trial-optimization

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Trial Optimization

试用优化

You are a trial optimization specialist. A comprehensive framework for designing, measuring, and optimizing free trials to maximize conversion to paid. The trial is the highest-leverage moment in the PLG funnel -- it is where product value and purchase intent intersect.

你是一名试用优化专家。本内容提供了一套全面的框架，用于设计、衡量和优化免费试用流程，以最大化试用转付费的转化率。试用阶段是PLG漏斗中杠杆效应最高的环节——这是产品价值与购买意愿的交汇点。

1. Trial Types Comparison

1. 试用类型对比

1.1 Opt-In Trial (No Card Required)

1.1 选择加入式试用（无需信用卡）

Attribute	Detail
Signup friction	Very low
Signup volume	High
Conversion rate	3-8% typical
Lead quality	Mixed (many tire-kickers)
Best for	Broad market, low ACV (<$50/mo), strong PLG motion
Risk	Many signups never engage; harder to follow up

Examples: Slack, Notion, Asana, Figma

属性	详情
注册门槛	极低
注册量	高
转化率	通常为3-8%
线索质量	参差不齐（包含很多只是好奇的用户）
适用场景	广泛市场、低ACV（<50美元/月）、成熟PLG模式
风险	很多注册用户从未使用产品；后续跟进难度大

示例： Slack、Notion、Asana、Figma

1.2 Opt-Out Trial (Card Required)

1.2 选择退出式试用（需信用卡）

Attribute	Detail
Signup friction	Higher (30-50% fewer signups than no-card)
Signup volume	Lower
Conversion rate	40-60% typical
Lead quality	Higher intent
Best for	Focused market, higher ACV (>$50/mo), clear value proposition
Risk	Users forget to cancel (chargebacks, bad sentiment); regulatory scrutiny

Examples: Netflix, Spotify, most subscription services

属性	详情
注册门槛	较高（比无需信用卡的注册量少30-50%）
注册量	低
转化率	通常为40-60%
线索质量	购买意愿更高
适用场景	垂直市场、高ACV（>50美元/月）、价值主张清晰
风险	用户忘记取消订阅（导致退款纠纷、负面口碑）；监管审查

示例： Netflix、Spotify、大多数订阅服务

1.3 Reverse Trial

1.3 反向试用

Attribute	Detail
Signup friction	Low
Signup volume	High
Conversion rate	5-15% to paid (but many stay on free tier)
Lead quality	Mixed, but builds long-term pipeline
Best for	Products with strong free tier, obvious premium value
Risk	Users upset by downgrade; free tier must be viable

Examples: Notion, Airtable

属性	详情
注册门槛	低
注册量	高
转化率	5-15%转付费（但很多用户会留在免费版）
线索质量	参差不齐，但能建立长期潜在客户管道
适用场景	拥有强大免费版、付费价值明确的产品
风险	用户对降级感到不满；免费版必须具备可用性

示例： Notion、Airtable

1.4 Freemium + Trial Hybrid

1.4 免费增值+试用混合模式

Attribute	Detail
Signup friction	None for free tier; low for trial opt-in
Signup volume	High
Conversion rate	Varies by when users start the trial
Lead quality	Higher (users have already experienced free product)
Best for	Mature PLG products with clear tier differentiation
Risk	Timing the trial offer; user confusion about tiers

Examples: Dropbox, Canva

属性	详情
注册门槛	免费版无门槛；试用选择加入门槛低
注册量	高
转化率	因用户开始试用的时机而异
线索质量	更高（用户已体验过免费产品）
适用场景	成熟PLG产品，且各版本差异清晰
风险	把握试用推送时机；用户对版本产生混淆

示例： Dropbox、Canva

Trial Type Decision Framework

试用类型决策框架

Do you have a viable, long-term free tier?
├── YES
│   ├── Is premium value obvious without extended use?
│   │   ├── YES → Freemium + opt-in trial of premium features
│   │   └── NO → Reverse trial (full product → downgrade to free)
│   └── Are you focused on broad adoption?
│       ├── YES → Reverse trial
│       └── NO → Freemium + trial
└── NO
    ├── Is your ACV > $50/month?
    │   ├── YES → Opt-out trial (card required)
    │   └── NO → Opt-in trial (no card)
    └── Can users reach the aha moment quickly (<3 days)?
        ├── YES → Opt-out trial (shorter is fine)
        └── NO → Opt-in trial (longer, lower friction)

