GROWtalks - Grow Like an Olympian, Know What Fast Really Means - Brian Krausz
1.
2. Growing Your Product
What happens after product-market
fit
Brian Krausz
Facebook Engineer
January 30, 2014
3. Who am I?
▪
GazeHawk
▪
Eye tracking startup
▪
YC/500s funded
!
▪
Facebook since 2012
▪
Web, iOS, infrastructure
4. When do you grow?
When do you grow?
!
After you find product market
fit
5. Don’t Waste Effort on Premature Growth
“You can always feel when product/market fit isn't happening
… and you can always feel product/market fit when it's
happening.”
- Marc Andreesen
▪
Engagement has more ancillary
benefits
▪
▪
▪
Better press & morale
Overlaps with growth anyway
Maximize growth ROI
▪
Even FB is careful here
Quote: http://www.stanford.edu/class/ee204/ProductMarketFit.html
7. The Happy Path
▪
Be the easiest path forward
for your users
!
▪
Go where your users are
!
▪
Minimize decisions
▪
“The paradox of choice”
The paradox of choice: http://www.ted.com/talks/barry_schwartz_on_the_paradox_of_choice.html
8. Your new users
▪
Not acclimated to your product
!
▪
Less like you than your current users are
!
▪
Using less-tested paths
9. Where do you focus your effort?
▪
It depends on your users
▪
Go where your new users
are
▪
▪
International (not just
language, culture)
▪
▪
Youth
Mobile
Don’t be afraid of big
changes
▪
Ex: FB iOS Navigation
10. International
Rest of World
Asia
Europe
US & Canada
MAU by region (in Millions)
1,200
960
720
480
207
196
225
212
245
234
268
255
288
277
304
298
327
346
362
319
339
351
253
261
269
272
276
221
229
239
246
176
179
183
186
189
193
195
198
199
Q3'11
Q4'11
Q1'12
Q2'12
Q3'12
Q4'12
Q1'13
Q2'13
Q3'13
240
0
Facebook Earnings Report, Q3 2013
11. Mobile
Mobile-Only MAU (in Millions)
260
254
219
208
189
156
104
157
126
52
0
Q3'12
Facebook Earnings Report, Q3 2013
Q4'12
Q1'13
Q2'13
Q3'13
17. A Word on Data
▪
Dashboards!
▪
▪
▪
Rallying cry for your team
Makes arguments shorter
Pick a few metrics to optimize
▪
▪
Double-edged sword
▪
▪
ex: MAU/WAU/DAU, churn, revenue, user sentiment
Data doesn’t tell you if you’re using the wrong data
Whenever possible, pre-emptive logging is faster
▪
Analytics over A/B test logging: it lasts longer
19. Balance data with analytics capabilities
!
▪
Invest in both
▪
Analytics are usually
under-invested in
!
▪
Re-evaluate often
▪
“Move fast and break
things”