Frequently Asked Questions

Yes, absolutely. Your data never leaves your device. Segmentor.app runs entirely in your browser using local processing—we never see, store, or transmit your customer data anywhere.

Think of it like using a calculator: the numbers you enter stay on your device. We don't have servers collecting your information because there's nothing to collect. Your customer data remains 100% private and under your control.

Key security features:

• ✅ Zero cloud storage—all processing happens locally
• ✅ No data transmission to external servers
• ✅ Your files stay on your computer
• ✅ You can work offline once the page loads

When you export your analysis as a .seg file or PDF report, those files are created directly on your device and saved to your chosen location.

No, we don't use cookies. Segmentor.app doesn't track you, create user profiles, or store any browsing data. We respect your privacy by design. The tool runs entirely in your browser with no account requirements for standard use.

Only on your device. Your customer data is stored in two ways, both completely under your control:

1. Browser temporary storage (automatic): When you're working on a segmentation, your data is temporarily held in your browser's memory. You can clear this anytime through your browser settings.

2. .seg project files (manual): Use the Save button to export your complete project as a .seg file to your computer. You choose where to store it—it's just a regular file you control.

Yes, because we never see it. This isn't just a privacy promise—it's how the technology works. segmentor.app uses a privacy-by-design architecture. All calculations happen in your browser using JavaScript, similar to how a spreadsheet works.

Yes and no—we give you the choice! The original 1995 Apostles Model used specific terminology:

• Apostles (a sub-zone within Loyalists)
• Terrorists (a sub-zone within Defectors)

We've modernised these terms to:

• Advocates (instead of Apostles)
• Trolls (instead of Terrorists)

You choose: In the visualisation controls, switch between 'Modern' and 'Classic' terminology. The segmentation logic stays the same—only the labels change. We default to modern terms but respect those who prefer the original academic language.

Loyalists are the full quadrant (top-right) of customers with both high satisfaction and high loyalty.

Advocates are the most loyal and satisfied customers within that quadrant—essentially 'Loyalists Plus.' They don't just stay—they actively promote you.

Think of it like this: All Advocates are Loyalists, but not all Loyalists are Advocates. Advocates are your superfans.

The Apostles Model is a customer segmentation framework that classifies customers into four groups based on two dimensions: satisfaction and loyalty. It was developed by Thomas O. Jones and W. Earl Sasser Jr. in their groundbreaking 1995 Harvard Business Review article "Why Satisfied Customers Defect."

The classic model identified four customer types:

• Loyalists: High satisfaction + High loyalty (includes Apostles sub-zone)
• Mercenaries: High satisfaction + Low loyalty
• Hostages: Low satisfaction + High loyalty
• Defectors: Low satisfaction + Low loyalty (includes Terrorists sub-zone)

An Apostle is a sub-zone within the Loyalists quadrant—customers with both high satisfaction AND high loyalty who are your best customers and genuinely love what you do.

Characteristics of Apostles:

• ✅ Highly satisfied with your product/service
• ✅ Actively recommend you to others
• ✅ Resist competitive offers
• ✅ Forgive occasional mistakes
• ✅ Provide valuable feedback
• ✅ Drive most of your organic growth

Proximity analysis identifies customers positioned near segment boundaries who could move between segments with targeted interventions. We use different distance calculation methods depending on the type of proximity:

Lateral Proximity (adjacent quadrants, like Loyalists near Mercenaries):

• Uses single-dimension distance measurement
• Calculates distance in one direction only (either satisfaction OR loyalty, whichever is relevant to the boundary)
• Fixed threshold of 2.0 points from the boundary
• Example: A Loyalist at satisfaction 4.5, loyalty 6.0 (with midpoint at 4, 5) is 1.0 points away from the Mercenaries boundary (loyalty dimension)

Diagonal Proximity (opposite quadrants, like Defectors near Loyalists):

• Uses Chebyshev distance (also called maximum metric)
• Formula: max(|satisfaction difference|, |loyalty difference|)
• Fixed threshold of 2.0 for all diagonal relationships
• Includes diagonal neighbors as "1 space away" (visually adjacent on the grid)
• Example: A customer at (2,2) to target at (3,3) = max(1,1) = 1 point away ✅

Special Zone Proximity (near Apostles or Terrorists zones):

• Uses Chebyshev distance to zone boundaries
• Maximum distance of 1 position from zone perimeter
• Includes all 8 surrounding positions (including diagonals) as "1 space away"

These calculations help identify customers who are at risk of moving between segments or who have high potential for strategic intervention.