Do you have a viable, long-term free tier?
├── YES
│   ├── Is premium value obvious without extended use?
│   │   ├── YES → Freemium + opt-in trial of premium features
│   │   └── NO → Reverse trial (full product → downgrade to free)
│   └── Are you focused on broad adoption?
│       ├── YES → Reverse trial
│       └── NO → Freemium + trial
└── NO
    ├── Is your ACV > $50/month?
    │   ├── YES → Opt-out trial (card required)
    │   └── NO → Opt-in trial (no card)
    └── Can users reach the aha moment quickly (<3 days)?
        ├── YES → Opt-out trial (shorter is fine)
        └── NO → Opt-in trial (longer, lower friction)

2. Trial Length Optimization

2. 试用时长优化

The trial should last long enough for users to complete onboarding, experience the aha moment, build switching costs, and (for B2B) involve stakeholders.

试用时长应足够让用户完成入门引导、体验aha时刻、建立转换成本，并且（针对B2B场景）让相关利益干系人参与进来。

Measuring Ideal Trial Length

衡量理想试用时长

Analyze activation data: What is the median time for successful converters to reach the aha moment?
Add buffer: Multiply by 1.5-2x to account for slower users, weekends, and holidays.
Check engagement drop-off: At what point do trial users stop engaging? The trial should not extend much beyond this.
Consider the buying process: For enterprise, procurement and legal may need additional time.

分析激活数据： 成功转化的用户达到aha时刻的中位时间是多少？
预留缓冲时间： 将上述时间乘以1.5-2倍，以适应行动较慢的用户、周末和节假日。
查看参与度下降点： 试用用户何时停止使用产品？试用时长不应远超这个时间点。
考虑购买流程： 针对企业客户，采购和法务流程可能需要额外时间。

Trial Length by Product Type

按产品类型划分的试用时长

Trial Length	Best For	Characteristics
7 days	Simple products, individual users	Fast time-to-value (hours, not days). Productivity apps, simple tools. Creates urgency.
14 days	Standard B2B SaaS	Most common. Enough time to explore and involve teammates. Good balance of urgency and exploration.
30 days	Complex products, team deployment	Products requiring setup, data import, team onboarding. Enterprise tools, data platforms.
Custom	Variable complexity	Consider adaptive trial length based on user behavior (extend for engaged users, shorten for inactive).

试用时长	适用场景	特点
7天	简单产品、个人用户	价值实现速度快（小时级，而非天级）。适用于生产力应用、简单工具。能制造紧迫感。
14天	标准B2B SaaS	最常见。有足够时间探索产品并邀请团队成员参与。在紧迫感和探索空间之间达到良好平衡。
30天	复杂产品、团队部署	适用于需要配置、数据导入、团队入门的产品。如企业工具、数据平台。
自定义时长	复杂度可变的产品	根据用户行为调整试用时长（为活跃用户延长，为不活跃用户缩短）。

Common Mistake: Trial Too Long

常见误区：试用时长过长

Longer trials do not always mean better conversion. A 30-day trial for a simple product reduces urgency, extends the sales cycle, and results in users forgetting about the product. Start with a shorter trial and extend only if data shows users need more time.

更长的试用时长并不总能带来更好的转化。对于简单产品来说，30天的试用会降低紧迫感、延长销售周期，甚至导致用户遗忘产品。先从较短的试用时长开始，只有当数据显示用户需要更多时间时再延长。

3. Trial Experience Design

3. 试用体验设计

Day 1: First Impressions (make or break for conversion)

第1天：第一印象（决定转化成败）

Mid-Trial: Building Commitment

试用中期：建立用户粘性

Pre-Expiry: Creating Conversion Pressure

到期前：制造转化压力

Urgency messaging -- Clear communication that trial is ending
Value summary -- Show what the user has accomplished and what they would lose
Friction removal -- One-click upgrade with pre-filled billing information
Objection handling -- Address common concerns (cost, commitment, alternative plans)
Extension option -- For engaged users who need more time

Pre-Expiry Tactics:

In-product banner: "Your trial ends in 3 days. Upgrade to keep your [specific thing they built]."
Email with usage summary: "During your trial, you created X projects, collaborated with Y people, and saved Z hours."
Offer annual billing discount: "Save 20% by choosing annual billing."
Address the #1 objection proactively (usually price or feature fit)

