FAQ: audience segmentation for festivals - Nevent

Quick definition

How many filters can I combine in a segment?

No technical limit. Recommendation: simple campaigns 2-4 filters, segmented 5-8, ultra-specific 10+. Each additional filter reduces the audience by roughly 30-50% and increases precision. Optimal balance: 4-6 filters for most cases.

Example: A segment with 6 filters (Temperature: Very Hot, Events: ≥2, City: Madrid, Genre: Electronic, Spend: ≥€300, Email opens: ≥3) = 850 ultra-qualified fans from a 50k base (1.7%).

Frequently Asked Questions

Quick answers to the most common questions about segmenting attendees at festivals, venues and events.

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General

How many filters can I combine?

Answer: There is no technical limit, but the practical recommendation is:

• Simple campaigns: 2-4 filters
• Segmented campaigns: 5-8 filters
• Ultra-specific campaigns: 10+ filters

More filters = smaller, more specific audience.

Tip

Start with 2-3 filters. If your audience is too large, keep adding more criteria.

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Are segments updated automatically?

Answer: Yes, segments are dynamic by default.

Every time you run a campaign, Nevent recalculates who meets the criteria at that moment.

Example:

• Today: You create a “Hot Temperature” segment → 1,000 fans
• Tomorrow: 50 new fans become “Hot”
• You run the campaign: It sends to 1,050 fans (the current ones)

Exception: You can save “static” (frozen) segments that lock the list at a specific point in time.

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Can I save a “static” (frozen) segment?

Answer: Yes, when saving a segment you can choose:

• Dynamic (recommended): Updates automatically
• Static: Freezes the fan list at that exact moment

When to use static segments:

• Cohort studies (longitudinal tracking of the same group)
• Multi-step campaigns where you need consistency
• Historical analysis (“Fans who attended Festival 2024”)
• Compliance (preserving who gave consent on date X)

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Can I export my segment?

Answer: Yes, you can export the fan list to CSV for:

• External analysis (Excel, Google Sheets)
• Importing to other platforms
• Stakeholder reports
• Backup

The export includes: Name, email, phone and basic fields.

GDPR

Only export fans who gave consent and use the data responsibly in accordance with data protection law.

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How do I know if my segment is too small?

Answer: Quick guide by campaign type:

Size	Assessment	Action
< 50	Very small	⚠️ Consider broadening
50-200	Small	✅ OK for exclusive offers
200-1,000	Medium	✅ Ideal for segmentation
1,000-10,000	Large	✅ Optimal for campaigns
> 10,000	Very large	⚠️ Consider sub-segmenting

Exception: If your total base is small (< 500 fans), a segment of 30-50 may be reasonable.

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Behaviour and Logic

What happens if a fan belongs to multiple segments?

Answer: They will receive multiple emails if they are in multiple active campaigns.

How to avoid this:

1. Use exclusions: “Did not receive email in the last 7 days”
2. Plan your calendar: Space out your campaigns
3. Prioritise segments: Define a hierarchy (VIPs first, then general)
4. Use fatigue filters: Nevent can automatically limit emails per fan per week

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Can I see which fans are in my segment before sending?

Answer: Yes, the Preview function shows you:

• Total estimated number
• A list of 10-50 example fans with full profiles
• Geographic distribution (if applicable)
• Distribution by Nevent Temperature

Use this to validate before running and make sure the segment makes sense.

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Do segments affect deliverability?

Answer: Indirectly, yes.

Well-built segments improve deliverability:

• ✅ Engaged fans open more → better sender reputation
• ✅ Fewer spam complaints → ISPs trust you
• ✅ Relevant messages → fewer unsubscribes
• ✅ High open rate → Gmail/Outlook prioritise you

Poorly built segments worsen deliverability:

• ❌ Sending to inactive fans → low open rate → spam folder
• ❌ Over-contacting → spam complaints
• ❌ Irrelevant messages → unsubscribes
• ❌ Cold audience → low engagement

Conclusion: Effective segmentation is key to good deliverability.

