startup phenomenon - analytics for startups
TRANSCRIPT
Master Class: Analytics for Startups - Startup Phenomenon
Lars LofgrenGrowth Manager - November 2013
@larslofgren
The data problems that startups face1
Gateway metrics2
4 gateways and the metrics for each3
We’ll cover...
Let’s start measuring!
If you’re SaaS, track these:
Monthly Recurring Revenue1
Monthly Churn2
Cost Per Acquisition3
Lifetime Value4
Signup Funnel5
Use these for ecommerce:
Site Conversion Rate1
Total Revenue2
Average Order Value3
Annual Repurchase Rate4
Merchandise5
Consumer tech? Track these bad boys:
Monthly Active Users1
Daily Active Users2
Virality3
Engagement by Cohort4
Activation5
Sounds easy right? Time to jump in!
There’s just one little problem...
You can’t track them. At least not right away.
You’re just getting started.
Advanced metrics are a luxury you don’t need.
Over time, your data decays.
Your data is messy.
It takes time to perfect your metrics.
Super basic version of lifetime value for SaaS:
Average subscription length
Average monthly subscription X
Advanced LTV formula:
LTV =(Average revenue per
account X gross margin)
*forentrepreneurs.com/saas-metrics-2-definitions
Xmonthly churn (monthly churn)
(Monthly growth in average revenue) X (1 - monthly churn)
2
Lack of data.1
Advanced metrics are a luxury.2
Data decays over time.3
Data gets messy.4
It takes time to perfect metrics.5
Let’s review the problems we face:
Gateway Metrics
When picking metrics, always ask yourself:
What’s my single biggest constraint right now and which metric will tell
me if I’m making progress?
Why ignore other data?
You need to do the right things in the right order.
Every business model is slightly different.
Let’s cover the main gateways that startups face when getting traction.
Gateway 1: Is your idea any good?
Your main constraint:
Getting anyone to care about your idea.
Your main metric:
Can you get anyone to pay for your product or use it regularly?
Bad metrics for this gateway:
Asking people if they’ll pay1
Adwords clicks2
Beta or waiting list signups3
Traffic4
Gateway 2: Is your product good enough?
Your main constaint:
Having a product that’s good enough to build a business on.
Your main metric:
Ask 500 users the Product/Market Fit Question
What’s the P/M Fit Question?
How would you feel if you could no longer use [your product]?
Very disappointed1
Somewhat disappointed2
Not disappointed (it isn’t really that useful)
3
Your goal for the P/M Fit Question:
At least 40% of your users should say “Very disappointed”.
*Sean Ellis and Hiten Shah get credit for this one
What about traffic, conversions, or engagement?
None of that matters (yet).
Gateway 3: Can you grow?
Your main constraint:
Acquiring customers consistently from at least one channel.
Possible channels:
Inbound (Google, Content, Social)1
Paid (PPC, Affiliates)2
3 Virality (Invites, Referrals)3
Pick just one to start.
Work on a single channel for 3 months. Assume it’ll work and get the resources needed to execute.
Your main metrics:
Your acquisition funnel and your main business metric.
Main business metrics:
SaaS: Monthly Recurring Revenue1
Ecommerce: Monthly Revenue2
3 Consumer Tech: Monthly Active Users3
SaaS Funnel:
Ecommerce Funnel:
Consumer Tech Funnel:
Why not cost per acquisition?
You don’t even know if you can acquire customers let alone how
much it’ll cost.
Gateway 4: Do you have a stable model?
Your main constraint:
In order to keep scaling, you need a healthy model for your business.
Your main metrics:
They depend entirely on which business model you’ve choosen.
The SaaS Model:
LTV is at least 3x acquisition cost 1
Recover acquisition cost within 12 months2
3 Get monthly churn below 2%3
The Ecommerce Model:
Annual repurchase rate below 40% = focus on customer acquisition
1
Annual repurchase rate 40%-60% = acquisition and loyalty
2
*Kevin Hillstrom in Lean Analytics
Annual repurchase rate above 60% = focus on loyalty
3
The Consumer Tech Model
Virality > 11
Usage 3 out of 7 days2
30% users active day after signup3
Organic growth of 100s signups/day4
Clear path to 100,000+ users5
*Andrew Chen’s “Zero to Product/Market Fit”
Time to get serious with data.
How to get the data you need:
One team owns data quality.1
Hire a data scientist if you need to.2
Clean up your data.3
Use customer analytics.4
Tie all data back to individual users.5
Where to find these slides:
kiss.ly/startup-phenom