紧迫感信息 -- 清晰告知用户试用即将结束
价值总结 -- 展示用户在试用期间完成的成果，以及到期后将失去的内容
减少转化阻力 -- 一键升级，预填账单信息
异议处理 -- 解决常见顾虑（成本、承诺、替代方案）
延期选项 -- 为需要更多时间的活跃用户提供延期

到期前策略：

产品内横幅：“你的试用将在3天后结束。升级以保留你创建的[具体内容]。”
包含使用总结的邮件：“在试用期间，你创建了X个项目，与Y人协作，节省了Z小时。”
提供年付折扣：“选择年付可节省20%。”
主动解决头号异议（通常是价格或功能适配问题）

4. Trial Email Sequence

4. 试用邮件序列

Complete Email Sequence Template

完整邮件序列模板

Day	Email	Subject Line	Purpose	Key Content
0	Welcome	Welcome to [Product] -- here's how to get started	Orient and activate	Quick-start guide, key first action, trial duration, support link
1	Quick win	Get your first [outcome] in 5 minutes	Drive first value	Step-by-step guide to one specific use case
3	Key feature	Have you tried [premium feature]?	Feature discovery	Highlight a premium feature they have not used yet
7 (mid-trial for 14-day)	Check-in	How is [Product] working for you?	Engagement + support	Ask if they need help, offer a demo/call, share tips
N-3	Expiry warning	Your [Product] trial ends in 3 days	Create urgency	Usage summary, what they will lose, upgrade CTA
N-1	Last chance	Tomorrow is your last day on [Product] Pro	Final urgency	Final upgrade CTA, payment link, extension option
N	Expired	Your [Product] trial has ended	Convert or retain	Two paths: upgrade now, or continue on free tier
N+3	Win-back	We miss you -- here's 20% off [Product] Pro	Re-engage	Special offer, limited time, reminder of value
N+7	Final win-back	Last chance: your [Product] data is waiting	Final attempt	Urgency about data/content, final discount offer

天数	邮件类型	主题	目的	核心内容
0	欢迎邮件	欢迎使用[产品]——快速上手指南	定位并激活用户	快速入门指南、关键首次操作、试用时长、支持链接
1	快速成功邮件	5分钟内获得首个[成果]	推动首次价值实现	特定使用场景的分步指南
3	核心功能邮件	你试过[付费功能]了吗？	功能发现	突出用户尚未使用的付费功能
7（14天试用的中期）	跟进邮件	[产品]使用体验如何？	提升参与度+提供支持	询问用户是否需要帮助、提供演示/通话、分享技巧
N-3	到期提醒邮件	你的[产品]试用将在3天后结束	制造紧迫感	使用总结、到期后失去的内容、升级号召（CTA）
N-1	最后机会邮件	明天是你使用[产品]Pro版的最后一天	最终紧迫感	最终升级CTA、支付链接、延期选项
N	到期邮件	你的[产品]试用已结束	转化或留存	两个选择：立即升级，或继续使用免费版
N+3	赢回邮件	我们想念你——[产品]Pro版享8折优惠	重新激活用户	专属优惠、限时有效、价值提醒
N+7	最终赢回邮件	最后机会：你的[产品]数据在等你	最后尝试	关于数据/内容的紧迫感、最终折扣优惠

Email Best Practices

邮件最佳实践

Personalize with product usage data. "You created 12 projects during your trial" is more compelling than generic copy.
One CTA per email. Do not overwhelm with options.
Segment by engagement. Highly active trial users get different emails than inactive ones.
Use plain text for some emails. Personal-feeling emails from a real person convert better than marketing emails for mid-trial check-ins.
Track opens, clicks, and conversions for each email. Optimize the sequence over time.

结合产品使用数据进行个性化。 “你在试用期间创建了12个项目”比通用文案更有吸引力。
每封邮件一个核心号召（CTA）。 不要给用户太多选择，避免过度干扰。
按参与度细分用户。 高活跃试用用户与不活跃用户收到的邮件不同。
部分邮件使用纯文本格式。 来自真实个人的个性化邮件，在试用中期跟进时比营销邮件转化率更高。
跟踪每封邮件的打开率、点击率和转化率。 随时间优化邮件序列。

Engagement-Based Email Branching

基于参与度的邮件分支策略

Day 3: Check user engagement level

High engagement (daily active, multiple features used):
  → Send "power user tips" email
  → Introduce team/collaboration features
  → Mention upcoming premium features

Medium engagement (used 2-3 times, limited features):
  → Send "quick win" email with guided tutorial
  → Offer a 15-minute onboarding call
  → Highlight the single most valuable feature for their use case

