Chapters

01Pre-Launch Foundation
1.1 Define Your Launch Narrative
1.2 Build Your Positioning Framework
1.3 Map Customer Pain Points & Jobs-to-be-Done
1.4 Develop Persona-Specific Messaging
1.5 Create Competitive Positioning
02Product Documentation & Collateral
03Internal Enablement
04Launch Calendar & Campaign Planning
05Website & SEO Optimization
06Website & SEO
07Email Marketing Campaigns
08Social Media Strategy
09Launch Day Execution
10Post-Launch Activities
11Measurement & Analytics
12Launch Checklist
Progress11 of 12

Chapter 11

Measurement & Analytics

Ongoing

You can't improve what you don't measure. This section ensures you track what matters.

11.1 Launch Metrics Dashboard

What you're creating: A centralized view of launch performance.

Deliverables

Real-time metrics dashboard
Key metric definitions
Target benchmarks

How to execute

1
Define your metrics
·Awareness Metrics: Website traffic (sessions, unique visitors), Social reach (impressions, followers gained), PR mentions (articles, backlinks), Brand searches (via Google Trends)
·Engagement Metrics: Email open rate and click rate, Social engagement rate (likes, comments, shares), Video views and completion rate, Time on site and pages per session
·Conversion Metrics: Demo requests, Free trial sign-ups, Paid conversions, Conversion rate by channel
·Product Metrics: Feature activation rate, Daily/weekly active users, Feature usage, Error/bug rate
·Revenue Metrics: Pipeline generated, Deals influenced, Average deal size, Sales cycle length
·Customer Success Metrics: Onboarding completion rate, Time to value, Support tickets, Customer satisfaction (NPS, CSAT)
2
Set targetsExample targets in the table below
MetricBaselineT-DayT+7T+30T+90
Website visitors10K/mo+50%+75%+100%+150%
Trial sign-ups200/mo+100%+125%+150%+200%
Activation rate60%65%70%75%80%
Deals influenced515254060
3
Build dashboard
·Section 1 Overview: Total reach (across all channels), Total conversions (trials + demos), Revenue influenced
·Section 2 Channel Performance: Website (Traffic, conversions), Email (Sends, opens, clicks, conversions), Social (Reach, engagement), Paid (Spend, impressions, conversions, ROAS)
·Section 3 Product Performance: Sign-ups, Activation rate, Feature usage, Retention
·Section 4 Sales Impact: Demos booked, Opportunities created, Deals won, Pipeline generated
·Tools: Google Data Studio (free), Databox (paid), Geckoboard (paid), Custom (via your data warehouse)
4
Schedule reviews
·Daily (first week): Quick metrics check (5 min), Note anomalies, Adjust tactics if needed
·Weekly (first month): Deep dive (30 min), Compare to targets, Identify what's working/not, Plan next week's focus
·Monthly (ongoing): Comprehensive review (1 hour), Report to leadership, Update strategy
Who owns itProduct Marketing, Growth Marketing
Tools neededGoogle Analytics, Mixpanel, Databox
Update frequencyReal-time data, reviewed daily/weekly

11.2 Performance Analysis

What you're creating: Insights from launch data to improve future launches.

Deliverables

Channel performance report
Content performance report
Conversion funnel analysis
ROI analysis

How to execute

1
Analyze by channelFor each channel evaluate the metrics in the table below
ChannelInvestmentReachEngagementConversionsCACROASRating
LinkedIn$5K50K5%150$334.5x⭐⭐⭐⭐⭐
Email$1K25K22%200$512x⭐⭐⭐⭐⭐
Paid Search$10K100K2%100$1001.8x⭐⭐⭐
📌Insights — Which channels delivered best ROI? Where should you invest more? What should you cut?
2
Analyze content performanceFor each piece of content evaluate the metrics in the table below
ContentTypeViewsEngagementConversionsTime InvestedEfficiency
Demo videoVideo5K45%12010 hrs⭐⭐⭐⭐⭐
Launch blogBlog3K25%508 hrs⭐⭐⭐
Feature threadTwitter10K8%202 hrs⭐⭐⭐⭐
📌Insights — What content formats work best? What topics resonate? Where should you double down?
3
Analyze conversion funnelMap the journey
·Website Visit → Sign-up → Activation → Paid Conversion: 100% → 15% → 60% → 25% (10,000 → 1,500 → 900 → 225)
·Why did 85% not sign up? (Landing page, CTA, value prop?)
·Why did 40% not activate? (Onboarding, complexity, value?)
·Why did 75% not convert? (Pricing, features, competition?)
·Biggest drop-off: Sign-up (85% loss). If sign-up improves to 20%, conversions increase 33%
4
Calculate ROI
·Launch investment: Team time $50K, Tools/software $5K, Paid advertising $15K, Events $10K, Total $80K
·Launch returns (first 90 days): Trials 1,500, Paid conversions 225, Average deal $5,000/year, Revenue $1.125M ARR, ROI 14x, Payback period 25 days
5
Document learnings
·What worked: Short-form video performed best, Customer testimonials drove conversions, Email had highest ROI, LinkedIn generated quality leads
·What didn't work: Display ads underperformed, Long-form blog posts got low engagement, Event attendance was lower than expected
·What we'd do differently: Start email campaign earlier, Invest more in video content, Skip display ads, Focus on virtual events over in-person
Who owns itProduct Marketing Lead
TimelineReport complete by T+30
Present toMarketing leadership, exec team

11.3 Post-Launch Retrospective

What you're creating: A comprehensive review meeting to capture lessons.

