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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 Sisense 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">Sisense</div>
<div class="score-card__score">47/100</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 Sisense (28/100) trap users in dashboard paradigms. Both competitors require IT intervention for new questions, creating the exact bottlenecks Scoop eliminates. Choose Scoop for immediate independence, competitors only if locked into existing vendor 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 required ever.</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 answers to unexpected questions without waiting for IT</li>
<li class="content-section__list-item">You want to eliminate dashboard maintenance and semantic layer overhead completely</li>
<li class="content-section__list-item">Excel is your team's primary tool and you need analytics there</li>
<li class="content-section__list-item">Investigation requires 3-10 follow-up questions, not just drill-downs</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 heavily in Qlik's ecosystem and can't migrate</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 IT resources for constant dashboard maintenance</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Consider Sisense If</h3>
<ul class="content-section__list">
<li class="content-section__list-item">You need embedded analytics in custom applications specifically</li>
<li class="content-section__list-item">Your organization requires on-premise deployment with no cloud options</li>
</ul>
</div>
<div class="content-section__subsection">
<h3 class="content-section__subtitle">Bottom Line</h3>
<p class="content-section__paragraph">The BUA scores reveal the truth: Scoop's 82/100 represents genuine business empowerment while competitors languish below 50/100 . Business users gain immediate independence to investigate data themselves.</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>Sisense</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class=""><strong>BUA Score</strong></td><td class="">47/100</td><td class="">28/100</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>Sisense</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 Independence</td><td class="">1/8</td><td class="">2/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Setup Requirements</td><td class="">0/8</td><td class="">0/8</td><td class="">4/8</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 Sisense at 0/20 (unscored). Scoop enables full conversational investigation without IT help, while Qlik Sense and Sisense require IT-built dashboards and data models before business users can explore. Business users ask questions directly in Scoop; competitors need technical setup first.</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>Sisense</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Workflow Integration</td><td class="">2/8</td><td class="">2/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Context Preservation</td><td class="">1/8</td><td class="">1/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Response Delivery</td><td class="">2/8</td><td class="">2/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Collaboration Features</td><td class="">3/8</td><td class="">3/8</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 living natively in Slack and Teams, while Qlik Sense and Sisense score near zero, trapping users in separate portals. Scoop eliminates context switching between work chat and analytics, saving 2-3 hours weekly per user through integrated workflow.</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>Sisense</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Natural Language Quality</td><td class="">0/8</td><td class="">2/8</td><td class="">8/8</td>
</tr>
<tr>
<td class="">Business Terminology</td><td class="">0/8</td><td class="">1/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Error Clarity</td><td class="">0/8</td><td class="">0/8</td><td class="">1/8</td>
</tr>
<tr>
<td class="">Learning Curve</td><td class="">0/8</td><td class="">0/8</td><td class="">1/8</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 Sisense. While Qlik Sense and Sisense require users to understand data models and technical terminology, Scoop uses conversational AI to accept natural business questions. This eliminates weeks of training and IT translation requests.</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>Sisense</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Chart Selection</td><td class="">0/8</td><td class="">0/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Formatting</td><td class="">0/8</td><td class="">0/8</td><td class="">5/8</td>
</tr>
<tr>
<td class="">Context Awareness</td><td class="">0/8</td><td class="">0/8</td><td class="">4/8</td>
</tr>
<tr>
<td class="">Export Quality</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 15/20 on Presentation versus 0/20 for Qlik Sense and Sisense. Scoop automatically selects and formats charts based on question context, while Qlik Sense and Sisense require manual chart selection and extensive formatting through property panels, adding hours to every analysis.</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>Sisense</th><th>Scoop</th>
</tr>
</thead>
<tbody>
<tr>
