?' and get automated breakdowns by dimension. However, it still operates within a semantic layer that limits investigation to predefined metrics. Scoop approaches investigation like a conversation with an analyst. Ask 'why did revenue drop?' and it automatically checks seasonality, segments, anomalies, and correlations. Then ask 'what about competitor pricing?' and it maintains context while diving deeper. No semantic layer means it can investigate any pattern in raw data. The key difference: Qlik shows you data to explore, Zenlytic automates some analysis within boundaries, while Scoop conducts full investigations like a human analyst would. For business users, this means the difference between spending hours clicking through visualizations versus getting answers in minutes through conversation.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A retail operations manager notices conversion rates dropped 20% last week. With Qlik Sense, she opens the dashboard, clicks through product categories, regions, and time periods, manually looking for patterns. After 45 minutes of exploration, she spots that mobile conversion specifically tanked. She needs IT to build a new view to investigate device-specific issues. With Zenlytic, she asks 'why did conversion drop last week?' It automatically segments the drop, showing mobile as the issue. She asks follow-ups about mobile performance, getting deeper analysis within the semantic model's limits. With Scoop, she types the same question. Scoop automatically investigates: checks all segments, identifies mobile issue, correlates with a site update on Tuesday, and shows specific checkout page errors. She asks 'which products were most affected?' and gets immediate answers. Total investigation time: Qlik 2+ hours with IT help, Zenlytic 20 minutes within boundaries, Scoop 5 minutes with unlimited depth.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Qlik Sense pioneered visual data exploration but requires manual investigation and technical skills. Zenlytic adds AI automation but operates within semantic layer constraints. Scoop delivers true conversational investigation—like having a data analyst who instantly explores every angle. For business users facing urgent questions, the difference between 5 minutes and 2 hours isn't just efficiency—it's the difference between solving problems and watching them compound.</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 BI data into Excel to create the reports executives actually use. This disconnect between where data lives and where work happens costs enterprises millions in duplicate effort. The real question isn't whether platforms support Excel—it's whether they eliminate the need for that Monday morning export ritual. Modern platforms should bring analytics directly into Excel, not force users to choose between familiar tools and fresh data. Let's examine how each platform bridges this critical gap.</p>
<p class="content-section__paragraph">The architectural divide is stark. Qlik Sense treats Excel as a destination for data dumps—their add-in pulls from pre-built Qlik apps, requiring IT to maintain semantic layers and users to learn Qlik's interface first. You can't ask new questions from Excel; you're limited to what IT already built. Zenlytic offers no Excel integration at all, forcing complete platform abandonment for spreadsheet users. Their 'export to CSV' approach means every Monday starts with manual downloads and broken formulas. Scoop flips the paradigm: Excel becomes a natural language interface to your data. Type 'show me sales by region last quarter' in a cell, and get live results. No semantic layer maintenance, no IT tickets, no Monday morning export ritual. The difference compounds over time. A financial analyst updating weekly reports saves 2 hours per week with live connections versus manual exports. Across a 50-person FP&A team, that's 5,200 hours annually. But the real gain is agility—when the CFO asks a follow-up question during the board meeting, you answer it from Excel in real-time, not promise to 'run that query after the meeting.'</p>
<p class="content-section__paragraph"><strong>Example</strong>: Sarah, a financial analyst, maintains 15 weekly Excel reports for executive leadership. With Qlik Sense, she opens each report Monday morning, launches Qlik, navigates to the right app, exports updated data, pastes into Excel, and fixes broken references. Total time: 3 hours. If an executive asks for a different view, she submits an IT ticket for a new Qlik object. With Zenlytic, she manually exports 15 CSV files, copies data, and rebuilds formulas that break each week. Any new question means logging into Zenlytic, writing SQL, and exporting again. With Scoop, her Excel templates contain formulas like =SCOOP('revenue by product line last 30 days'). Opening the spreadsheet auto-refreshes everything. When the CFO asks 'what about enterprise customers only?', she modifies the formula to =SCOOP('revenue by product line last 30 days for enterprise customers') and gets instant results. Weekly time: 20 minutes versus 3 hours.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Excel integration reveals each platform's true philosophy. Qlik and Zenlytic treat Excel as a necessary evil—a place data goes to die. Scoop treats Excel as a legitimate analytics interface where 500 million users already work. The difference isn't technical; it's philosophical. Do you force users to abandon their tools or meet them where they are? For enterprises spending millions on BI platforms that users bypass for Excel exports, Scoop's approach eliminates the entire problem.</p>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Side-by-Side Scenario Analysis</h3>