Chebyshev distance (also called maximum metric or chessboard distance) measures distance as the maximum of the absolute differences in each dimension. This means diagonal neighbors are considered "1 space away" just like horizontal or vertical neighbors.

Chebyshev Distance Formula: max(|x2-x1|, |y2-y1|)

Why we use it:

• For diagonal proximity: It naturally includes diagonal neighbors, which makes sense when identifying customers at risk of moving to opposite quadrants
• For special zones: It treats all 8 surrounding positions (up, down, left, right, and all 4 diagonals) as equally close, which aligns with how customers might move on the satisfaction-loyalty grid

Example:

• Point A at (5, 8) to Point B at (6, 9)
• Chebyshev: max(|6-5|, |9-8|) = max(1, 1) = 1 ✅ (includes diagonal)
• Euclidean: √((6-5)² + (9-8)²) = √2 ≈ 1.41
• Manhattan: |6-5| + |9-8| = 1 + 1 = 2

For our proximity analysis, Chebyshev distance provides the most intuitive and business-relevant measurement of customer movement risk.

They answer different questions:

• Trend Chart: Shows how average satisfaction and average loyalty change over time. Each point is an average of the customers who have data on that date.
• Movement Flow Visualization: Shows step-by-step movements between segments from one dated check-in to the next. A single customer can contribute to multiple movements if they change segments multiple times.

It’s a data-driven way to talk about time without guessing. When enough dated history exists, the report estimates the typical gap between consecutive dated records (using the median gap across customers). We label this as Average time between check-ins (cadence).

We only use absolute-day language when there’s enough data to be confident. Otherwise, the report uses more cautious wording like “between consecutive check-ins.”

Getting started is simple:

1. Visit the main tool page
2. Enter your data using one of three options:
   • Upload a CSV file with your customer data
   • Enter data manually using the form
   • Try sample data to explore (Explore mode)
3. Or try our demo mode with a guided tour: Launch Demo →
4. View your customers automatically segmented into the four quadrants
5. Use filters and analysis tools to gain insights

No registration required—just enter your data and start analysing!

You only need two mandatory columns:

• Satisfaction Score: How satisfied they are (1-3, 1-5, or 1-7 scale)
• Loyalty Score: How likely they are to stay (1-5, 1-7, 1-10, or 0-10 scale)

Optional columns you can add:

• Customer Name/ID: Unique identifier for each customer
• Email: For tracking customers over time
• Date: For filtering by time periods
• Country, Language, or any other attributes: For filtering and analysis purposes

Try with sample data first to see the format.

You can source satisfaction and loyalty data from multiple places:

For Loyalty Scores:

• Purchase behaviour: Track repeat purchases, subscription renewals, or frequency of transactions
• Survey questions: Ask "How likely are you to continue buying from us?" (1-5, 1-7, 1-10, or 0-10 scale)
• Recommendation questions: "How likely are you to recommend us?" is commonly used as a loyalty measure (normally on a 0-10 scale)

For Satisfaction Scores:

• Listening strategies: Analyse customer service chats, support emails, complaints, reviews, and social media comments using sentiment analysis
• Surveys: Ask "How satisfied are you with our product/service?" (1-3, 1-5, or 1-7 scale)
• Review scores: Convert review ratings (e.g., 1-5 stars) to satisfaction scores

Accepted scales:

• Satisfaction: 1-3, 1-5, or 1-7
• Loyalty: 1-5, 1-7, 1-10, or 0-10

The tool will automatically normalise different scales if needed. You can mix different scales in the same dataset.

Your CSV should have:

• Header row: Column names in the first row
• Required columns: Name/ID, Satisfaction, Loyalty
• Data types: Numbers for satisfaction/loyalty scores
• Encoding: UTF-8 (most common)

Example format:

Name,Satisfaction,Loyalty,Email,Country
John Smith,4,5,john@example.com,USA
Jane Doe,2,3,jane@example.com,Canada

Yes, absolutely! The tool works excellently for employee experience surveys too. Simply map your employee metrics accordingly—use satisfaction scores for job satisfaction and loyalty scores for retention likelihood.