<td class="">Direct Connection</td><td class="">2/8</td><td class="">1/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Schema Flexibility</td><td class="">1/8</td><td class="">2/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Data Preparation</td><td class="">2/8</td><td class="">1/8</td><td class="">7/8</td>
</tr>
<tr>
<td class="">Source Variety</td><td class="">3/8</td><td class="">3/8</td><td class="">6/8</td>
</tr>
<tr>
<td class="">Refresh Management</td><td class="">2/8</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 16/20 on data capabilities versus near-zero for Qlik Sense and Sisense. While Qlik Sense requires IT to build associative models and Sisense needs ElastiCube preparation, Scoop connects directly to databases for immediate analysis. Business users start investigating in minutes instead of waiting weeks for IT setup.</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 architecture difference shows in practice. Qlik Sense's associative model lets users explore data relationships through clicking and filtering. Users navigate green/white/gray associations to find patterns. This works well for trained analysts but requires understanding Qlik's unique paradigm. Sisense focuses on pre-built dashboards with some drill-down capability. Users can filter and segment, but each new question requires building another widget or dashboard. Neither platform supports true conversational investigation. Scoop's AI analyst architecture enables multi-pass investigation through natural conversation. Ask 'Why did sales drop?' and Scoop automatically checks seasonality, segments, products, and regions. Follow up with 'What about competitor pricing?' without losing context. The AI generates hypotheses you might not consider—like correlation with marketing spend changes or sales team turnover. This isn't about better dashboards. It's about enabling business users to conduct complex root cause analysis independently. Where traditional BI requires 5-10 manual queries taking an hour, Scoop reaches the same conclusion in 3-5 minutes through intelligent automation.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A retail operations manager notices inventory turnover dropped 20% last month. With Qlik Sense, she opens the inventory dashboard, clicks through product categories, filters by region, checks the calendar for seasonality, then manually compares to previous periods. After 45 minutes of clicking through associations, she identifies slow-moving items in three stores. With Sisense, she'd need IT to build specific queries for each investigation angle. With Scoop, she types: 'Why did inventory turnover drop last month?' Scoop automatically analyzes: product mix changes, seasonal patterns, store-level variations, and supplier delivery delays. In 3 minutes, it identifies that delayed shipments from two suppliers caused stockouts of fast-moving items, forcing stores to hold more slow-moving inventory. She asks: 'Which products were most affected?' and gets specific SKUs to address. Total investigation time: 5 minutes versus 45+ minutes of manual exploration.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Investigation capability separates Scoop from traditional BI dashboards. While Qlik Sense offers data exploration through its associative model and Sisense provides dashboard drill-downs, only Scoop enables true conversational investigation. Business users can pursue complex root cause analysis through natural dialogue, with AI automatically generating and testing hypotheses. This 10x speed improvement in reaching root cause transforms how organizations respond to critical business changes.</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 costs enterprises millions in duplicate work and stale data. The irony? Excel remains where 750 million business users live, yet most BI platforms treat it as an afterthought. True Excel integration means working where users already are, not forcing them into yet another portal. Let's examine how each platform bridges—or fails to bridge—this critical gap.</p>
<p class="content-section__paragraph">Qlik Sense offers the most complete traditional integration with its Excel add-in, allowing users to pull Qlik objects directly into spreadsheets. But here's the catch: you still need to know Qlik's interface and have pre-built visualizations. It's a bridge, not a solution. Sisense takes the opposite approach—no Excel integration at all. Users export static CSV files and rebuild everything manually. Every Monday, thousands of hours vanish into this black hole of busywork. Scoop flips the entire model. Instead of pulling from another platform, you chat with your data directly in Excel. Type 'What drove the revenue spike in March?' and get an answer with charts, right in your spreadsheet. No training, no pre-built objects, no IT tickets. The architectural difference is profound: Qlik extends its platform into Excel (bringing complexity with it), while Scoop makes Excel itself intelligent. For the 750 million Excel users worldwide, this isn't just convenience—it's the difference between actually using analytics and letting licenses expire.</p>