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Can I combine existing segments?

Answer: Not directly, but you can replicate the logic:

Process:

1. View the filters of Segment A
2. View the filters of Segment B
3. Create Segment C that combines both with AND/OR logic

Example:

• Segment A: “Fans from Barcelona”
• Segment B: “VIPs with spend > €500”
• New Segment C: “Fans from Barcelona AND VIPs with spend > €500”

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Criteria and Categories

What exactly is “Nevent Temperature”?

Answer: It is a predictive score (0-100) that Nevent automatically calculates for each fan based on:

• Frequency of event attendance
• Purchase recency
• Total historical spend
• Email engagement (opens, clicks)
• Platform interaction
• Purchase speed (early bird vs last minute)

Scale:

• 🔥 Very Hot (84-100): Ultra-engaged super fans
• 🔥 Hot (67-83): Very active fans
• 🌡️ Warm (51-66): Moderate engagement
• ❄️ Cold (34-50): Low engagement
• ❄️ Very Cold (17-33): Little engagement
• 🧊 Frozen (0-16): Inactive or very new

Practical use:

• 🔥 Very Hot: Target for VIP and exclusives
• 🌡️ Warm: Most general campaigns
• ❄️ Cold: Reactivation and win-back campaigns

Note

You do not need to understand the algorithm. Simply interpret the temperature as “how likely is this fan to buy or engage”.

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Can I create my own custom criteria?

Answer: Yes, through custom fields.

How it works:

1. Create a custom field (e.g. “Client Type”)
2. Assign values to your fans (e.g. “Business”, “Individual”, “Press”)
3. Use the “Custom field” criterion in segmentation
4. Filter by Field = "Client Type" and Value = "Business"

Useful custom field examples:

• Loyalty tier (Bronze, Silver, Gold, Platinum)
• Industry (Tech, Finance, Healthcare)
• Acquisition source (Facebook, Google, Referral)
• Assigned Customer Success Manager

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I cannot find the criterion I am looking for — what should I do?

Possible reasons:

1. It is in another category: E.g. looking for “City” in Spend instead of Fan Attributes
2. Not yet synchronised: The field has not been imported from your ticketing platform
3. You need a custom field: You need to create it manually
4. It does not exist: The functionality is not yet available

Solution:

• Check the full categories reference
• Contact support: support@nevent.ai
• Request new criteria (product roadmap)

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Groups and Testing

Do groups change over time?

Answer: No. A fan will always be in the same group.

Group assignment is based on a hash of the user_id, which is deterministic and permanent.

Example: If Fan X is in Group 5 of 10 today, they will still be in Group 5 in 6 months.

This is crucial for consistency in long-term A/B tests.

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Can I select multiple groups for a campaign?

Answer: Yes. You can send to:

• A single group: Group 1
• A range of groups: Groups 1-5
• Specific groups: Groups 1, 3, 7, 9

Usage example:

Week 1: Send to Group 1 (pilot test)
Week 2: If it works, send to Groups 2-10 (full rollout)

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How do I split 13,456 fans into 10 groups?

Answer: Nevent does this automatically with balanced distribution:

• Groups 1-6: ~1,346 fans each
• Groups 7-10: ~1,345 fans each

The difference is minimal (±1 fan). The algorithm guarantees balance.

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Can I see which fans are in each group?

Answer: Yes, in the segment preview you can:

1. Select a specific group (e.g. Group 3)
2. View the full list of fans in that group
3. Export that group to CSV if needed

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Performance and Technical

How long does it take to calculate a large segment?

Answer: It depends on size and complexity:

Base Size	Complexity	Preview Time	Full Execution Time
< 10K fans	Simple (2-3 filters)	< 1 sec	5-10 sec
10K-100K	Medium (5-7 filters)	1-3 sec	15-30 sec
100K-500K	Complex (10+ filters)	3-8 sec	45-90 sec
> 500K	Very complex	10-15 sec	2-5 min

Preview uses sampling to be ultra fast (P95 < 2 sec). Full execution processes all fans for the send.