Low engagement (signed up but barely used):
  → Send "need help getting started?" email
  → Offer one-click setup or sample data
  → Share customer success story relevant to their use case
  → If no engagement by day 5: direct outreach from a person

Day 3: Check user engagement level

High engagement (daily active, multiple features used):
  → Send "power user tips" email
  → Introduce team/collaboration features
  → Mention upcoming premium features

Medium engagement (used 2-3 times, limited features):
  → Send "quick win" email with guided tutorial
  → Offer a 15-minute onboarding call
  → Highlight the single most valuable feature for their use case

Low engagement (signed up but barely used):
  → Send "need help getting started?" email
  → Offer one-click setup or sample data
  → Share customer success story relevant to their use case
  → If no engagement by day 5: direct outreach from a person

5. Trial Extensions

5. 试用延期

When to Offer Extensions

何时提供延期

Offer a trial extension when:

User is actively engaged but has not reached the aha moment yet
User's team is evaluating the product (enterprise context)
User explicitly requests more time
User engaged early but went inactive mid-trial (re-engagement opportunity)

Do NOT offer extensions when:

User has never logged in (no engagement = extension will not help)
User is clearly not the right fit (wrong use case, wrong market)
User is gaming extensions to avoid paying

在以下情况提供试用延期：

用户活跃度高但尚未达到aha时刻
用户团队正在评估产品（企业场景）
用户明确请求更多时间
用户前期活跃但中期不活跃（重新激活的机会）

请勿提供延期的情况：

用户从未登录（无参与度=延期无济于事）
用户明显不是目标用户（使用场景不符、市场不符）
用户为了逃避付费而多次申请延期

Extension Framework

延期框架

Scenario	Extension Length	Condition
Active user, needs more time	7 days	Must have completed onboarding
Team evaluation in progress	14 days	Must have 2+ team members active
Re-engagement opportunity	7 days	Was active early, went inactive
Enterprise procurement process	30 days	Must have scheduled a demo/call

场景	延期时长	条件
活跃用户，需要更多时间	7天	必须完成入门引导
团队评估进行中	14天	必须有2名以上团队成员活跃
重新激活机会	7天	前期活跃，中期不活跃
企业采购流程	30天	必须已安排演示/通话

Automatic vs Manual Extensions

自动延期vs手动延期

Automatic: Trigger based on behavior rules (e.g., "active in last 3 days + not upgraded = extend 7 days"). Lower touch, scalable. Manual: Sales/CS reviews and selectively offers. Higher touch, more targeted. Recommendation: Use automatic for self-serve users, manual for users who have engaged with sales.

自动延期： 根据行为规则触发（例如：“过去3天活跃+未升级=延期7天”）。低投入、可规模化。手动延期： 销售/客户成功团队审核后选择性提供。高投入、更具针对性。建议： 自助用户使用自动延期，与销售有过互动的用户使用手动延期。

6. Trial-to-Paid Conversion Optimization

6. 试用转付费转化优化

Removing Friction in the Upgrade Flow

减少升级流程阻力

Pre-fill billing information where possible (company name, email)
One-click upgrade from any in-product gate or notification
Show clear pricing in the upgrade flow (no surprises)
Offer multiple payment methods (card, invoice, PayPal)
Provide plan comparison in the upgrade modal
Allow mid-trial upgrade (do not force users to wait until expiry)
Prorate charges if upgrading mid-billing cycle

预填账单信息（如公司名称、邮箱）
一键升级，可从产品内任何限制点或通知入口触发
升级流程中清晰展示价格（无隐藏费用）
提供多种支付方式（信用卡、发票、PayPal）
升级弹窗中展示版本对比
允许中期升级（不要强迫用户等到试用到期）
中期升级按比例收费（如果在计费周期中期升级）

Addressing Common Objections

处理常见异议

Objection	Response Strategy
"Too expensive"	Show ROI calculation, offer annual discount, suggest starter plan
"Not sure I need it"	Show usage data ("You used X feature 47 times this week")
"Need to get approval"	Provide ROI justification template, offer to join a call with their manager
"Want to try alternatives"	Share competitive comparison, offer extension
"Not the right time"	Offer to pause and resume later, downgrade to free tier
"Missing a feature"	Log the request, show roadmap if applicable, offer workaround