<p class="content-section__paragraph"><strong>Example</strong>: Sarah, a financial analyst, needs to update the monthly board deck. With Qlik Sense, she opens the web portal, navigates to the right dashboard, exports the data, switches to Excel, imports it, and manually recreates the formatting. Time: 45 minutes. With Sisense, she doesn't even try—she knows IT would need to build an export first. With Scoop, she types in Excel: 'Show me revenue by product line, last 6 months, with month-over-month growth.' The chart appears instantly. She asks: 'Why did Enterprise grow 40% in March?' Scoop identifies the three major deals that drove it. Total time: 3 minutes. The board deck updates itself with live data. No exports, no rebuilding, no stale numbers.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Qlik Sense provides traditional BI-to-Excel connectivity that still requires platform expertise. Sisense offers nothing beyond manual exports, treating Excel as a data graveyard. Scoop transforms Excel into an intelligent analysis environment where any user can investigate data using plain English. For organizations where Excel is the de facto analytics platform, Scoop eliminates the entire extract-transform-present cycle that consumes 20% of analyst time.</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 compare multiple scenarios simultaneously. This isn't about running one analysis then another—it's about seeing alternatives side-by-side to make informed choices. Traditional BI forces sequential analysis through separate dashboards or reports. Modern platforms should enable parallel scenario exploration. Let's examine how Qlik Sense, Sisense, and Scoop handle this critical strategic capability that drives everything from pricing decisions to market expansion planning.</p>
<p class="content-section__paragraph">The architectural divide becomes stark in scenario analysis. Qlik Sense offers powerful set analysis but requires users to understand expressions like {<Year={2024}, Region={'North'}>} to create scenarios. Business users typically need IT support to build comparative views. Sisense provides dashboard duplication but lacks native side-by-side comparison—users toggle between tabs, losing visual context. Neither platform handles dynamic scenario generation well. Users must pre-build each scenario variation. Scoop transforms this through conversational scenario creation. Ask 'Compare revenue if we increase prices 10% versus adding 50 new customers' and get instant side-by-side analysis. The AI understands business logic, automatically adjusting related metrics like margin and customer acquisition cost. No formula writing. No dashboard cloning. This isn't just convenience—it's about exploration speed. Strategic planning sessions that took hours of dashboard preparation now happen in real-time. The conversation becomes the analysis.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A CPO needs to evaluate three pricing strategies for next quarter. With Qlik Sense, she requests IT to create three parallel dashboards with modified set analysis expressions—a two-day turnaround. Each scenario requires manual formula adjustments for revenue impact, margin changes, and volume projections. Sisense allows her to duplicate dashboards herself, but she must manually adjust filters and calculations in each copy, taking 3-4 hours. Switching between tabs to compare loses visual context. With Scoop, she types: 'Show me revenue impact comparing 10% price increase, volume discount strategy, and premium tier addition.' Scoop generates side-by-side comparisons instantly, automatically calculating cascading effects on margins, customer segments, and competitive positioning. Follow-up questions like 'What if competitor matches our pricing?' extend the analysis naturally. Total time: 5 minutes versus hours or days.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Scenario analysis reveals the gulf between dashboard tools and investigation platforms. Qlik Sense and Sisense require technical expertise and manual setup for each scenario—turning strategic planning into IT projects. Scoop enables real-time scenario exploration through natural conversation, letting business leaders test hypotheses as fast as they can think of them. This isn't about features; it's about whether strategy discussions happen in boardrooms or ticket queues.</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 patterns 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 Qlik Sense, Sisense, and Scoop handle pattern discovery when a marketing manager asks 'Which customers are likely to churn next quarter?' or a supply chain director needs to know 'What's driving these inventory anomalies?'</p>
<p class="content-section__paragraph">The architecture tells the story. Qlik Sense treats ML as an add-on—you need Qlik AutoML ($30K+ annually) plus training to use it effectively. Their Insight Advisor provides basic pattern suggestions, but complex analysis requires switching to specialized tools. Sisense follows the traditional path: data scientists build models in Python or R, then deploy them through Sisense Fusion. Business users see results but can't explore patterns themselves. Scoop flips this model. Every query automatically runs pattern detection. Ask 'What's unusual about last month's sales?' and Scoop identifies statistical anomalies, checks correlations, and highlights outliers—no configuration needed. The key difference is investigation depth. When Scoop finds an anomaly, you can immediately ask 'Why?' and it investigates potential causes. Qlik and Sisense show you the anomaly but leave investigation to manual analysis. This architectural choice matters. A Forrester study found 67% of business users abandon advanced analytics tools within 6 months due to complexity. Scoop's approach keeps ML invisible but results visible.</p>