Teresa Monroe's team often uses segmentor.app for dual CX/EX analysis, helping organisations understand both customer and employee experience in parallel.

Yes! Most tools support CSV export, which is all you need. Simply export your data from Google Forms, Excel, Microsoft Forms, Qualtrics, or any other survey platform as a CSV file, then upload it to segmentor.app.

Ensure your exported CSV includes satisfaction and loyalty columns (or equivalent metrics), and the tool will handle the rest.

Absolutely! You have two options to explore the tool:

1. Explore mode: Click "Try Sample Data" to load sample customer data and explore all features freely
2. Demo mode: Launch the guided demo tour → to see the tool in action with step-by-step guidance

Both options let you experience the full tool with realistic sample data before uploading your own.

No, there's no hard limit on the amount of data you can upload. The tool processes everything locally in your browser, so the practical limit depends on your device's performance.

Most laptops handle 5,000+ entries comfortably, and many users work with up to 10,000 rows without issues. Performance may vary based on your hardware specifications.

In demo mode, there's a 100-entry limit to showcase the tool's capabilities.

No account required! The tool works entirely in your browser with no registration, login, or email needed. Just visit the site and start using it.

Getting started is simple:

1. Upload your data: Click "Upload CSV" and select your customer data file
2. Or try sample data: Click "Load Sample Data" to see how it works
3. View your segments: The tool automatically categorizes your customers
4. Analyze results: Click on any customer point to see details
5. Save your work: Use the Save button to download your project

Your CSV only needs these two mandatory columns:

• Satisfaction Score: 1-10 scale (or 1-5, we'll normalize it automatically)
• Loyalty Score: 1-10 scale (or 1-5, we'll normalize it automatically)

Optional columns:

• Customer ID: If you don't provide this, segmentor.app will assign automatic IDs
• Customer Name, Email, etc.: Any additional details you want to include

Accepted scales: Satisfaction: 1-3, 1-5, or 1-7. Loyalty: 1-5, 1-7, 1-10, or 0-10. We automatically detect and normalise different scales.

Examples:

// Minimal format (anonymous feedback)
Satisfaction,Loyalty
8,9
6,4

// With customer details
Customer ID,Satisfaction,Loyalty,Customer Name
CUST001,8,9,John Smith
CUST002,6,4,Jane Doe

Yes! If your data includes a Date column and you have the same customers (identified by email or ID) appearing at different times, the tool automatically shows a Historical Progress section.

This lets you:

• See how average satisfaction and loyalty trends over time
• Track individual customer movements between segments
• Identify customers who move multiple times (multi-movement journeys)
• Understand which transitions are most common

Tip: Include a Date column in your CSV and use consistent customer identifiers (email or ID) to enable historical tracking.

Absolutely! Click the "Load Sample Data" button to see how the tool works with example customer data. This is perfect for:

• ✅ Understanding how the Apostles Model works
• ✅ Seeing what your results will look like
• ✅ Testing the tool's features
• ✅ Demonstrating to colleagues

Great question! While segmentor.app makes customer segmentation accessible to everyone, we know that turning insights into strategy isn't always straightforward.

We've partnered with Teresa Monroe, Europe's leading Customer Experience (CX) and Employee Experience (EX) consulting agency, to provide expert guidance when you need it. They specialise in:

• ✓ Complete CX program development from the ground up
• ✓ Expert segmentation analysis and strategic recommendations
• ✓ Implementation support and team training
• ✓ Organisational transformation and cultural change

Teresa Monroe has helped hundreds of companies transform their customer experience—from Fortune 500s to innovative scale-ups. They bring decades of experience turning customer data into business transformation.

Yes! You can drag the midpoint (centre point) to reposition where the quadrants divide. This is useful when your data distribution suggests different thresholds would be more meaningful.

You can also resize the Apostles and Terrorists zones using the resize handles in the top-right and bottom-left corners of the chart.

