We live in an age where context is critical to building relationships with your customers. And many of us use marketing automation tools that can target groups/segments. But machine learning allows you to go one step further and deliver uniquely personalized content, messages and offers to each and every one of your customers — and do it on a massive scale.

1. Unleashing the power of
web scale personalization.
MACHINE LEARNING
MAKES YOU MORE HUMAN

2. TODAY’S ROADMAP
1st
half:
● Quick review - What is machine learning?
● Putting ML into marketing terms
● Comparing ML marketing against other options
● Current & near-future examples
2nd
half:
● Build a personality analysis service

3. WHY IT’S IMPORTANT
● “Smart” is coming, ready or not
● Machine learning is here and its impact on our lives is
only going to grow
● It’s a paradigm shift — Seems strange that we would
now have access to these “out-of-reach” tools
● It’s much easier than you think
● And it will quickly become the norm
● Now is the time to jump in, ahead of the curve

4. WHAT IS MACHINE LEARNING?

5. PATTERN RECOGNITION
Finding patterns in data.
So we can apply that pattern to other data.

6. FOR EXAMPLE...
Identify the pattern in
buying habits of women
who just became pregnant.
Locate that pattern in
others and target them
with special offers for
pregnancy products.

7. Will the current app user buy “maternity clothes” now?
BREAKING IT DOWN
is female?
is age
> 20?
is Y app
installed?
is X app
installed?
end
has used <
30 days?
was X
function
used?
was Y
function
used?
no
yes
no
yes
no
yes
no
yes
end no
77.1%
yes
end
probably
52.3%
93.6%
2.3%
15.8% 23.4%

8. WHY NOW?
The expensive and complicated
machine learning systems Target
had back in 2012 are cheap and
simple today.
And you have easy access to
them.
businessinsider.com/the-incredible-story-of-how-target-exposed-a-teen-girls-pregnancy-2012-2

9. OUR JOURNEY

10. THE PROBLEM WE’LL TACKLE
One of the biggest challenges we face as marketers is
how to personalize messaging to individual prospects
and customers so that it most strongly resonates with
each unique recipient.

11. TODAY’S THEME
Machine learning makes your business more human.

12. AND WHAT MAKES US HUMAN?
Empathy.
The ability to understand and
share the feelings of another.

13. boagworld.com/usability/adapting-empathy-maps-for-ux-design

14. BUILDING RELATIONSHIPS

15. “The goal of a company is to have customer service
that is not just the best but legendary.”
~Sam Walton
Founder, Walmart

16. RELATIONSHIP IS END-TO-END
“You can always find out the true nature of
a business by simply asking for a refund.”

17. RELATIONSHIPS 101
Listen to what they say,
Become an expert in who they are, and
Find ways to make their life better.

18. HOW DOES MACHINE LEARNING
FIT IN?

19. IT’S A QUESTION OF SCALE
Building deep meaningful relationships
takes a lot of work.
As human beings, we can only build great
relationships with a handful of people.
But machine learning can amplify that effort so you
can build great relationships with millions.

20. FOR EXAMPLE...
Pick one of your customers.
Read every piece of content they’ve ever put out — every blog
post, tweet, facebook update, Instagram image, etc.
How well would you know them? Pretty damn well — you
understand them and can share their feelings.
That’s empathy.
And how well do you think you could market to them now?

21. Machine learning is an amplifier.
It allows you build empathy at a scale and depth that is
simply beyond human capabilities.
● Model the habits, likes, dislikes and values of your
customers, then
● Predict the behavior of those customers and
personalize their content accordingly
NOW SCALE THAT UP

22. IN EFFECT...
Computers can dig deeper and personalize at a larger
scale than humans are capable of.
This allows machine learning-powered brands to
develop deeper relationships — with more customers
— than previously possible.

23. BACK TO MESSAGE
PERSONALIZATION

24. CRAFTING MESSAGES
Today, we’ll talk about 3 different options…
● Old school — very limited
● A better way — somewhat limited
● The machine learning way — sky’s the limit
Plus, some examples from the near future.

25. OLD SCHOOL

26. HOPE & A PRAYER
Deliver one version of
your message and send
it to every recipient at
the same time.
Hope they like it.

27. VERY LIMITED
● No personalization, eg. “Hi, you”
● Written for everyone, connects with no one
● Single delivery time, opens will be stroke of luck

28. A BETTER WAY

29. MULTIPLE FLAVORS
Deliver multiple variations
of your message and
randomly distribute them
across every recipient at
the same time.
Determine which variation
performs the best — use it
next time.