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Do segments consume credits or cost anything?

Answer: No. Creating and running segments is unlimited and free.

You only pay for:

• Emails sent
• SMS sent
• Push notifications (according to your plan)

You can create, edit, preview and run segments without limit.

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What is the best segment size for early bird?

The optimal early bird segment size varies by event type and total capacity. The general rule: 5-15% of total capacity sold in the early bird phase.

Recommended sizes by event type

Event Type	Total Audience	Early Bird Segment	Recommended %	Timing
Small venue	500-2,000	150-400	30-20%	7 days before
Medium venue	2,000-10,000	300-1,000	15-10%	14 days before
Medium festival	10,000-50,000	1,000-3,500	10-7%	30 days before
Large festival	50,000-200,000	2,500-8,000	5-4%	60 days before
Macro festival	200,000+	5,000-15,000	2.5-7.5%	90 days before

Recommended criteria for early bird segment

Optimal combination (AND):

• Temperature: Very Hot + Hot (highly engaged fans)
• RFM: Champions + Loyal (strong purchase history)
• Past events: ≥2 purchases in the last 12 months

Example — Festival with 50,000 capacity:

Temperature: ≥Hot
AND RFM Score: Champions, Loyal
AND Past events (specific festival): ≥1
AND Days since last purchase: ≤365

Expected result:

• Segment: 3,500-4,500 fans (7-9% of 50k)
• Conversion: 12-18%
• Early bird tickets sold: 420-810
• Revenue: €189,000 - €364,500 (price €450)

Common mistakes to avoid

❌ Segment too small (<500 fans):

• You do not reach the early bird target
• You miss critical revenue in phase 1

❌ Segment too large (>20% capacity):

• Reduces scarcity (no urgency)
• Leaves fewer tickets for phases 2 and 3
• Risk: not filling the event in later phases

❌ Including cold fans (Cold/Frozen temperature):

• Low conversion (2-4% vs 12-18% for Hot fans)
• You waste early bird access on an audience that will not convert
• Better to save them for phase 2 once more of the lineup is confirmed

Best practice

Two-phase strategy:

1. Phase 1A — Super exclusive (48h): Champions + Very Hot only (1-2% capacity)
2. Phase 1B — General early bird (7-14 days): Loyal + Hot (5-8% capacity)

Benefit: Generates FOMO in phase 1B (“Champions already bought, fewer tickets left”)

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How do I segment attendees who opened an email but did not buy?

This is an email cart abandonment segment (opener non-buyer) with a typical recovery rate of 25-40% if you act within a 48-72 hour window.

Full segment: “Email Opener — Non-Buyer”

Criteria (AND combination):

Email opened: Specific campaign (e.g. "Early Bird Primavera 2026")
AND Tickets purchased: 0
AND Days since email open: ≥2, ≤7

Interpretation: Fans who showed interest (opened) but did not complete a purchase. The 2-7 day window lets you act before they lose interest.

Recommended recovery sequence (3 emails)

Email #1 — Reminder + Answer Questions (Day +2)

Subject: “Questions about [Festival]? We have the answers”

Content:

• We noticed you opened our email about the early bird
• Something holding you back? Here are the 5 most common questions:
  1. Lineup: Will more artists be announced? Yes, we confirm 80% of the remaining acts in February
  2. Refund policy: 100% refund up to 30 days before
  3. Accommodation: Hotel + ticket packages from €280
  4. Groups: Can I buy multiple tickets? Yes, up to 10 in one order
  5. Payment: We accept card, PayPal and instalment payments (3 months interest-free)

CTA: “Buy my early bird ticket”

Expected recovery rate: 8-12%

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Email #2 — Urgency + Scarcity (Day +4)

Subject: ”⏰ Last chance for early bird — X tickets left out of 4,500”