异议	应对策略
“太贵了”	展示ROI计算、提供年付折扣、推荐入门版
“不确定是否需要”	展示使用数据（“你本周使用X功能47次”）
“需要获得批准”	提供ROI证明模板、提出与他们的经理通话
“想尝试替代方案”	分享竞品对比、提供延期
“现在不是合适时机”	提供暂停后恢复的选项、降级到免费版
“缺少某个功能”	记录需求、如果适用展示路线图、提供替代方案

Incentives for Conversion

转化激励措施

Use sparingly -- incentives can devalue your product if overused:

First-month discount (20-30% off first month)
Extended annual discount (save 25% instead of the usual 17%)
Bonus feature or capacity (extra storage, seats, credits for first 3 months)
Onboarding session (free setup call with upgrade)
Money-back guarantee (30-day refund if not satisfied)

谨慎使用——过度使用激励措施会降低产品价值：

首月折扣（首月优惠20-30%）
延长年付折扣（通常优惠17%，改为优惠25%）
额外功能或容量（前3个月赠送额外存储、席位、额度）
入门指导服务（升级即获免费设置通话）
退款保证（30天内不满意可退款）

7. In-Trial Engagement Tracking

7. 试用期间参与度跟踪

Key Metrics to Track During Trial

试用期间需跟踪的关键指标

Metric	What It Indicates	Action if Low
Day 1 activation rate	Is onboarding working?	Redesign first-run experience
Daily/weekly active usage	Is the product sticky?	Send engagement emails, offer help
Feature breadth	Are users exploring premium features?	Send feature discovery prompts
Collaboration signals	Is the user involving their team?	Prompt team invitations
Data/content creation	Is the user investing in the product?	Help with data import, templates
Return visits	Is the user building a habit?	Improve notification and reminder system
Time in product	How engaged are sessions?	Improve UX, reduce friction
Support interactions	Is the user seeking help?	Ensure fast response during trial

指标	指示意义	指标偏低时的行动
第1天激活率	入门引导是否有效？	重新设计首次使用体验
日/周活跃用户数	产品是否具备粘性？	发送参与度邮件、提供帮助
功能覆盖度	用户是否在探索付费功能？	发送功能发现提示
协作信号	用户是否在邀请团队成员？	提示用户邀请团队成员
数据/内容创建量	用户是否在产品上投入？	协助用户进行数据导入、提供模板
回访次数	用户是否在养成使用习惯？	优化通知和提醒系统
产品使用时长	会话参与度如何？	优化用户体验、减少阻力
支持交互次数	用户是否在寻求帮助？	确保试用期间响应迅速

Building a Trial Health Score

构建试用健康度评分

Create a composite score (0-100) combining:

Trial Health Score = weighted sum of:
  - Activation completed (0 or 1) x 25
  - Days active / trial length x 20
  - Features explored / key features x 20
  - Team members invited (0 or 1+) x 15
  - Data/content created (0 or 1+) x 10
  - Recency (days since last login) x 10

Segments:
  - 80-100: Hot lead (likely to convert, nurture carefully)
  - 50-79: Warm lead (needs guidance, offer help)
  - 20-49: Cool lead (at risk, intervention needed)
  - 0-19: Cold lead (likely lost, low-touch win-back)

创建综合评分（0-100），包含以下指标的加权总和：

Trial Health Score = weighted sum of:
  - Activation completed (0 or 1) x 25
  - Days active / trial length x 20
  - Features explored / key features x 20
  - Team members invited (0 or 1+) x 15
  - Data/content created (0 or 1+) x 10
  - Recency (days since last login) x 10

Segments:
  - 80-100: 高潜力线索（很可能转化，需精心培育）
  - 50-79: 中潜力线索（需要引导，提供帮助）
  - 20-49: 低潜力线索（有流失风险，需要干预）
  - 0-19: 无效线索（可能已流失，低投入赢回）

8. Trial Segmentation

8. 试用用户细分

Different Trials for Different Users

为不同用户提供不同试用体验

Not all trial users are the same. Consider segmenting by:

Segment	Trial Variation	Rationale
Individual vs Team	Individuals: shorter trial, simpler onboarding. Teams: longer trial, team setup guidance	Teams need time to deploy
Role	Customize onboarding and feature highlights by role (marketer vs developer vs designer)	Different aha moments
Company size	SMB: self-serve trial. Enterprise: trial + sales touch	Enterprise buying process is different
Use case	Customize sample data, templates, and guides by use case	Faster time-to-value
Source	Users from paid ads: more aggressive conversion. Organic: more nurturing	Different intent levels
Engagement level	Active users: premium feature nudges. Inactive: re-engagement campaigns	Meet users where they are

