spv - northwestern deck (data and machine learning in the real world- from the government to...

Copyright © 2016 Seven Peaks Ventures

Seven Peaks VenturesData and Machine Learning in the Real World: From the Government to

Startups to the Enterprise


Agenda• There and Back Again • The Data Rules • Now What • Amplero: A Real World Example

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There and Back Again…

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• Lumber town • McCormick, Computer Engineering • Northwestern Swimming • Washington, DC • Arbor Software • XMLA • Hyperion • Oracle • Seven Peaks Ventures

The journey…so far


The Data Rules

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Rule #1: There is a LOT of data

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Rule #2: There are a lot of technologies

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Rule #3: There are more coming…

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Rule #4: Most technologies are bullshit

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Rule #5: Bots are mostly bullshit…today

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Rule #6: No one really knows what to do with it

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What do the CIA, P&G and most

Startups have in common?


Rule #7: It’s hard to find resources

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• A scramble is on, creating buyer competition for great teams • Perversely, revenue can reduce value - since an M&A buyer

wants the acquired AI team to focus entirely on THEIR next gen offerings without distraction.

• That’s convenient, because revenue is hard to generate • Supply and demand is at work in these valuations. High-

quality AI engineers are in very short supply, and majors who have fallen behind the AI race


Rule #8: Artificial Intelligence is wrong

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• Over-hyped by the media…but let’s talk jobs • Prefer Automated Intelligence (AI) or

Machine Intelligence vs. Artificial Intelligence


Rule #9: AI is not magical…it’s hard

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Not sexy…


Rule #10: It’s all about the data (quality, features…)

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Better Data != More DataOverfitting Bias Variance Features


Rule #11: It’s all about the business value

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Rule #12: Hardware eats data

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Rule #13: The user experience is make or break

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“What Alexa has shown us that rather than trying to boil the ocean with AI and conversational interfaces, what we need to do is to apply human design intelligence, break down the conversation into smaller domains where you can deliver satisfying results, and within those domains, spend a lot of time thinking through the "fit and finish" so that interfaces are intuitive, interactions are complete, and that what most people try to do "just works."

What Would Alexa Do?


Rule #14: It’s all about the motivations

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Rule #15: Ethics & bias matter

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Rule #16: Laws matter

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Rule #17: It’s all about timing…and the herd

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Peak


Rule #18: Create a Data Board…now

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• Lack of or poor execution on data tactics and strategy

• Insufficient and immature infrastructure to effectively utilize data assets

• Inability to understand, identify, collect, or utilize data assets

• Lack of ROI from existing data initiatives

• Limited resources that understand technical and revenue aspects to properly define and leverage data to drive the business

• Backwards looking data organization

High Data Maturity

Data Gap

Stag

e

MVP

Descriptive 1.0


Rule #19: People & culture matter

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“The first responsibility of a leader is to define reality. The last is to say thank you. In between the two the leader must become a servant and a debtor” —Max de Pree

“Bad news doesn’t get better with age…” —Matt Abrams

“Words matter…what you do matters” —Matt Abrams Max De Pree

-Founder of Herman Miller


Now What?

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Take This With You

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• Make an impact…regardless of what it is • Learn…continuously • Check your bias at the door…debate / understand / disagree…but do it well • Leave it better than you found it • Provide value • Add to these rules


“The Watney Rule”

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“At some point, everything's gonna go south on you... everything's going to go south and you're going to say, this is it. This is how I end. Now you can either accept that, or you can get to work. That's all it is. You just begin. You do the math. You solve one problem... and you solve the next one... and then the next. And If you solve enough problems, you get to come home. All right, questions?”


A Real World Example

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About Olly…Machine learning scientist and serial technology entrepreneur with 32 patents granted

Proven track record of leading science and engineering at high growth startups including AdReady, Atigeo, & Mindset Media.

Founding Principal Scientist at INRIX, the first tech spinout from Microsoft Research

One of the most prolific consulting data scientists in the world!

PhD work in Quantum Computing yielded the fastest computer ever measured!