Content:

• Real-time counter of remaining tickets
• “3,200 of 4,500 early birds already sold (71%)”
• “Last year they sold out 48h before the deadline”
• Testimonial: “I bought last year and it was the best decision — María, 2023-2024”

Visual: Progress bar showing % sold

Urgency CTA: “I do not want to miss out”

Expected recovery rate: 10-15%

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Email #3 — Final Incentive (Day +6)

Subject: ”💔 Special 10% discount just for you — Last chance”

Content:

• “We noticed you have not bought yet — we want you to come”
• Unique discount code: COMEBACK10 (valid 48h)
• Discounted price: €405 (vs €450 standard)
• “This code is personal — only you have it”
• Countdown timer: 48h until expiry

Guarantee: “If you change your mind, 100% refund up to 30 days before (no questions asked)”

CTA: “Use my discount COMEBACK10”

Expected recovery rate: 7-13%

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Expected performance — Full sequence

Email	Timing	Sent	Opens	Clicks	Purchases	Revenue
#1 FAQ	Day +2	1,200	45% (540)	25% (135)	10% (120)	€54,000
#2 Urgency	Day +4	1,080	38% (410)	30% (123)	12% (130)	€58,500
#3 Discount	Day +6	950	42% (399)	35% (140)	10% (95)	€38,475 (net of discount)
TOTAL	7 days	-	-	-	345	€150,975

Total recovery rate: 345 out of 1,200 opener non-buyers = 28.75%

Campaign ROI:

• Cost: 3 emails (€0 on Nevent) + discount email #3 (95 fans × €45) = €4,275
• Revenue: €150,975
• ROI: 35.3x (3,530% return)

Automation in Nevent

Configure triggers:

1. Email #1: Automatic +48h after open with no purchase
2. Email #2: Automatic +96h after open with no purchase
3. Email #3: Automatic +144h after open with no purchase
4. Stop trigger: If they purchase at any point, exit the sequence

Exclusions:

• Already purchased a ticket (at any time)
• Unsubscribed
• In another active campaign

Common mistakes

❌ Sending all 3 emails to everyone: Bombardment. Better to stagger based on engagement ❌ Discount from email #1: Trains fans to wait for a discount ❌ Window >7 days: They lose interest. Optimal window: 2-7 days after open ❌ No personalisation: Generic email does not resonate. Mention “we saw you opened…”

Variation for VIPs

If the opener non-buyer is a VIP (RFM Champions/Loyal), do NOT send email #3 with a discount.

Replace with:

• Email #3 VIP: “Exclusive backstage access included — Just for you”
• Incentive: Free upgrade to VIP (not a discount)
• Preserves premium perception

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Can I segment by preferred music genre?

Yes. Nevent automatically assigns music genre preferences based on the fan’s historical behaviour (events attended, email clicks, pages visited).

How automatic assignment works

Nevent analyses 3 data sources:

1. Purchase history (weight: 60%):

   • Fan’s past events
   • Main genre of each event
   • Example: Attended 3 electronic festivals → Preference: Electronic

2. Email clicks (weight: 25%):

   • Artists clicked in newsletters
   • Most visited lineup sections
   • Example: Always clicks the EDM lineup → Preference: EDM

3. Web behaviour (weight: 15%):

   • Time spent on event pages by genre
   • On-site searches
   • Example: Searches “techno festival 2026” → Preference: Techno

Minimum confidence: 2-3 interactions to assign a genre with high confidence

Genres available in Nevent

Main Category	Sub-genres
Electronic	EDM, Techno, House, Trance, Dubstep, Drum & Bass
Rock	Classic rock, Alternative rock, Garage rock
Indie	Indie rock, Indie pop, Indie folk
Hip Hop / Urban	Rap, Trap, Reggaeton, R&B
Pop	Mainstream pop, Electropop, K-pop
Metal	Heavy metal, Death metal, Hardcore
Latino	Reggaeton, Salsa, Bachata, Regional Mexican
Experimental	Avant-garde, Noise, Industrial
Other	Jazz, Soul, Funk, Blues, Country

