data-driven growth at startups
TRANSCRIPT
Data-driven growth at startups
Hyper Island, Sep 1 2015 Lisa Enckell, @enckelli
Focus groups Surveys Sampling “Gut feel”
Market research is nothing new
Real user behavior
Three ways marketers use data at startups
What’s good for the business
1. Keeping track
vs What makes us look good
Weekly health check
1. Keeping track
Spot early trends and stay curious!
1. Keeping track
Product features Emails and notifications Marketing campaigns and channels
2. Performing experiments
3. Automating user communication
On-boarding Retention (decrease churn) Up-sell/engagement
3. Automating user communication
Trigger/sender Automatic Manual
App to user Welcome emails Receipts
Campaigns Product updates
User to user Anniversaries Birthdays
In-app messages Invites to non-users
Who should do the work?
Data in the organization
1. Make it accessible and available for everyone!
Data in the organization
2. Everyone should and could be data-drivenNew features and A/B-tests (product manager/developers)Conversions (product manager/marketer)Response times (back-end)KPIs and trends (marketing/leadership)Campaigns and acquisition (marketing)User insights (marketing/support/product)Notifications and emails (marketing)Recruiting time (HR/leadership)Sales cycles, up-sell and on-boarding time (sales)
Viral growth
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The viral loop
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The viral loop
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On-ramp
The viral loop
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On-ramp
Branching factor
The viral loop
Viral factor K = I・C
Invites I Conversion rate C Cycle time p
Given that I get a new customer today, how many new customers will they bring in over the next p days?
0 5 10 15 20
0
50
100
150
200
K = 1.2
K = 1.1
K = 0.5
For different values of viral factor K
Users
Weeks
0 5 10 15 20
0
100
200
300
400
500
p = 0.5
p = 1
p = 2
For different lengths of cycle time
Users
Weeks
Maximize viral factor K = IC
Maximize no of invites I Maximize conversion rate C
Minimize cycle time p
In summary:
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Thank you!
Lisa Enckell, @enckelli