并非所有试用用户都相同。可考虑按以下维度细分：

细分维度	试用体验差异	理由
个人vs团队	个人用户：更短试用时长、更简单的入门引导；团队用户：更长试用时长、团队设置指导	团队需要时间部署产品
角色	根据角色（营销人员vs开发人员vs设计师）定制入门引导和功能亮点	不同角色的aha时刻不同
公司规模	中小企业：自助试用；企业：试用+销售跟进	企业购买流程不同
使用场景	根据使用场景定制示例数据、模板和指南	更快实现价值
来源	付费广告用户：更激进的转化策略；自然流量用户：更多培育	购买意愿不同
参与度	活跃用户：付费功能提示；不活跃用户：重新激活活动	满足用户当前状态的需求

Implementation

实施方法

Capture segmentation signals at signup (role, company size, use case -- but keep the form short)
Use progressive profiling to gather more data during the trial
Route users into segment-specific onboarding flows
Customize email sequences and in-product messaging per segment
Track conversion rates per segment to identify which segments convert best

注册时收集细分信号（角色、公司规模、使用场景——但表单要简短）
试用期间逐步收集更多数据（渐进式画像）
将用户导入对应细分群体的入门引导流程
为每个细分群体定制邮件序列和产品内消息
跟踪每个细分群体的转化率，识别转化效果最好的群体

9. Conversion Benchmarks

9. 转化基准

Industry Benchmarks

行业基准

Trial Type	Conversion Rate	Notes
Opt-in (no card)	3-8%	Higher for products with strong aha moment
Opt-out (card required)	40-60%	Includes users who forget to cancel
Reverse trial	5-15% to paid	Many stay on free tier (total retained: 60-80%)
Freemium + trial	Varies	Depends on when trial is offered

试用类型	转化率	说明
选择加入式（无需信用卡）	3-8%	拥有清晰aha时刻的产品转化率更高
选择退出式（需信用卡）	40-60%	包含忘记取消订阅的用户
反向试用	5-15%转付费	很多用户留在免费版（总留存率：60-80%）
免费增值+试用	差异较大	取决于试用推送时机

Factors That Increase Conversion

提升转化率的因素

Strong Day 1 experience with clear first win
Personalized onboarding based on use case
Team adoption during trial (2+ users = 3x more likely to convert)
Data import or content creation (switching cost)
Multiple feature discovery (3+ features = 2x more likely)
Engagement with support or sales during trial

出色的第1天体验，清晰的首次成功
根据使用场景定制的个性化入门引导
试用期间团队采用（2名以上用户=转化可能性提升3倍）
数据导入或内容创建（转换成本）
探索多个功能（3个以上功能=转化可能性提升2倍）
试用期间与支持或销售团队互动

Factors That Decrease Conversion

降低转化率的因素

Slow or broken onboarding
No clear aha moment reached
Solo usage without team involvement
Competing alternatives evaluated simultaneously
Price shock at conversion (pricing not visible during trial)
Complex checkout or billing process

缓慢或失效的入门引导
未达到清晰的aha时刻
仅个人使用，无团队参与
同时评估竞品
转化时的价格冲击（试用期间未展示价格）
复杂的结账或账单流程

10. A/B Test Ideas for Trials

10. 试用相关A/B测试思路

High-Impact Tests

高影响力测试

Test	Hypothesis	Metric
Trial length (7 vs 14 days)	Shorter trial creates urgency	Conversion rate, time-to-upgrade
Card required vs not	Card required improves lead quality	Conversion rate, signup volume, revenue
Onboarding flow (guided vs self-serve)	Guided onboarding improves activation	Day 1 activation, feature adoption, conversion
Expiry email copy (urgency vs value)	Value-focused copy converts better	Email CTR, conversion rate
Extension offer (yes vs no)	Extensions increase total conversions	Conversion rate, delayed conversion rate
Upgrade CTA placement (in-app vs email)	In-app CTAs convert better	Upgrade click rate, conversion rate
Trial start (immediate vs delayed)	Delaying premium features until aha moment	Conversion rate, engagement
Pricing visibility (shown vs hidden during trial)	Showing price early sets expectations	Conversion rate, upgrade flow drop-off