Yes, for points on quadrant boundaries. Click any data point to see its details. If the point sits on a boundary line, you'll see reassignment buttons to move it to an adjacent quadrant.

Manual reassignments are automatically cleared if you move the midpoint and the point is no longer on a boundary.

The chart controls let you:

• Toggle between Classic (Apostles/Terrorists) and Modern (Advocates/Trolls) terminology
• Show or hide Near-Apostles zones
• Control label visibility (all, quadrants only, or none)
• Toggle grid lines and scale numbers
• Show or hide axis legends

Yes. In the data table, click the edit icon to modify satisfaction or loyalty scores. Click the delete icon to remove individual entries, or use "Delete All Rows" to clear everything.

You can also exclude entries from analysis without deleting them—they'll remain in your data but won't appear in calculations.

In the data table, click the details icon (eye or info icon) next to any customer entry to see all their information including name, email, satisfaction and loyalty scores, quadrant assignment, date, and any additional attributes you've uploaded.

You can also click any point on the chart to open an information box showing the customer's details. For overlapping points, you'll see a frequency count.

Yes! The tool offers comprehensive filtering:

• Date filters: Analyse specific time periods with presets or custom ranges
• Attribute filters: Filter by country, language, or any custom attributes in your data
• Score filters: Filter by satisfaction or loyalty values

You can combine multiple filters to narrow down your analysis to specific customer segments.

Applying filters: Use the filter controls in the main customer segments chart to select criteria. You can filter by date ranges, specific attributes (like country or language), or score ranges. Multiple filters work together—only customers matching ALL your selected criteria will be shown.

Connection intelligence: When you set filters in the main chart, the tool automatically connects those filters to all other reports and charts throughout the tool. This means:

• All reports (Data Report, Action Plan) automatically filter to match your main chart filters
• All other charts and visualisations update to reflect the same filtered subset
• Statistics and distributions recalculate based on the filtered data
• Everything stays synchronised—when you change filters in the main chart, all connected views update automatically

Disconnecting filters: You can disconnect individual reports or charts from the main filter by editing their own filter settings. This allows you to compare different filtered views side-by-side—for example, keeping the main chart filtered by one country while viewing a report filtered by a different country.

Tip: Use connection intelligence to quickly analyse specific segments across all your reports, then disconnect individual views when you need to compare different filters.

The average gives you a single number, but it doesn't represent any individual customer. For example, an average of loyalty=3.5 and satisfaction=7.8 tells you the mathematical centre of your data, but no customer actually has those exact scores.

Response concentration shows where your customers actually cluster—identifying the mode (the most frequently occurring combinations) of your satisfaction-loyalty pairs, along with other frequent patterns. It reveals where most of your responses tend to be located on the chart—the real patterns in your data.

Why this matters: By comparing the concentration to the average, you can see how volume is affecting your numbers. If you have many customers clustered in one area but a few outliers pulling the average in a different direction, the concentration will show you the true story of where your customers are, while the average might be misleading.

This helps you understand whether your averages are being skewed by outliers or whether they accurately represent where most of your customers actually sit.

Yes. The tool automatically detects and normalises 1-3, 1-5, and 1-7 satisfaction scales. You can mix different scales in the same dataset—the tool will handle the conversion automatically.

Yes. The tool automatically detects and normalises 1-5, 1-7, 1-10, and 0-10 loyalty scales. Your satisfaction and loyalty scales can be different—the tool handles each independently.

Highly accurate for standard scales. The tool converts scale equivalents linearly, preserving the proportional relationships between values. For example, a score of 4 on a 1-5 scale maps proportionally to 7.5 on a 1-10 scale.

Custom scales are detected proportionally based on their range. You can test the normalisation with sample data to verify the conversion matches your expectations.

When multiple customers share the same satisfaction and loyalty scores, they're displayed as a single point with a frequency indicator. Click the point to see all customers at that position and their details.

If you move the midpoint and a manually reassigned point is no longer on a boundary, the manual reassignment is automatically cleared. The point reverts to its natural classification based on the new midpoint position.

You can reload your saved project file to restore previous settings. The tool doesn't have an in-session undo feature, so it's recommended to save your work regularly using the Save button.

