The FemtoConf 2018 Notes and recaps can be found on the central hub page.
Website: profitwell.com
Twitter: @Patticus
- How growth is changing: What we think works doesn’t actually work. This has dire consequences for your business.
- We are living on another planet:
- 10 years ago you could build a database with a shiny UI and you were good
- Today you face fierce competition
- Number of competitors when you started:
- 5 years ago: about 3
- 1 year ago: roughly 10
- Sales & Marketing channels are plentiful
- Number of sales & marketing channels utilized
- 15 years old: 2.31
- 1 year old: 13.22
- competition is getting harder and harder
- Number of sales & marketing channels utilized
- Time taken to fully onboard product in an organization:
- 10 years ago: 56.7 hours
- 1 year ago:
- Customer acquisition cost (CAC) has increased significantly by about 70% over the past 5 years
- relative value of features is declining
- willingness to pay has declined over time
- Customers do not care about your features (average NPS is actually down from 33 to 10.2)
- What once worked is no longer working for building a business
- Our playbook was acquire, acquire, acquire
- Pricing (and retention) is an afterthought
- Acquisition is now table stakes
- Impact of improving:
- Monetization >> Retention >> Acquisition
- We are building the wrong product, because we don’t talk to our customers enough
How do we fix this?
- Stop building. Stop buying ads. Stop guessing and checking.
- For the love of God: Talk to your customer!
- How do we do that?
- There are three types of data you’re really looking to measure:
- Demographic data (purely for segmentation – i.e. size of team, revenue, software they are using)
- Relative Preference Data
- Willingness to Pay Data
- Surveys
- a non-compensated survey should be at most 5 questions long
- compensated surveys maximum of 15 minutes
- Start with a draft of your buyer personas
- What’s our experimental design look like?
- Relative preference: What do people value?
- Don’t let them rank features on a scale of 1 to 10
- Force them to decide on the most/least important feature
- Relative preference: What do people value?
- There are three types of data you’re really looking to measure:
- How much are people willing to pay?
- At what (monthly) price point does PRODUCT become too expensive that you’d never consider purchasing it?
- At what (monthly) price point does PRODUCT start to become too expensive, but you’d still consider purchasing it?
- At what (monthly) price point is PRODUCT a really good deal?
- At what (monthly) price point does PRODUCT become so cheap that you question the quality of it?
[…] Patrick Campbell: Value based pricing […]