# Segmentation best practices for email - festivals 2026

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:::tip[Quick definition]
**What are the best practices for segmentation?**

9 rules: (1) Start with RFM, (2) Minimum size 500 fans, (3) Test one variable at a time, (4) Avoid over-segmentation (no more than 15 segments), (5) Update criteria each campaign, (6) Always measure, (7) Combine max 3-5 criteria, (8) Respect frequency, (9) Clean up inactive contacts.

**Example:** A promoter with 50k fans who created 25 segments generated audience fatigue (12% open rate). They consolidated to 8 segments and recovered 28% open (+16pp).
:::

# Segmentation Best Practices

Apply these 9 rules to maximise the impact of your festival and event attendee segments, increase ticket sale conversion and improve the ROI of your email marketing campaigns.

---

## 1. Preview Before Sending

Always use the **Preview** function to:

✅ See the estimated size of your audience
✅ Review 10-20 example profiles
✅ Detect if the segment is too small or too large
✅ Verify that the filters are correct

### Target Sizes

### What is the ideal segment size for each type of festival campaign?

| Campaign Type | Ideal Size |
|---------------|------------|
| Mass email | 1,000+ fans |
| Segmented promotion | 300-1,000 fans |
| Exclusive VIP offer | 50-300 fans |
| A/B test (per variant) | 100+ fans |

**If your segment has:**
- < 50 fans: Too specific → consider broadening
- \> 10,000 fans: Too broad → consider sub-segmenting

---

## 2. Start Simple, Iterate Towards Complexity

### First Campaign

❌ **Do not do this:**
```
(City equals "Madrid" OR "Barcelona")
AND (Age 25-40)
AND (Events >= 3)
AND (Spend > €200)
AND (Temperature "Hot")
AND (Did not open email in 30 days)
```

✅ **Do this:**
```
City equals "Madrid"
```

### Recommended Progression

1. **Weeks 1-2**: Simple segments (1-2 criteria)
2. **Weeks 3-4**: Add behaviour (spend, attendance)
3. **Month 2**: Combine demographics + behaviour
4. **Month 3+**: Advanced multi-group segments

**Measure results** at each iteration and learn which criteria make the most difference.

---

## 3. Document Your Successful Segments

### Naming Convention

✅ **Good names:**
- `VIP_Reactivation_Madrid_Q1_2026`
- `EarlyBird_Festival_Barcelona_Summer`
- `New_Fans_Last_30days`
- `Test_SubjectLine_Group_A`

❌ **Bad names:**
- `Segment 1`
- `Test xyz`
- `Campaign_final_final_v2`
- `asdf`

### What to Document

When a segment produces good results:

1. **Save it** with a descriptive name
2. **Note down**:
   - Which campaign you ran
   - Results (open rate, click, conversion)
   - Date of execution
   - Key learnings
3. **Reuse it** in similar campaigns
4. **Share it** with your team

**Documentation example:**
```
Name: VIP_Reactivation_Madrid_Q1_2026
Date: 15 Jan 2026
Audience: 456 fans
Campaign: 3-step email sequence with 20% discount
Results:
  - Open: 48%
  - Click: 18%
  - Conversion: 22%
  - ROI: 12x
Learnings: 20% discount is the sweet spot, 30% cannibalises margins
```

---

## 4. Respect Audience Fatigue

Do not over-contact the same segments.

### ❌ Bad Example

```
Monday: Email to "Fans in Madrid"
Tuesday: Email to "Fans aged 25-35 in Madrid"
Wednesday: Email to "Fans who bought in Madrid"

→ Same fan receives 3 emails in 3 days
```

### ✅ Done Well

```
Monday: Email to "Fans in Madrid who did NOT receive an email in the last 7 days"
Thursday: Email to a completely different audience (Barcelona)
Next Monday: You can contact Madrid again
```

### General Rules

| Frequency | Audience |
|-----------|----------|
| **Maximum 2-3 emails/week** | To the same segment |
| **Minimum 3-5 days** | Between emails to the same fan |
| **1 email/day** | For Very Hot, highly engaged VIPs only |

**Exception**: Automated sequences for welcome, abandoned carts, etc. (transactional flows).

The optimal frequency depends on segment temperature. For specific questions, see our [FAQ section on frequency and deliverability](./faq#frequency).

---

## 5. Use Groups for Small Tests

Before sending to 50,000 fans, **test with a small group**.