Deliverables

Retrospective meeting
Lessons learned doc
Template for next launch

How to execute

1
Schedule retrospective (T+30)
·Invite: Product Marketing, Growth Marketing, Product Management, Sales, Customer Success, Design
·Duration: 90 minutes
2
Prepare meeting agenda
·Pre-work (send 48 hours before): Share launch metrics, Ask team to reflect on what went well, what didn't, and what they'd change
·Part 1 Celebrate wins (15 min): What exceeded expectations? What are we proud of? Who deserves recognition?
·Part 2 Review metrics (20 min): Did we hit our goals? What surprised us? Where did we fall short?
·Part 3 Discuss challenges (30 min): What didn't work? What blockers did we face? Where did we waste time/resources?
·Part 4 Capture lessons (15 min): What would we do differently? What should we stop/start/continue? What should be a standard practice?
·Part 5 Plan improvements (10 min): What changes should we make now? What do we need for next launch? Who owns each action item?
3
Document lessons learned
·What to keep: Early email teaser campaign (drove registrations), Employee advocacy (expanded reach), Video-first approach (high engagement)
·What to change: Start creative production earlier (was rushed), More sales training touchpoints (they felt underprepared), Simpler pricing messaging (confused prospects)
·What to add: Beta program before launch, More customer testimonials ready at launch, Better internal coordination tool
·What to remove: In-person event (low attendance, high effort), Display ads (poor ROI), Lengthy blog posts (low engagement)
4
Create launch playbook templateBuild reusable template with
·Timeline with key milestones
·Checklist of all deliverables
·Templates for common assets (emails, social posts, one-pagers)
·Meeting agendas for key sessions
·Dashboard templates
·Roles and responsibilities matrix
5
Share widelyDistribute retrospective findings to
·Everyone involved in launch
·Leadership
·Broader marketing team
·Future launch teams
Who owns itProduct Marketing Lead
TimelineMeeting at T+30, doc published T+32
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Will this work with my janky screen recordings?

We don’t use your data to train our models. Each feature is designed to be privacy-first, so you can be assured that your data is always secure.

Is my data safe? What security measures do you take to ensure this?

We don’t use your data to train our models. Each feature is designed to be privacy-first, so you can be assured that your data is always secure.

Frequently Asked Questions

Will this work with my janky screen recordings?

Yes you do not need to be perfect. Record whatever you want and AI will fix it for you.

What if I want to sound like myself?

We are coming up with voice cloning feature next.

Will this work with my janky screen recordings?

Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks that typically require human intelligence. These tasks include problem-solving, learning, perception, speech recognition, and language understanding. AI aims to create machines that can mimic human cognitive functions and improve their performance over time.

Is my data safe? What security measures do you take to ensure this?

We don’t use your data to train our models. Each feature is designed to be privacy-first, so you can be assured that your data is always secure.

Is my data safe? What security measures do you take to ensure this?

We don’t use your data to train our models. Each feature is designed to be privacy-first, so you can be assured that your data is always secure.

Is my data safe? What security measures do you take to ensure this?

We don’t use your data to train our models. Each feature is designed to be privacy-first, so you can be assured that your data is always secure.

Will this work with my janky screen recordings?

We don’t use your data to train our models. Each feature is designed to be privacy-first, so you can be assured that your data is always secure.

Is my data safe? What security measures do you take to ensure this?

We don’t use your data to train our models. Each feature is designed to be privacy-first, so you can be assured that your data is always secure.

Frequently Asked Questions

Will this work with my janky screen recordings?

Yes you do not need to be perfect. Record whatever you want and AI will fix it for you.

What if I want to sound like myself?

We are coming up with voice cloning feature next.

Will this work with my janky screen recordings?

Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks that typically require human intelligence. These tasks include problem-solving, learning, perception, speech recognition, and language understanding. AI aims to create machines that can mimic human cognitive functions and improve their performance over time.

Is my data safe? What security measures do you take to ensure this?

We don’t use your data to train our models. Each feature is designed to be privacy-first, so you can be assured that your data is always secure.

Is my data safe? What security measures do you take to ensure this?

We don’t use your data to train our models. Each feature is designed to be privacy-first, so you can be assured that your data is always secure.

Is my data safe? What security measures do you take to ensure this?

We don’t use your data to train our models. Each feature is designed to be privacy-first, so you can be assured that your data is always secure.

Will this work with my janky screen recordings?

We don’t use your data to train our models. Each feature is designed to be privacy-first, so you can be assured that your data is always secure.

Is my data safe? What security measures do you take to ensure this?

We don’t use your data to train our models. Each feature is designed to be privacy-first, so you can be assured that your data is always secure.