Example segment: EDM festival

Criteria:

Preferred genre: Electronic, EDM, Techno, House
AND Past events (any electronic genre): ≥1
AND Temperature: ≥Warm

Typical result:

• Total base: 80,000 contacts
• Electronic fans: 18,000-22,000 (22-27%)
• Final segment with filters: 15,000 fans

Personalised email:

• Subject: ”🎧 [EDM Festival] — Techno/house lineup confirmed + Early Bird”
• Hero: Only prominent EDM artists (do not show rock/indie)
• Content: Electronic stage schedules, after-parties

Performance vs generic message:

• Open rate: 32% vs 18% generic (+14pp)
• Click rate: 28% vs 12% generic (+16pp)
• Conversion: 6.5% vs 2.8% generic (+3.7pp)
• Lift: 2.32x revenue per fan

Multi-genre segmentation (OR operator)

Use case: Festival with a diverse lineup (Primavera Sound: rock + indie + electronic)

Criteria:

Preferred genre: Rock OR Indie OR Electronic

Result: 45,000 fans (56% of 80k base)

Personalisation by dominant genre:

Fan’s Dominant Genre	Email Hero Image	Featured Lineup	Personalised Subject
Rock	The Strokes (rock headliner)	60% rock, 40% other	”🎸 Primavera 2026: The Strokes + rock lineup”
Indie	Arctic Monkeys (indie headliner)	60% indie, 40% other	”🎵 Primavera 2026: Arctic Monkeys + indie”
Electronic	Daft Punk (EDM headliner)	60% electronic, 40% other	”🎧 Primavera 2026: Daft Punk + EDM”

Technology: Dynamic content blocks in email (1 template, 3 versions)

Continuous improvement of assignment

Nevent learns with every interaction:

1. Fan with no genre assigned (new):

   • Send generic email with full lineup
   • Track clicks: Which artists did they open?
   • Assign genre based on first 3 clicks

2. Fan with 1 genre assigned (medium confidence):

   • Highlight main genre (70% of content)
   • Show related genres (30%)
   • If they click a secondary genre → Add preference

3. Fan with 2-3 genres assigned (high confidence):

   • Advanced personalisation by dominant genre
   • Cross-sell events in secondary genres

Limitations and considerations

Automatic assignment works best when:

• ✅ Fan has a history of 2+ events
• ✅ Festival/promoter sends regular newsletters (to track clicks)
• ✅ Genres are clearly differentiated (easy: rock vs EDM, difficult: indie rock vs indie pop)

Assignment may fail when:

• ❌ Fan buys tickets as gifts (not their own preferences)
• ❌ Fan is a “musical omnivore” (equally likes everything)
• ❌ Multi-genre event with no data on which stages they visited

Solution: Allow fans to update preferences manually (link in email footer: “Update my music preferences”)

Real case: Sónar Barcelona

Segment: Electronic fans for Sónar 2026

Criteria:

Preferred genre: Electronic, EDM, Techno, House, Trance
AND City: Barcelona, ≤100km (locals + nearby)
AND Past events (any electronic): ≥1

Result:

• Segment: 12,500 fans from a base of 95,000 (13%)
• Open rate: 38% (vs 22% general base)
• Conversion: 8.2% (vs 3.1% general base)
• Tickets sold: 1,025
• Revenue: €184,500

Key insight: Genre + Geo combined increase relevance exponentially (2.6x conversion)

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How does segmentation affect deliverability?

Segmentation SIGNIFICANTLY IMPROVES deliverability because it increases engagement (opens, clicks) — the most important signal for ISPs (Gmail, Outlook) when evaluating sender reputation.