<p class="content-section__paragraph"><strong>Example</strong>: A retail operations manager notices inventory discrepancies across stores. With Scoop, she types: 'Find patterns in inventory variances by store.' Scoop automatically clusters stores by behavior, identifies that Tuesday deliveries show 3x more discrepancies, correlates this with staffing levels, and discovers understaffed stores have 47% higher variance rates. Total investigation: 4 minutes, 3 follow-up questions. In Qlik Sense, she'd need to manually create visualizations, configure the Insight Advisor, potentially engage IT for AutoML setup, and still wouldn't get the staffing correlation without explicit configuration. Sisense would require their data team to build a custom model, deploy it through Fusion, and create a dashboard—a 2-3 week process. The business impact? Scoop identified a $2.3M inventory problem in minutes that traditional BI platforms would take weeks to surface.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Machine learning in BI platforms typically means 'data scientists build models that business users view in dashboards.' Scoop reverses this: business users ask questions and ML happens automatically behind the scenes. While Qlik and Sisense offer powerful ML capabilities, they require technical expertise, additional licenses, and lengthy implementation. Scoop makes pattern discovery as simple as asking a question, turning every business user into a data detective.</p>
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<h3 class="content-section__subtitle">Workflow Integration & Mobile</h3>
<p class="content-section__paragraph">Your sales team closes a deal during their morning commute. The finance analyst investigates a variance from their couch. The CEO reviews quarterly performance between meetings. Modern business happens everywhere, yet most BI platforms chain users to their desks. The real test isn't whether a platform has a mobile app—it's whether business users can actually get answers when and where they need them. Let's examine how each platform handles the reality of distributed, always-on business intelligence.</p>
<p class="content-section__paragraph">The workflow integration divide reveals a fundamental architectural difference. Qlik Sense and Sisense built their platforms assuming users would come to them—hence the 'portal prison' architecture where everything happens inside their application. Their mobile apps are essentially dashboard viewers, not investigation tools. You can see the KPI dropped, but you can't ask why. Scoop's chat-based architecture naturally extends everywhere. The same conversation interface works in Excel, Slack, mobile, or any system with an API. A sales manager can start investigating win rates in Excel, continue the analysis in Slack with their team, and finish on mobile during their commute. It's the same conversation thread, same context, same capability. Qlik's Excel add-in only pulls pre-built visualizations. Sisense requires exporting data and losing all interactivity. Neither supports true investigation outside their main platform. The business impact is stark: with traditional BI, mobile means viewing yesterday's dashboard. With Scoop, mobile means asking new questions and getting immediate answers. This isn't about features—it's about architecture. Chat naturally goes everywhere. Dashboards don't.</p>
<p class="content-section__paragraph"><strong>Example</strong>: Monday morning, 7:45 AM. The VP of Sales is on the train when she gets a text about a major deal falling through. With Scoop's mobile app, she types: 'What other deals are at risk this quarter?' Scoop analyzes the CRM data and identifies three similar deals showing warning signs. She shares the analysis thread to the sales team's Slack channel with a question: 'Can someone investigate why these accounts went cold?' Two account executives jump in, asking follow-up questions directly in Slack. By 8:30 AM, before she even reaches the office, they've identified a competitor's new pricing strategy affecting all three deals. With Qlik Sense or Sisense, she would have opened the mobile app, viewed a static pipeline dashboard, seen the deal was at risk (which she already knew), and had to wait until reaching her laptop to begin any real investigation. The team collaboration would require screenshots, emails, and multiple tools.</p>
<p class="content-section__paragraph"><strong>Bottom Line</strong>: Workflow integration isn't about having a mobile app or an API—it's about maintaining full analytical capability wherever business happens. Qlik Sense and Sisense offer mobile viewers for pre-built content. Scoop extends complete investigation capability to Excel, Slack, and mobile. When your business moves at the speed of Slack conversations and mobile decisions, the difference between viewing dashboards and asking questions becomes the difference between watching problems and solving them.</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 Qlik Sense and Sisense which require IT setup, Scoop connects directly to your data in 30 seconds.</p>