To reset the chart, you can either reload your original data or adjust the midpoint and zone sizes back to their default positions manually. There isn't a one-click reset, but reloading your project file will restore all saved settings.

Yes! You can share your analysis in several ways:

• Export as PDF or Excel: Share complete reports with all insights
• Share project files: Export as .seg file for colleagues to load and continue analysis
• Export charts: Share visual charts as PNG images
• Export CSV: Share the segmented data for further analysis

All exports are created on your device—you choose how and where to share them.

Each circle shows the count of customers moving from the source quadrant to the destination quadrant between two consecutive dated check-ins.

Tip: Click a circle to see the customers behind that specific movement.

This is normal. Different parts of Historical Progress summarize different things:

• Diagram: Focuses on movements between the 4 main quadrants (Hostages, Loyalists, Defectors, Mercenaries) between consecutive check-ins.
• Stats above: May reflect a broader view of movements and can include cases that the diagram doesn’t draw directly (for example, movements involving extra zones depending on your counting preferences).

If you turn on “count-as” merges (e.g., Count Advocates as Loyalists), the diagram counts those movements into the 4-quadrant view without changing the layout.

Top Movements shows the most common single-step transitions (e.g., Hostages → Loyalists).

Customer Journeys (multi-movement) shows full paths per customer across multiple check-ins (e.g., Hostages → Loyalists → Mercenaries), and lets you filter by Minimum movements (2+, 3+, etc.).

The tool accepts common date formats:

• dd/MM/yyyy (e.g., 15/03/2024)
• MM/dd/yyyy (e.g., 03/15/2024)
• yyyy-MM-dd (e.g., 2024-03-15)

The tool automatically detects the format based on your CSV headers or tries standard parsing. Dates don't need to be in chronological order—the tool sorts them automatically for each customer.

Important: Each customer needs to appear with 2+ different dates (using the same email or ID) for Historical Progress to work.

Yes! Click the export button (download icon) next to the Historical Progress section title to download a CSV file containing all customers with 2+ dates.

The export includes:

• All dates for each customer (Date 1, Date 2, etc.)
• Satisfaction and loyalty scores for each date
• Quadrant assignments for each date
• Movement count and journey path summary

The file is saved as segmentor-app_Historical_Progress_data_DD-MM-YYYY-hh-mm.csv and is UTF-8 encoded for compatibility with Excel and other spreadsheet software.

Your data is automatically saved in your browser's temporary storage, so you can refresh the page without losing your work during a session. However, for long-term storage, use the Save button to download a .seg project file.

If you clear your browser cache or use a different browser, you'll need to load your saved .seg file to restore your work.

Yes! You can customize the watermark in your reports. Go to Controls > Watermark > Watermark Controls to adjust logo settings, size, position, and transparency. All customization features are free.

Yes! You can customize colors throughout the tool. Highlight KPIs with different colors, customize bar chart colors, and more. All color customization features are free.

These options change how movements are counted into the 4-quadrant Movement Flow view.

• The diagram layout never changes: Hostages (top-left), Loyalists (top-right), Defectors (bottom-left), Mercenaries (bottom-right).
• When enabled, movements involving extra zones (e.g., Advocates/Near‑Advocates or Trolls) are counted into Loyalists or Defectors for the purposes of the diagram and customer lists.

Teresa Monroe is a respected Paris-based consulting firm specialising in Customer Experience (CX) and Employee Experience (EX) management. We're proud to partner with them to offer strategic guidance for segmentor.app users who need expert support beyond basic analytics.

Their Credentials:

• Track Record: Founded in 2014, Teresa Monroe has built a strong reputation delivering CX and EX projects for leading organisations. They boast 300+ satisfied clients and have delivered impactful work for companies including Leroy Merlin (tailored real-time customer experience measurement tool), Legrand (CX strategy, personas, journeys, KPIs, and tool implementation), and Videotron (Qualtrics platform rollout and integration). Their approach emphasises collaborative partnerships and tangible improvements.
• Industry Recognition & Expertise: Official partners with Qualtrics (multiple team members hold certifications such as CX Expert and Solution Architect) and Zendesk. The team includes senior consultants with deep backgrounds—many with 20+ years individually in CX, insights, and leadership (e.g., former roles at Qualtrics, Legrand, Airbnb, Samsung, and Microsoft)—and several recognised experts (e.g., founding CXPA member, Forrester CX Champ). The firm is a certified B Corporation, reflecting commitment to ethical practices.
• Methodology Excellence: They offer end-to-end support, from maturity assessments and strategy roadmapping to practical implementation using platforms like Qualtrics for feedback capture and analysis, Zendesk for service optimisation, and integrations for actionable insights. Emphasis is placed on data-driven decisions, change management, team capability building, and measurable outcomes in satisfaction, engagement, and cultural transformation.
• European & Global Focus: Headquartered in Paris with a presence across 7 locations worldwide, the team speaks 7 languages and delivers multi-country projects. Their work with major European firms demonstrates practical experience in diverse business environments.

Services They Provide:

• CX and EX strategy development and roadmapping
• Advanced segmentation analysis and insights
• Program design and implementation support
• Team training and capability building
• Ongoing advisory and optimisation

We're open to feedback and always interested in hearing about your needs! Email us with your requests, and we'll consider them for future updates.

For partnerships and enterprise needs, custom setups can be arranged. Teresa Monroe's partnership, for example, includes custom configurations tailored to their consulting workflows.

Yes! You can save your complete project. Use the Save button to download a .seg file that contains:

• ✅ All your customer data
• ✅ Segmentation results
• ✅ Any custom settings
• ✅ Analysis notes

To load it later: Use the Load button and select your .seg file. Everything will be restored exactly as you left it.

The tool handles common issues gracefully. When you upload your CSV:

• Missing scores: Rows with missing satisfaction or loyalty values are flagged for review. You can edit or exclude them directly in the data table.
• Invalid values: Non-numeric values or scores outside your scale range are automatically detected and reported.
• Header names: The tool automatically detects satisfaction and loyalty columns even if they're named slightly differently (e.g., "Satisfaction", "Satisfaction Score", "Sat"). However, if your headers are completely different, you may need to rename them to include "Satisfaction" and "Loyalty" in the column names.
• Bulk errors: If multiple rows have issues, the tool shows a detailed error report. Simply correct your CSV and re-upload.

The tool will display specific error messages indicating which rows have problems and how to fix them, so you can address issues quickly.

You can export in multiple formats:

• PNG: Chart images for presentations
• PDF: Complete reports with charts and analysis
• CSV: Raw customer data with segment assignments
• Excel (XLSX): Action plans with multiple worksheets

Export options are available in the reporting section and chart controls.

The tool generates two main reports:

• Data Report: Statistics, distributions, and quadrant breakdowns
• Action Plan: Strategic recommendations, proximity analysis, conversion opportunities, and risk warnings

Both reports include visual charts and can be customised before export.

The Actions Report contains strategic recommendations and analysis that could influence business decisions. Before generating it, we require you to accept our Report Disclaimer & Limitation of Liability.

Why this matters: The report is generated automatically using rule-based algorithms. While it provides valuable insights, it's important to understand that:

• The report is for general informational purposes only
• It is NOT professional, legal, financial, or regulated advice
• You are responsible for verifying the accuracy and suitability of any recommendations
• The tool processes your data automatically and cannot account for all business contexts

By accepting the disclaimer, you acknowledge that you understand these limitations and agree to use the report appropriately. You can read the full disclaimer before accepting—it's available via the link in the warning box.

Note: The Data Report doesn't require acceptance because it only presents statistical facts about your data, not strategic recommendations.

The Action Plan includes:

• Proximity Analysis: Identifies customers close to quadrant boundaries who could be converted
• Recommendation Score: Calculates your overall recommendation score
• Response Concentration: Shows where most responses cluster
• Strategic Priorities: Highlights high-impact opportunities

The ROI Score is a simple prioritization metric calculated as Impact × Actionability on a 1-9 scale.

• Impact is rated as: High (3), Medium (2), or Low (1)
• Actionability is rated as: Easy (3), Medium (2), or Hard (1)

Higher scores indicate actions that are both high-impact and easier to implement, helping you prioritize where to focus your efforts first.

The Recommendation Converter computes a loyalty score using the formula: (% Promoters - % Detractors) × 100, which gives you a score ranging from -100 to +100.