Impact on Sender Reputation

Metric	Mass Email	Basic Segmentation	Advanced Segmentation
Open rate	12-18%	20-28%	35-45%
Click rate	2-4%	5-9%	12-20%
Spam reports	0.3-0.8%	0.1-0.3%	<0.1%
Unsubscribes	0.5-1.2%	0.2-0.5%	0.1-0.3%
Bounce rate	2-5%	2-5%	1-3%
Domain reputation	6-7/10	7-8/10	8-9/10
Inbox placement	70-80%	82-90%	92-97%

Why segmentation improves deliverability

1. Increases engagement rate (positive signal for ISPs)

When you send relevant emails to a specific audience:

• More fans open (high open rate)
• More fans click (high click rate)
• ISPs interpret: “This sender delivers valuable content”
• Result: Inbox placement increases

Mathematical example:

• Mass email: 80k sends × 15% open = 12,000 opens
• Segmentation in 5 groups: 80k sends × 28% open = 22,400 opens
• +10,400 positive signals for ISPs (+87%)

2. Reduces spam reports (negative signal)

Irrelevant email → Fan marks as spam

• Mass email: “I am not interested in electronic” → SPAM (0.5%)
• Segmentation: Only send electronic content to electronic fans → SPAM (0.05%)

Impact: Reducing spam rate from 0.5% to 0.05% = 90% fewer negative signals

3. Reduces unsubscribes (negative signal)

A fan who only receives relevant emails does not unsubscribe:

• Mass email: 1% unsubscribe rate
• Advanced segmentation: 0.2% unsubscribe rate

Secondary benefit: You keep your database longer (less churn)

Case study: Cruïlla Festival 2024

Initial situation (January 2024):

• Strategy: Mass email to 150k fans
• Domain score: 6.8/10 (Gmail Postmaster Tools)
• Inbox placement: 76% (24% to spam/promotions)
• Spam report rate: 0.6%

Change implemented (February 2024):

• New strategy: Segmentation into 8 groups (RFM + Geo + Genre)
• Frequency: Reduced from 2 emails/week to 1 email/week (but more relevant)

Results after 3 months (May 2024):

• Domain score: 8.4/10 (+1.6 points)
• Inbox placement: 94% (+18pp)
• Spam report rate: 0.18% (70% reduction)
• Average open rate: 18% → 32% (+14pp)

Revenue impact:

• May 2024 early bird campaign: +52% revenue vs May 2023 (same audience)
• Attributable to: Higher inbox placement (more fans see the email) + higher open rate

ISP factors improved by segmentation

Gmail (Google Workspace):

• Engagement rate (opens/clicks) is factor #1
• Spam reports are factor #2
• Segmentation improves both → Better inbox placement

Outlook/Hotmail (Microsoft):

• Domain reputation (calculated from opens, clicks, spam)
• Segmentation increases reputation → Less to Junk folder

Apple Mail (iCloud, me.com):

• User engagement + machine learning
• If fans open consistently → Inbox
• If they never open → Promotions tab

Best practices to maximise deliverability with segmentation

1. Segment by historical engagement as well

Do not only segment by demographic/RFM criteria — also segment by engagement:

Segment A — Super engaged:
Temperature: Very Hot
Email opens last 90 days: ≥5
→ Always send (inbox placement: 98%)

Segment B — Moderately engaged:
Temperature: Hot, Warm
Email opens last 90 days: 2-4
→ Send main campaigns

Segment C — Low engagement:
Temperature: Cold, Very Cold
Email opens last 90 days: 0-1
→ Only send critical campaigns (early bird, sold-out warning)
→ Consider sunset (clean up) if 6 months without opening

2. Clean up inactive contacts (sunset policy)

Fans who do NOT open emails for 6-12 months damage deliverability:

• ISPs see: “You send to people who do not want your emails”
• Solution: Win-back campaign (one last attempt) → If they do not open, remove from active base

Example:

• Base of 150k fans, 40k (27%) have not opened in 12 months
• Action: Sunset 40k inactive fans
• Result: Domain reputation rises from 6.5 → 7.8 in 2 months