<p class="content-section__paragraph">When executives need to compare multiple business scenarios—like 'What if we raise prices 10% versus cutting costs 15%?'—they're testing strategic decisions worth millions. Traditional BI forces this analysis into Excel exports and manual calculations. Modern platforms should enable instant scenario comparison without leaving the analysis environment. The difference between platforms isn't whether they can show scenarios, but how many steps business users need to compare them side-by-side. Let's examine how each platform handles this critical strategic planning capability.</p>
<p class="content-section__paragraph">Qlik Sense handles scenarios through its alternate states feature, but setup requires technical knowledge of set analysis expressions. Business users must request IT support to create comparative visualizations. Each scenario needs manual configuration in the data model. Zenlytic offers better natural language support but lacks true side-by-side display. Users describe scenarios conversationally, yet must run them sequentially and mentally compare results. No automatic visual comparison exists. Scoop transforms scenario analysis through conversational AI. Users type 'Compare revenue if we increase prices 10% versus expanding to three new markets.' Scoop automatically generates side-by-side visualizations showing impact across all metrics. The key architectural difference: Scoop's AI understands business intent and creates comparative analysis automatically. Qlik and Zenlytic require users to manually construct each comparison. This isn't just convenience—it's the difference between testing three scenarios or thirty in a strategy session. When boards ask 'What are our options?', Scoop users explore dozens of scenarios while competitors struggle with three.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A CFO preparing for board meeting needs to compare three growth strategies: raising prices 8%, cutting operational costs 12%, or investing $5M in marketing. With Scoop, she types: 'Show me revenue, profit, and cash flow for these three scenarios side by side.' Scoop instantly displays comparative charts with all three scenarios overlaid. She adjusts: 'What if we combine 5% price increase with $3M marketing spend?' New comparison appears in seconds. Total analysis time: 5 minutes. In Qlik Sense, she would need IT to create alternate states for each scenario, build calculated measures incorporating variables, and design comparative visualizations. Timeline: 2-3 days. Zenlytic would let her describe scenarios but require running each separately, copying results to Excel for comparison. The board gets static slides instead of dynamic exploration.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Scoop delivers true scenario comparison through natural conversation, while Qlik Sense requires technical setup and Zenlytic lacks side-by-side display. The business impact is dramatic: strategic decisions in minutes versus days. When every delayed decision costs money, Scoop's instant scenario analysis transforms planning from a technical project into a business conversation.</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 customer churn, forecast demand spikes, and reveal competitive threats. But discovering these insights shouldn't require a data science degree. 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 pattern discovery, from automatic anomaly detection to predictive analytics that anyone can understand and act upon.</p>
<p class="content-section__paragraph">Qlik Sense's Insight Advisor promises AI-powered discovery but requires extensive data model preparation. Users must define associations, configure KPIs, and train the system on business logic. The cognitive engine generates insights, but they're limited to pre-modeled relationships. Zenlytic takes a technical approach—users write SQL queries with statistical functions for pattern detection. Want correlation analysis? Write a correlation matrix query. Need outlier detection? Code a z-score calculation. Both platforms treat ML as an add-on requiring special skills. Scoop embeds pattern discovery into natural conversation. Ask 'What's driving customer churn?' and Scoop automatically runs correlation analysis, checks seasonal patterns, identifies outliers, and presents findings in plain English. No configuration, no SQL, no data science degree. The difference is architectural: Qlik and Zenlytic bolt ML onto traditional BI. Scoop builds ML into the investigation engine itself. This means business users get sophisticated analysis without knowing they're using machine learning. They just ask questions and get answers that include patterns they didn't know to look for.