Erdos number = 3

Olly Downs, PhD CEO & Chief Scientist, Amplero


About Amplero….

April 2016 Spin-Out of Globys, Inc. incubated over the past 3 years

$8M Series A round in July 2016 to fund go-to-market and early customer growth beyond telco

Funded by Wildcat Venture Partners, Salesforce Ventures, Trilogy Equity, and Seven Peaks Ventures

The Amplero Intelligence Platform solves marketers biggest problems – increasing revenue, reducing churn, and growing customer lifetime value (CLV) - for leading brands such as:

Enabling marketers to achieve what is not humanly possible


Predictive Customer Value Management


B2C System of Intelligence for Martech

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Dat

a So

urce

s

Analytics/Modeling Suite

Self-learning

Mktg. Automation

Marketing Tools/Suites

Push

Cha

nnel

s

Data Warehouse

Scores, clusters, predicted values…

Transactional Data

Consolidated Data

Targeting Triggers

Marketing Feedback

Pull

Cha

nnel

sRequests Personalization Decision – Real-time


How Amplero works

Modelling & Enrichment

Marketing Assets

Machine Learning

Experimenting

Enriched Data

Decision Tree

Messages/Offers

Customer Data

Customers

Marketer

Decisioning

machinelearning

MachineLearning


Proven Value Proposition

KPI Lift

Business

Exponential Testing

Marketer

Improved Experience

Consumer

1000xIncrease in the number of statistically significant

tests executed per year

from 21to 2messages per customer per month

strategic & creative

9xIncrease in ARPU Lift

400%customer retention lift

Identified churners 15-21days in advance vs. traditional day of churn


Amplero @ Boost Mobile • MultivariateMarketingatScale32 campaign strategies running concurrently with ability to flex to marketing changes and new initiatives:

+ Over 600 configured experiences and growing

+ 37.5M SMS messages sent to-date

+ 5.4M unique customers targeted, penetrating most of

the marketable base

Num

ber O

f SM

S M

essa

ges

Sent

0

75000

150000

225000

300000

Date

12/15/2019 1/3/2020 1/23/2020 2/7/2020 2/25/2020 3/11/2020 3/29/2020 4/13/2020 5/1/2020 5/20/2020 6/9/2020 6/24/2020 7/10/2020 7/27/2020 8/12/2020 8/27/2020 9/17/2020 10/2/2020

EDU_2 Month Unlimited Upsell (U2MU) EDU_Always On- Test EDU_Bucket' O Plenty (BOP) EDU_Close the Gap - Immediate Pay Off (IPO)EDU_Close the Gap_Respond to Me (RM) EDU_Come Again -Referral (CA-R) EDU_Dealz EDU_Educate Me (EM)EDU_Handset Upgraders (HU) EDU_Ladder Up (LU) EDU_Nurture Newcomer Social Referral (NN) EDU_Nurture Newcomers (NN)EDU_P2P BAU - Sprint EDU_P2P_Amplero Migration (AM) EDU_Preemptive Strike (PS) EDU_Rate Plan Right Fit (RPRF)EDU_Reminder (R) EDU_Rotten Apple (RA) EDU_Self Service (SS) EDU_Welcome Extended Family (WEF)EDU_Welcome Outsiders (WO) GFT_Loyalty_ 2 Months Unlim (L) GFT_Nurture Newcomers (NN) OF_ Preemptive Strike (PS)OF_Close the Gap - Wake up Dormant (WUD) OF_Close the Gap - Wake up Zombies (WUZ) OF_Close the Gap_ Immediate Pay Off (IPO) OF_Future Pay Off (FPO)OF_Ladder Up (LU) OF_Nurture Newcomers (NN) OF_Reward Seekers (RS) OF_Rotten Apple (RA)


In just under 10 months, Amplero machine

learning based campaigns has

generated over $9M in incremental revenue at

an ROI of 650%.

Lift To Date: $9.2 million

Margin: $7.8 million

Amplero @ Boost Mobile

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More than 650% ROI

Cum

ulat

ive

Incr

emen

tal R

even

ue L

ift


Seven Peaks Ventures

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