3. Differentiated frequency by segment

Not all segments tolerate the same frequency:

Segment	Maximum Frequency	Reasoning
Champions (Very Hot)	2-3 emails/week	High engagement, they want information
Loyal (Hot/Warm)	1 email/week	Moderate engagement
Promising (Warm)	2 emails/month	Building trust
At Risk (Cold)	1 email/month + win-back	Avoid fatigue
Cold/Inactive	Critical campaigns only	Minimise spam reports

Tools for monitoring deliverability

Google Postmaster Tools (free):

• Domain reputation (0-10)
• Spam rate
• Feedback loop (spam complaints)
• URL: https://postmaster.google.com

Microsoft SNDS (free):

• IP reputation for Outlook/Hotmail
• Colour code: Green (good), Yellow (warning), Red (bad)
• URL: https://sendersupport.olc.protection.outlook.com/snds/

Return Path / Validity (paid):

• Full inbox placement (Gmail, Outlook, Yahoo, Apple)
• Competitor benchmarking
• Price: ~€200/month

Myths about segmentation and deliverability

❌ Myth: “Segmenting reduces volume, which damages reputation” ✅ Reality: ISPs do not penalise low volume. They penalise low engagement. Better to send 10k emails at 40% open than 100k at 10% open.

❌ Myth: “If I segment too much, each email varies a lot — ISPs will find that suspicious” ✅ Reality: ISPs do not compare content between emails. They only measure engagement per individual send.

❌ Myth: “Deliverability only depends on SPF/DKIM/DMARC” ✅ Reality: SPF/DKIM/DMARC are minimum requirements (table stakes). Engagement is what actually determines inbox vs spam.

Conclusion

Segmentation = More relevance = More engagement = Better deliverability = More revenue

Virtuous cycle:

1. You segment → Relevant emails
2. Fans open more → High engagement
3. ISPs see engagement → Inbox placement rises
4. More emails reach the inbox → More fans see your email
5. More conversion → More revenue
6. Reinvest in better segmentation → Repeat cycle

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How do I identify VIPs at risk of churning?

VIPs at risk of churning are fans with high historical value (heavy spend, frequent purchases) but low recent activity (no purchase in the last 6-12 months). Winning them back is critical because their average LTV is €800-2,500.

”VIP At Risk” segment

Criteria (4 AND filters):

Total historical spend: ≥€500
AND Number of events attended: ≥3
AND Days since last purchase: ≥180, ≤365
AND Email opens in the last 30 days: ≤2

In plain English: A fan who has spent heavily (≥€500) and attended repeatedly (≥3 events) but is now inactive (last purchase 6-12 months ago, barely opens emails).

Typical VIP At Risk profile

Demographics:

• Age: 28-42 years
• Historical spend: €800-2,500
• Events attended: 3-6 (spanning 2-4 years)
• Last purchase: 6-12 months ago
• Open rate last 90 days: 0-15% (vs 45-65% when active)

Additional red flags:

• Has not visited the website in the last 90 days
• Has not interacted on social media (if they follow the promoter)
• Changed email (bounces) or city (moved)

Expected segment size

Depends on total VIP base size:

Total VIP Base	VIP At Risk (5-10%)	LTV at Risk	Recoverable Revenue Potential (20% win-back)
5,000	250-500	€200k-1.25M	€40k-250k
10,000	500-1,000	€400k-2.5M	€80k-500k
20,000	1,000-2,000	€800k-5M	€160k-1M

Insight: Recovering 20% of VIPs At Risk can generate six figures of revenue at large festivals.

Why they become “At Risk”

Main reasons (based on post-churn surveys):

1. Event fatigue (28%):

   • “I have been 4 years in a row, I need a break”
   • Solution: Offer other events from the portfolio (cross-sell)

2. Change in circumstances (24%):

   • New partner, children, relocation, job change
   • Solution: Emails with a “come back with friends/partner” angle

3. Competition (18%):

   • Discovered a similar/better festival
   • Solution: Emphasise unique differentiators

4. Price (15%):

   • “It has got too expensive”
   • Solution: VIP discount (15-20%)

5. Lineup not convincing (10%):

   • “They no longer book artists I like”
   • Solution: Survey for desired artists, personalise lineup highlights

6. Other (5%):

   • Previous negative experience, etc.