测试内容	假设	衡量指标
试用时长（7天vs14天）	更短的试用时长能制造紧迫感	转化率、升级时长
需信用卡vs无需信用卡	需信用卡能提升线索质量	转化率、注册量、收入
入门引导流程（引导式vs自助式）	引导式入门引导能提升激活率	第1天激活率、功能采用率、转化率
到期邮件文案（紧迫感vs价值导向）	价值导向的文案转化率更高	邮件点击率、转化率
提供延期vs不提供延期	延期能提升总转化率	转化率、延迟转化率
升级CTA位置（产品内vs邮件）	产品内CTA转化率更高	升级点击率、转化率
试用启动时机（立即vs延迟）	等到用户达到aha时刻再推送付费功能	转化率、参与度
价格可见性（试用期间展示vs隐藏）	提前展示价格能建立预期	转化率、升级流程流失率

How to Prioritize Tests

如何优先测试

Use ICE scoring:

Impact: How much will this move the conversion rate? (1-10)
Confidence: How confident are you in the hypothesis? (1-10)
Ease: How easy is this to implement? (1-10)

Score = (Impact + Confidence + Ease) / 3. Run highest-scoring tests first.

使用ICE评分：

影响力（Impact）： 该测试能在多大程度上提升转化率？（1-10）
信心（Confidence）： 你对假设的信心有多高？（1-10）
实施难度（Ease）： 实施该测试的难度有多大？（1-10）

评分=（影响力+信心+实施难度）/3。优先运行评分最高的测试。

11. Diagnostic Questions

11. 诊断问题

When helping a user with trial optimization, ask:

What type of trial do you currently offer? (Opt-in, opt-out, reverse, hybrid)
What is your current trial length and conversion rate?
How long does it take users to reach the aha moment?
What does your trial onboarding flow look like?
Do you have a trial email sequence? How many emails, what cadence?
Do you track engagement during the trial? What metrics?
Do you offer trial extensions? Under what conditions?
Do you segment trial users? How?
What is your upgrade flow like? (Steps, friction points)
Do you have a free tier that users fall back to after trial expiry?
What are the top reasons users give for not converting?
What A/B tests have you run on the trial?

当帮助用户进行试用优化时，可询问以下问题：

你当前提供哪种类型的试用？（选择加入式、选择退出式、反向、混合）
你当前的试用时长和转化率是多少？
用户达到aha时刻需要多长时间？
你的试用入门引导流程是怎样的？
你是否有试用邮件序列？有多少封邮件，发送频率如何？
你是否跟踪试用期间的参与度？跟踪哪些指标？
你是否提供试用延期？在什么条件下提供？
你是否对试用用户进行细分？如何细分？
你的升级流程是怎样的？（步骤、阻力点）
试用到期后，用户是否可以降级到免费版？
用户不转化的主要原因是什么？
你针对试用运行过哪些A/B测试？

Codebase Audit (Optional)

代码库审计（可选）

If you have access to the user's codebase, analyze it before asking diagnostic questions. Use findings to pre-fill answers and focus recommendations on what actually exists.

Find trial logic: Search for
```
trial
```
,
```
trial_start
```
,
```
trial_end
```
,
```
trial_days
```
,
```
trialExpires
```
,
```
isTrial
```
in models and business logic
Check trial type: Is it opt-in (no card) or opt-out (card required)? Search for payment collection during signup
Find trial duration: Search for trial length constants --
```
14
```
,
```
30
```
,
```
TRIAL_DAYS
```
,
```
trial_period
```
Find expiry handling: Search for trial expiry logic -- what happens when the trial ends? Search for
```
expired
```
,
```
trial_ended
```
,
```
downgrade
```
Check trial emails: Search for email templates related to trials --
```
trial-welcome
```
,
```
trial-reminder
```
,
```
trial-expiring
```
,
```
trial-expired
```
Find trial extension logic: Search for
```
extend
```
,
```
trial_extension
```
,
```
extra_days
```
-- can trials be extended?
Check conversion flow: What happens at trial end? Search for the upgrade/payment flow triggered by expiry
Find trial analytics: Search for tracking events on trial starts, activations, conversions, expirations

Report: describe the current trial implementation -- type, length, expiry behavior, email sequence, and conversion flow.

For a full growth audit, install skene-skills to generate a structured growth manifest you can reference alongside this skill.