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<h3 class="content-section__subtitle">Which is better for business users: Qlik Sense or Sisense?</h3>
<p class="content-section__paragraph">Qlik Sense scores 47/100 on business autonomy versus Sisense's 28/100. Both require IT support for data modeling and dashboard creation. Scoop's 82/100 score means business users work independently. Neither Qlik nor Sisense enables true self-service—both trap users in pre-built dashboards requiring IT for changes.</p>
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<div class="content-section__subsection">
<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 or using set analysis expressions for anomaly investigation. Users navigate pre-built paths, not true investigation. Scoop automatically runs 3-10 queries to find root causes, testing hypotheses like an analyst would. Qlik's single-query architecture prevents dynamic multi-step analysis.</p>
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<h3 class="content-section__subtitle">Can Sisense do root cause analysis automatically?</h3>
<p class="content-section__paragraph">No, Sisense requires manual dashboard drilling and pre-configured drill paths. Its Pulse feature alerts to changes but doesn't investigate why. Scoop automatically chains queries to find root causes—checking segments, time periods, and correlations. Sisense's dashboard paradigm can't match true investigative analysis requiring multiple dynamic queries.</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. Ask 'why did sales drop?' and it checks regions, products, time periods, and correlations automatically. Unlike Qlik Sense and Sisense's single-query dashboards, Scoop thinks like an analyst—forming hypotheses, testing them, and drilling deeper until finding answers.</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, ongoing maintenance, consultant fees, and productivity loss. Total typically reaches 5-10x the license fee. Scoop eliminates implementation, training, maintenance, and consultant costs—reducing TCO by 90%. Hidden costs make Qlik far more expensive than advertised.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Are there hidden fees with Sisense?</h3>
<p class="content-section__paragraph">Yes, Sisense's hidden costs include data modeling consultants, ElastiCube maintenance, user training, and ongoing dashboard development. Implementation alone often costs 2-3x annual licenses. Scoop has no hidden fees—just a subscription. No consultants, no training, no maintenance. The advertised price is the actual price.</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 for basic proficiency, months for advanced features. Users must learn data modeling, set analysis, and expression 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">Do I need SQL knowledge for Sisense?</h3>
<p class="content-section__paragraph">Yes, Sisense requires SQL for custom queries and data preparation. Their ElastiCube technology needs SQL understanding for optimization. Even 'code-free' features require technical knowledge. Scoop translates plain English to SQL automatically. Ask questions naturally—Scoop handles the technical complexity behind the scenes.</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. No semantic layer setup, no data modeling, no dashboard building. Qlik Sense and Sisense both require IT for initial setup and ongoing maintenance. Scoop delivers true self-service analytics.</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. Ask questions naturally, get answers with charts. No building, no configuring, no training. Qlik Sense and Sisense require months of setup and IT support. Scoop works immediately—like having a data analyst on your team.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Does Qlik Sense work with Excel?</h3>
<p class="content-section__paragraph">Qlik Sense offers limited Excel export but no native integration. Users export static data, losing interactivity. Scoop works directly inside Excel—ask questions in a sidebar, get live answers. No switching applications, no static exports. Your analysis stays dynamic and connected to real-time data sources.</p>
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<div class="content-section__subsection">
<h3 class="content-section__subtitle">Can I use Sisense directly in Slack?</h3>
<p class="content-section__paragraph">Sisense's Slack integration only shares dashboard screenshots and basic alerts. You can't ask new questions or investigate issues. Scoop works natively in Slack—ask any question, get answers instantly. No leaving Slack, no switching to dashboards. True conversational analytics where your team already works.</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—if you can ask a colleague a question, you can use Scoop. No query languages, no technical syntax, no dashboard building. Qlik Sense requires learning expressions and data modeling. Sisense needs ElastiCube training. Scoop's AI handles all technical complexity automatically.</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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</section>