Recommended recovery campaign

3-email sequence over 14 days (see full example in Use Cases #2: VIP Reactivation)

Email #1 — Nostalgia (Day 0):

• Subject: “We miss you, [Name] 💔”
• Content: Recap of past events, photos, artists they saw
• Soft CTA: “See upcoming events”
• No hard sell (emotional reconnection only)

Email #2 — Incentive (Day +5):

• Subject: “20% special discount — Only for former VIPs”
• Content: Unique code VIPBACK20, expires in 7 days
• Testimonial: “I came back after 2 years and it was better than ever”
• CTA: “Use my VIP discount”

Email #3 — Last chance (Day +10):

• Subject: ”⏰ Your VIP discount expires tomorrow”
• Content: Urgency + featured lineup + countdown
• CTA: “Claim my discount now”

Expected win-back rate: 15-25% of the At Risk segment

Example with numbers:

• VIP At Risk: 680 fans
• Win-back rate: 20% (136 fans)
• Average ticket value: €180
• Revenue recovered: €24,480
• Campaign cost: €500 (time + discounts)
• ROI: 48.9x

Impact of NOT acting

What happens if you ignore VIPs At Risk:

Metric	No Action (12 months)	With Win-back Campaign
VIP At Risk churn rate	60-70% (become Lost)	30-40% (half recovered)
LTV lost	680 × 70% × €850 = €404k	680 × 40% × €850 = €231k
Revenue recovered	€0	136 × €180 = €24.5k
Difference	—	-€173k LTV saved + €24.5k revenue

Conclusion: Not acting costs hundreds of thousands in LTV + immediate revenue.

Prevention: stopping Champions becoming At Risk

The best strategy is to prevent churn BEFORE fans reach At Risk:

Early warning signals (intervene when you spot):

1. A Champion who did not buy early bird (first time in 3 years)
2. Open rate dropped from 60% to 30% in the last 3 months
3. Has not visited the website in 60 days (vs monthly visits before)

Preventive action:

• Personalised email: “We noticed you did not buy early bird this year — everything OK?”
• Offer a call with an account manager (large festivals)
• Survey: “What can we improve?”
• Gentle incentive: 10% discount (not 20% — save that for At Risk)

Prevention is 3x more effective than recovery:

• Prevention: Retain 70-80% of Champions with early risk signals
• At Risk recovery: Only 15-25% win-back rate

Tools in Nevent

Automatic alert: Nevent can send you a notification when a fan enters “VIP At Risk”:

• Configuration: “Alert when a VIP (≥€500 historical) does not purchase in 180 days”
• Method: Email to account manager or dashboard alert
• Frequency: Weekly

VIP Health dashboard:

• Visual segmentation: Champions (green), Loyal (blue), At Risk (yellow), Lost (red)
• Trending: How many Champions → At Risk this week?
• Forecast: “Projection: 120 VIPs at risk of churning in the next 90 days”

Real case: Mad Cool Festival

Situation (January 2024):

• VIPs At Risk identified: 680 fans
• LTV at risk: 680 × €850 = €578k
• Historical without action: 65% churn (442 fans lost)

Action (win-back campaign, February 2024):

• 3-email sequence (Nostalgia → Incentive → Urgency)
• Discount: 20% (VIPBACK20)
• Timing: 14 days

Result (March 2024):

• Win-back: 22% (150 fans out of 680)
• Immediate revenue: 150 × €180 = €27,000
• LTV saved: 150 × €850 = €127,500
• Churn reduced: 65% → 45% (-20pp)

Key insight: For every €1 invested in VIP win-back, you recover €54 in LTV.

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