It categorises your customers into:

• Promoters: High loyalty scores (typically 9-10 on a 0-10 scale, or equivalent on other scales)
• Passives: Moderate loyalty scores (typically 7-8 on a 0-10 scale)
• Detractors: Low loyalty scores (typically 0-6 on a 0-10 scale)

The report also sets conversion targets per segment, helping you understand which customers are most likely to move between categories with targeted interventions.

Proximity Analysis highlights at-risk customers near quadrant boundaries—those who could easily move between segments with small changes in satisfaction or loyalty.

The report suggests specific interventions for each segment. For example, it might recommend targeted actions to convert Mercenaries (high satisfaction, low loyalty) into Advocates by focusing on loyalty-building initiatives.

This analysis helps you prioritise your efforts on customers who are closest to moving into more valuable quadrants, maximising the impact of your interventions.

Common CSV issues:

• Missing headers: Ensure your first row contains column names (Satisfaction, Loyalty, etc.)
• Wrong column names: Column names must match exactly (case-sensitive)
• Invalid scores: Satisfaction and loyalty values must be numbers within your scale range
• Encoding issues: Save your CSV as UTF-8 encoding
• Empty rows: Remove any completely empty rows

The tool will show specific error messages indicating which rows have problems and how to fix them.

The tool works best with modern browsers:

• Chrome 60 or later
• Firefox 55 or later
• Safari 12 or later
• Edge 79 or later

For the best experience, use the latest version of your browser. Older browsers may have limited functionality.

Yes! The tool is fully responsive and works on mobile devices and tablets. All features are available, though some may be optimised for touch interaction on smaller screens.

There isn't a dedicated mobile app yet—the tool is web-based and desktop-optimised. Mobile devices may show a warning, but the basics work in landscape orientation. For the best experience, we recommend using a desktop or laptop computer.

The tool processes everything locally in your browser, so performance depends on your device. For datasets with thousands of entries, you may notice:

• Slightly slower chart rendering
• Brief delays when applying filters
• Longer report generation times

This is normal for local processing. If performance becomes an issue, try filtering your data to a smaller subset for analysis.

Historical Progress only appears when at least one customer has 2+ different dates (tracked using email or ID).

If most rows have no date, or each customer only appears once, there’s no “history” to compare — so the section won’t show.

If your Movement Type filters become too restrictive (for example, you disable both positive and negative movements), there may be no movements left to show.

Instead of removing the chart completely, we keep it visible but blurred so you can still access the menu and adjust filters back to a valid combination.

Demo mode is limited to 100 customer entries to showcase the tool's capabilities. To remove this limitation, exit demo mode and use the full tool with your own data. There's no limit on the number of entries in the standard tool.

If your .seg file won't load:

• Check file format: Ensure it's a valid .seg file exported from Segmentor
• File size: Very large files may take longer to load
• Browser storage: Clear your browser's local storage if you're experiencing issues
• Try a different browser: Some browsers handle file loading differently

If problems persist, try exporting your data as CSV as a backup.

Some features may be temporarily unavailable if:

• You're in demo mode (some advanced features are limited)
• Your data doesn't meet certain requirements (e.g., Near-Advocates requires sufficient data spread)
• The feature requires specific data attributes (e.g., date filtering requires date columns)

Check the tooltips or help text for specific requirements.

If you haven't saved your project, custom settings like midpoint position, zone sizes, and manual reassignments are stored in your browser's temporary storage. These may be cleared if:

• You clear your browser cache
• You use a different browser or device
• Your browser's storage quota is exceeded

Always save your project using the Save button to preserve all settings.

Yes! Once the page has loaded, you can work completely offline. All processing happens in your browser, so no internet connection is required after the initial page load.

The tool requires JavaScript to function—it's essential for local processing in your browser. If JavaScript is disabled, the tool won't work.

Please enable JavaScript in your browser settings for full functionality. All modern browsers have JavaScript enabled by default, so this is rarely an issue.

We were quoted £18,000 by domain speculators for the .com version, but we chose an .app domain for £6 and focussed on improving our service instead.

The .app domain also clearly signals that Segmentor is an application—a tool you use, not just a website you visit. This aligns perfectly with our tool-first approach.