30. GETTING WARMER
● Basic personalization, eg. “Hi, Sam”
● Everything is reactive — after the action has been
taken (and after you spent the $)
● Minimal access to underlying motivation factors
● Have to create multiple versions of same asset

31. THE MACHINE LEARNING WAY

32. INDIVIDUAL FLAVORS
Deliver personalized
variations of your
message for each and
every recipient. Sent at
ideal time for each
recipient.

33. A PARADIGM SHIFT
PredictOptimize vs.
React to signals
Start with guesses
Shape behaviors
Start with models
Up to now, marketers have focus on “optimizing” their campaigns.
With machine learning, we can now shift to “predicting.”

34. Behavior
Prediction
Interest
Tracking
PREDICTIVE PERSONALIZATION
Pages & content they’ve visited
Emails they’ve opened/clicked
Resources they’ve used/downloaded
Products they’ve viewed/wishlisted/bought
Searches they’ve made
Blog
Store
Find patterns Determine what they want to
see/do/buy next (and when)
Days/time they’re active App
Search
Devices they’ve used (& geo location)
Email
Social
• Recommended posts
• Recommended products
• Delivery day/time
• Dynamic content
• Related posts
• Sales offers
• Related products
• Cross/up sell
• Dynamic pricing
• Dynamic content
• Sales offers
• Functionality
• Query suggestions
• Results ranking
• Sales offers
• Content curation
• Delivery day/time
• Retweet/reshare
Tribe
• Recommended topics
• Topic curation
• Member introductions
Your
customer

35. PEOPLE LIKE PERSONALIZATION
● 69% of consumers believe a brand's consistency across channels
affects their loyalty
● 59% of consumers who have experienced personalization believe it
has a noticeable influence on purchasing
● 67% of consumers who have experienced personalization are highly
in favor of personalized coupons
All of these are strong points for machine learning-based marketing.
infosys.com/newsroom/press-releases/Documents/genome-research-report.pdf

36. WHY IT ROCKS
● Unique personalization, eg. “Hi, Sam — we noticed
that you were searching for...”
● Can fine-tune content per individual person
● Demonstrates genuine empathy for customers
● Driven by computers (faster, cheaper)

37. EXAMPLES

38. PERFECT MATCH
A quick note…
Computers are very good at doing the boring,
monotonous tasks people don’t like to do.
Tasks that can build billion dollar companies.

39. PRODUCT RECOMMENDATIONS
techblog.netflix.com/2012/04/netflix-recommendations-beyond-5-stars.html
templates.prediction.io/PredictionIO/template-scala-parallel-universal-recommendation

40. SENTIMENT ANALYSIS
keyhole.co
ibm.com/smarterplanet/us/en/ibmwatson/developercloud/tone-analyzer.html
templates.prediction.io/pawel-n/template-scala-cml-sentiment

41. AUTOMATED CAPTIONS
“A group of young
people playing a
game of frisbee.”
Automatically
create contextual
descriptions of
your images for
accessibility.
io9.gizmodo.com/computers-wrote-the-caption-for-this-photograph-and-ch-1660450610

42. TRANSLATION
Write your message
once, have it be
delivered in multiple
languages through
automated
translation.

43. PERSONALIZED CONTENT
Deliver blog posts
and other content,
uniquely
personalized for
each customer.
techcrunch.com/2016/04/21/facebook-news-is-new

44. PREDICTING CHURN
Monitor for signs that
a customer may bail.
Then deliver targeted
messages and
promotions to retain
them.

45. PREDICTIVE SEGMENTATION
Dynamically group
recipients based
on interests,
actions, etc.

46. LIFETIME VALUE FORECASTING
LTV - arguably, the single
most important metric
for marketing.
Forecasting the profit —
or value — your business
will gain from its entire
relationship with a
particular customer.
10xnation.com/customer-lifetime-value
Customer
Group
Retention
time
Transaction
Value
Transaction
Frequency
CLV
Young
Mothers
60 months $10 1 $600
Teenagers 24 months $10 1 $240
Single
Parents
48 months $12 1 $576

47. WRAPPING IT UP

48. NET IT OUT
The better you know your customers...
The better your marketing will be…
The better your customer relationships will be...
The more customers you'll have...
The more successful your business will be.

49. AND...
Machine learning amplifies your relationship-building
skills to levels beyond human capabilities.

50. WHAT ARE YOUR THOUGHTS?
Machine learning makes your business more human.

51. UNLEASH YOUR BUSINESS
EMBRACE EXPONENTIAL
10xnation.com