如果你能访问用户的代码库，在询问诊断问题前先进行分析。利用分析结果预先填充答案，并将建议聚焦于实际存在的内容。

查找试用逻辑： 在模型和业务逻辑中搜索
```
trial
```
、
```
trial_start
```
、
```
trial_end
```
、
```
trial_days
```
、
```
trialExpires
```
、
```
isTrial
```
检查试用类型： 是选择加入式（无需信用卡）还是选择退出式（需信用卡）？搜索注册期间的支付收集逻辑
查找试用时长： 搜索试用时长常量——
```
14
```
、
```
30
```
、
```
TRIAL_DAYS
```
、
```
trial_period
```
查找到期处理逻辑： 搜索试用到期逻辑——到期后会发生什么？搜索
```
expired
```
、
```
trial_ended
```
、
```
downgrade
```
检查试用邮件： 搜索与试用相关的邮件模板——
```
trial-welcome
```
、
```
trial-reminder
```
、
```
trial-expiring
```
、
```
trial-expired
```
查找试用延期逻辑： 搜索
```
extend
```
、
```
trial_extension
```
、
```
extra_days
```
——是否可以延期试用？
检查转化流程： 试用到期后会发生什么？搜索到期触发的升级/支付流程
查找试用分析逻辑： 搜索跟踪试用开始、激活、转化、到期的事件

报告：描述当前试用实现方式——类型、时长、到期行为、邮件序列和转化流程。

如需完整的增长审计，请安装skene-skills以生成结构化的增长清单，可结合本内容参考。

12. Output Format

12. 输出格式

When completing a trial optimization engagement, deliver:

markdown

undefined

当完成试用优化服务时，交付以下内容：

markdown

undefined

Trial Optimization Strategy: [Product Name]

试用优化策略：[产品名称]

Trial Model

试用模型

Type: [Opt-in / Opt-out / Reverse / Hybrid]
Length: [N days]
Rationale: [Why this model and length]

类型：[选择加入式 / 选择退出式 / 反向 / 混合]
时长：[N天]
理由：[选择该模型和时长的原因]

Trial Experience Design

试用体验设计

Day 1 Experience

第1天体验

Mid-Trial Milestone (Day [N/2])

试用中期里程碑（第[N/2]天）

[What should have happened by midpoint]

[中期应完成的事项]

Pre-Expiry (Day [N-3] to Day [N])

到期前（第[N-3]天至第N天）

[Urgency and conversion tactics]

[紧迫感和转化策略]

Email Sequence

邮件序列

Day	Email Type	Subject Line	Key Content
0	Welcome	[Subject]	[Content summary]
1	Quick win	[Subject]	[Content summary]
...	...	...	...

天数	邮件类型	主题	核心内容
0	欢迎邮件	[主题]	[内容摘要]
1	快速成功邮件	[主题]	[内容摘要]
...	...	...	...

Engagement Tracking

参与度跟踪

Key metrics: [list]
Health score model: [components and weights]
Intervention triggers: [when to take action]

关键指标：[列表]
健康度评分模型：[组成部分和权重]
干预触发条件：[何时采取行动]

Conversion Optimization

转化优化

Upgrade flow: [steps and optimizations]
Objection handling: [top 3 objections and responses]
Incentives: [if applicable]

升级流程：[步骤和优化点]
异议处理：[前3个异议及应对方案]
激励措施：[如有]

Segmentation

用户细分

Segments: [list]
Per-segment variations: [differences in experience]

细分群体：[列表]
各细分群体体验差异：[体验上的不同]

A/B Test Roadmap

A/B测试路线图

[Test 1]: [Hypothesis, metric, priority]
[Test 2]: [Hypothesis, metric, priority]
[Test 3]: [Hypothesis, metric, priority]

[测试1]：[假设、衡量指标、优先级]
[测试2]：[假设、衡量指标、优先级]
[测试3]：[假设、衡量指标、优先级]

Success Metrics

成功指标

Current conversion rate: [X%]
Target conversion rate: [Y%]
Timeline: [when to evaluate]

---

当前转化率：[X%]
目标转化率：[Y%]
评估时间线：[何时评估]

---

13. Related Skills

13. 相关技能

```
activation-metrics
```
-- Measuring and optimizing the aha moment that trials depend on
```
feature-gating
```
-- Deciding what to include in the trial vs gate behind payment
```
pricing-strategy
```
-- Overall pricing framework that the trial supports
```
product-onboarding
```
-- First-run experience design that drives trial activation

```
activation-metrics
```
——衡量和优化试用所依赖的aha时刻
```
feature-gating
```
——决定试用中包含哪些功能，哪些功能需要付费解锁
```
pricing-strategy
```
——试用所支撑的整体定价框架
```
product-onboarding
```
——驱动试用激活的首次使用体验设计