Scaled Inference

1. SCA LED
INFERENCE
Useful, Accessible AI

2. Useful, Accessible AI
Amp.ai
SCA LED
INFERENCE
Olcan Sercinoglu
Founder & CEO
Growth Amplified
via Autonomous Optimization

3. Source: Reforge post on "Building Growth: Product, Process, and Team"
Growth?

4. Design
Variants
Implement
Variants
Test with Data
Design
Variants
Implement
Variants
Optimize with Data
Retention
Acquisition
Activation
Engagement
Monetization
Source: SI Blog at https://scaledinference.com/blog
Growth via Testing vs Optimization

5. Predefined SegmentPredefined Segment
Negative Impact
Baseline Variant Learned Segment
Positive Impact

6. Learned Segment
Positive Impact
• Audiobook credits used during trial subscription?
• Dismissed promotion X within last 24 hours?
• Small screen & slow connection?
• Newer iOS device & high-GDP country?
• Weekday & after 10AM local time?
Example Learned Segments*
* Additional behavioral and demographic segments
available from 3rd party sources, e.g. Nielsen.

7. YES, but optimization (better metrics) first.
Personal (and contextual) behavior emerge from optimization.
Depending on metrics, we may prefer less personalization.
Fewer variants = simpler product & less code to maintain. Learned Segment
Positive Impact
Is This Personalization?

8. Positive Negative Negative
Time
Predefined
Segment
Positive Positive Positive
Learned
Segments

9. Finding Best
Variants
Finding Best
Segments
Sustaining
Growth
A/B
Testing
Amp.ai

10. decide
variant given segment
(based on context)
observe
context
context
observe
context
outcome
observe
outcome
observe
outcome
AmpSession
time
location
device
network
browser
...
CustomContext
new vs returning
free vs premium
past purchases
ProductPageUX
which thumbnail?
offer free shipping?
emphasize checkout?
emphasize add-to-cart?
AddToCart
item id
price
CheckoutCompleted
number of items
total price (metric)
Example Session
for Checkout Optimization
Variants
as Decisions

11. Sessions
Policies
Segment 1 → Variant A
Segment 2 → Variant B or C
Segment 3 → Variant C
... → ...
Applications
WebMobile IoTServer
Amp.ai
Insights
Metrics
Variants
Segments
Product & Growth
Experts + Developers

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Maximizing Growth
(vs Testing on Predefined Segments)
Amp.ai
A/B Testing
Time
Gains
(Cumulative)

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Use Case Metric Lift by Sessions Value Gain by Sessions
Cumulative, vs A/B Testing @ 1x
Gain Ratio
vs A/B Testing
CTA Click Rate
web, 100M users
8.9x
Sign Up Rate
web, 200M users
8.4x
Purchase Rate
mobile, 12M users
2.5x
Amp.ai A/B Testing * Variants designed for A/B Testing, not AO.

15. Use Case Sessions/mo
Baseline Value
per Session
Value Lift* Gain/mo* ROI*
Cancellation Rate
web, 80M users
120K US$32 +4% $150K 51x
Checkout Revenue
web, 6M users
3.2M US$1.90 +6% $363K 23x
Purchase Rate
web, 80K users
26K US$4.3 +9.5% $10K 7.7x
Subscription Revenue
mobile, 15M users
108K US$0.35 +56% $21K 6.4x
Tab Accept Rate
mobile, 5K users
21K US$0.1 +81% US$1,700 0.71x
* Typical results after first cycle (3-6 weeks) using variants designed for A/B Testing, not AO.

17. Amped Store Example
github.com/ScaledInference/amp-js-demo

18. Scaled Inference Blog
scaledinference.com/blog
• How to Personalize Offers & Prices
• How to Maximize Ecommerce Revenue
Growth using Amp.ai
• How to Implement Autonomous
Optimization Projects using Amp.ai
• How to Design Autonomous
Optimization Projects
• Growth Amplified via Autonomous
Optimization
• A/B Testing vs Autonomous
Optimization
Twitter: @olcan @ScaledInference
Email: olcan@scaledinference.com