### Recommended Workflow

1. **Split** your segment into 10 groups
2. **Send** only to Group 1 (10% of your base)
3. **Wait** 24-48h and measure results
4. **If it works well** → send to Groups 2-10
5. **If it does not work** → adjust and test again

**Benefits:**
- ✅ You reduce the risk of burning your entire audience
- ✅ You can adjust the message based on early data
- ✅ You catch errors (broken links, typos) with minimal impact
**Tip:** A test with 10% of your base (Group 1) gives you **enough data** for informed decisions without risking 100%.

---

## 6. Combine Behaviour + Demographics

The best segments combine **WHO** the fan is with **WHAT** they have done.

### Weak (Demographics Only)

```
Age 25-35 in Barcelona
```
**Problem**: Too broad, poor predictor of engagement.

### Better (Behaviour Only)

```
Attended 3+ festivals
```
**Better**, but ignores geographic and demographic context.

### Optimal (Combined)

```
Age 25-35 in Barcelona
AND
Attended 3+ festivals
AND
Temperature "Hot"
```
**High conversion probability**: Profile + behaviour + engagement.

---

## 7. Monitor Your Segment Sizes

### Assessment Guide

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

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

### What to Do If Your Segment Is Too Small

1. **Remove** the most restrictive criterion
2. **Change** operators (e.g. "greater than €500" → "greater than €200")
3. **Broaden the geography** (e.g. "City Madrid" → "Province of Madrid")
4. **Use OR** instead of AND (where it makes sense)

### What to Do If Your Segment Is Too Large

1. **Add** a behaviour criterion (engagement, spend)
2. **Refine** demographics (age, more specific location)
3. **Split** into sub-segments by Nevent Temperature
4. **Use groups** for progressive sends

---

## 8. Update Segments Regularly

Behaviour-based segments are **dynamic**.

**Example:**
- Today: Fan is at "Cold Temperature"
- They buy a ticket tomorrow
- Next week: They move up to "Hot"

### Update Frequency

| Segment Type | Frequency |
|--------------|-----------|
| **Behaviour** (temperature, purchases, engagement) | Before each campaign |
| **Demographic** (age, location) | Quarterly |
| **Historical** ("Attended Festival 2024") | Does not change (static) |
**Note:** Nevent automatically updates Nevent Temperature **weekly**. You do not need to do anything.

---

## 9. Use Exclusions When Necessary

Sometimes it is easier to define who you **do not** want to contact.

### Example: Promotion for New Fans

**Approach 1 (Include):**
```
Number of events attended: Equals 1
AND
Purchase date: In the last 90 days
```

**Approach 2 (Exclude):**
```
All fans in Madrid who accept emails
EXCEPT
  Number of events attended: Greater than 5
  (they are already loyal fans, this offer is not for them)
```

**When to use exclusions:**
- Offers for new fans (exclude VIPs)
- Reactivation (exclude fans who were recently active)
- Testing (exclude fans who already received another variant)

---

## Pre-Send Checklist

Before running your campaign, verify:

- [ ] Did I review the fan preview?
- [ ] Is the audience size reasonable?
- [ ] Is the segment name descriptive?
- [ ] Do the criteria make sense for my objective?
- [ ] Did I document what I am going to measure?
- [ ] Did I configure groups if this is an A/B test?
- [ ] Did I verify I am not over-contacting this audience?

---

## KPIs to Measure Success

### Email Performance

### What email marketing metrics should I aim for with festival segmentation?

| Metric | Baseline | Target with Segmentation | Excellent |
|--------|----------|--------------------------|-----------|
| **Open Rate** | 18-22% | 30-40% | 45%+ |
| **Click Rate** | 2-4% | 8-12% | 15%+ |
| **Conversion** | 1-3% | 5-10% | 12%+ |
| **Unsubscribe** | 0.5-1% | 0.1-0.3% | &lt;0.1% |

### Engagement

| Metric | What It Measures | Target |
|--------|------------------|--------|
| **Time to Open** | How quickly they open | < 24h (engaged fans) |
| **Click-to-Open Rate** | % who click after opening | 25-40% |
| **Bounce Rate** | Invalid emails | &lt; 2% |

### Business Impact

| Metric | Target |
|--------|--------|
| **ROI** | 8-15x |
| **Revenue per Email** | €5-15 |
| **Customer Lifetime Value** | +30% vs non-segmented |

---

## Next Steps

Apply these practices and consult:

1. **[FAQ](./faq)** — Answers to common questions
2. **[Use Cases](./use-cases)** — Practical application
3. **[Back to Introduction](./index)** — Full review

---

**Ready to segment like a pro?** 🚀

[Resolve doubts about Nevent Temperature, groups, deliverability and more →](./faq)