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A retail operations manager notices unusual inventory patterns. With Scoop, she types: 'Find patterns in our inventory turnover rates.' Scoop automatically analyzes seasonality, identifies products with abnormal behavior, correlates with promotional calendars, and discovers that items near checkout have 3x higher turnover during flash sales. Total interaction: one question, complete analysis in 45 seconds. In Qlik Sense, she'd need IT to configure Insight Advisor rules, define inventory KPIs, and model promotional relationships—a two-week project. With Zenlytic, she'd write multiple SQL queries: one for turnover calculation, another for seasonal decomposition, a third for correlation analysis. Each query requires statistical knowledge she doesn't have. The business impact? Scoop users discover patterns daily. Qlik and Zenlytic users wait for IT or analysts to configure pattern detection.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Machine learning shouldn't require a PhD to use. Qlik Sense requires extensive configuration and data modeling before AI insights appear. Zenlytic demands SQL expertise for any statistical analysis. Scoop makes pattern discovery conversational—business users just ask questions and get answers enriched with automatic anomaly detection, correlation analysis, and predictive insights. The result: patterns that would take hours to uncover manually surface in seconds through natural conversation.</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 data work happens everywhere—Excel models, Slack threads, mobile devices, email reports. The real test isn't whether a platform has an API or mobile app. It's whether business users can actually access insights where they work, without IT building custom integrations. Let's examine how each platform handles the reality of distributed work, from the CFO checking metrics on their phone to analysts collaborating in Slack to managers updating Excel reports.</p>
<p class="content-section__paragraph">The workflow integration divide reflects fundamental architecture choices. Qlik Sense follows the traditional BI pattern: powerful visualization engine, weak integration layer. Users get beautiful dashboards but can't access them where work happens. Mobile means viewing pre-built reports, not investigating new questions. Excel integration stops at copy-paste. Slack integration is just alert notifications. . Zenlytic, targeting technical users, assumes everyone works in their web interface. No Excel add-in. No mobile app. No Slack integration. Their API requires writing SQL, defeating the purpose of natural language. . Scoop's architecture—natural language at the core—enables true workflow integration. The Excel add-in lets analysts query databases without leaving spreadsheets. Slack integration means full conversational analytics in channels. Mobile isn't a viewer but a complete analyst. The API accepts plain English, not SQL. . This isn't about feature count. It's about meeting users where they already work.</p>
<p class="content-section__paragraph"><strong>Example</strong>: Monday morning. The VP of Sales is on a flight to a client meeting when she gets a text: 'Deal velocity dropped 30% last week.' With Qlik Sense mobile, she can open the sales dashboard and see the drop—but can't investigate why. She messages her analyst on Slack: 'Can you dig into this?' The analyst has to leave Slack, log into Qlik, build new visualizations, export to Excel for calculations, then screenshot results back to Slack. Total time: 45 minutes. With Scoop, the VP opens the mobile app and types: 'Why did deal velocity drop last week?' She gets an automatic investigation showing it's isolated to the enterprise segment, specifically deals over $100K, coinciding with a pricing change. She shares the finding directly to the sales Slack channel where her team can ask follow-up questions without leaving the conversation. Total time: 3 minutes. The difference: investigation capability that travels with you versus static dashboards that don't.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Workflow integration reveals the gap between 'having features' and 'enabling work.' Qlik Sense offers traditional BI exports and mobile viewers—fine for consuming reports, useless for investigation. Zenlytic ignores workflows entirely, assuming technical users live in their interface. Scoop brings full analytical power to where business users actually work: Excel, Slack, mobile, email. The business impact is measurable: 73% less context switching, 2 hours saved daily per analyst, and executives who can investigate problems from anywhere.</p>
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<h2 class="content-section__title">Frequently Asked Questions</h2>
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<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 Qlik Sense and Zenlytic which require IT setup, Scoop connects directly to your data in 30 seconds.</p>
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<h3 class="content-section__subtitle">How do I investigate anomalies in Qlik Sense?</h3>
<p class="content-section__paragraph">Qlik Sense requires building multiple dashboards and manual drill-downs to investigate anomalies. Users navigate pre-built visualizations hoping to find answers. Scoop automatically runs 3-10 queries to identify root causes, testing hypotheses like an analyst would. This multi-pass investigation finds insights dashboards miss entirely.</p>
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<h3 class="content-section__subtitle">Can Zenlytic do root cause analysis automatically?</h3>
<p class="content-section__paragraph">No, Zenlytic requires users to manually construct SQL queries for root cause analysis. Its semantic layer helps but doesn't automate investigation. Scoop automatically chains 3-10 queries, testing hypotheses and drilling into anomalies without user intervention. Business users get root causes in seconds, not hours.</p>
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<h3 class="content-section__subtitle">Does Scoop support multi-step analysis?</h3>
<p class="content-section__paragraph">Yes, Scoop excels at multi-step analysis, automatically chaining 3-10 queries per investigation. Unlike Qlik Sense's single dashboard view or Zenlytic's manual SQL approach, Scoop thinks like an analyst—forming hypotheses, testing them, and drilling deeper until finding root causes. No technical knowledge required.</p>
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<h3 class="content-section__subtitle">Does Qlik Sense work with Excel?</h3>
<p class="content-section__paragraph">Qlik Sense offers limited Excel export functionality requiring multiple steps and losing interactivity. Users must navigate menus, select data, and export static snapshots. Scoop works natively inside Excel—analyze data directly where you work. No exports, no switching applications, just natural conversation with your data.</p>
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<h3 class="content-section__subtitle">Can I use Zenlytic directly in Slack?</h3>
<p class="content-section__paragraph">Zenlytic doesn't offer native Slack integration—users must switch to their web portal for analysis. This breaks workflow and reduces adoption. Scoop works directly in Slack, letting teams analyze data where they collaborate. Ask questions, share insights, make decisions without leaving your conversation.</p>
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<h3 class="content-section__subtitle">What does Qlik Sense really cost including implementation?</h3>
<p class="content-section__paragraph">Qlik Sense true cost includes licenses, 3-6 month implementation, training programs, semantic layer maintenance, consultants, and lost productivity. Organizations typically spend 5-10x the license fee annually. Scoop eliminates implementation, training, and consultant costs—just a simple subscription reducing TCO by 90%.</p>
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<h3 class="content-section__subtitle">Are there hidden fees with Zenlytic?</h3>
<p class="content-section__paragraph">Zenlytic's hidden costs include semantic layer setup, SQL training, data modeling consultants, and ongoing maintenance. The platform fee is just the beginning. Most organizations need dedicated technical resources. Scoop has no hidden fees—one subscription covers everything. No consultants, no training, no maintenance.</p>
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<h3 class="content-section__subtitle">How long does it take to learn Qlik Sense?</h3>
<p class="content-section__paragraph">Qlik Sense requires 2-4 weeks of formal training plus months of practice to become proficient. Users must learn data modeling, set analysis, and dashboard design. Scoop requires zero training—if you can type a question, you can analyze data. Business users become productive immediately.</p>
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<h3 class="content-section__subtitle">Do I need SQL knowledge for Zenlytic?</h3>
<p class="content-section__paragraph">Yes, Zenlytic requires SQL knowledge for anything beyond basic queries. Their semantic layer helps but doesn't eliminate SQL requirements for complex analysis. Scoop requires zero SQL—just ask questions in plain English. The AI handles all technical complexity, letting business users focus on insights.</p>
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<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 and start analyzing in 30 seconds without IT. Qlik Sense requires IT for setup, maintenance, and changes. Zenlytic needs technical help for semantic layer updates. Scoop's 82/100 BUA score proves true business user autonomy.</p>
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<h3 class="content-section__subtitle">Which is better for business users: Qlik Sense or Zenlytic?</h3>
<p class="content-section__paragraph">Neither excels for business users. Qlik Sense scores 47/100 BUA requiring extensive training. Zenlytic scores 42/100 needing SQL knowledge. Both trap users in IT-dependent workflows. Scoop's 82/100 BUA score and natural language interface delivers true business user empowerment without technical barriers.</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 another dashboard builder. Traditional BI like Qlik and Zenlytic require building views before asking questions. Scoop starts with questions, automatically running multiple queries to find answers. No dashboards, no SQL, just conversation with data.</p>
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<h3 class="content-section__subtitle">Why doesn't Scoop require training?</h3>
<p class="content-section__paragraph">Scoop uses natural language like ChatGPT—if you can ask a question, you can use Scoop. Qlik Sense requires learning their expression language. Zenlytic needs SQL knowledge. Scoop's AI understands business questions directly, eliminating the technical translation layer that makes traditional BI complex.</p>
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<section class="cta-section">
<div class="cta-section__title">See Scoop in Action</div>
<div class="cta-section__subtitle">
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