Recording of Justin Royer, April Seifert, and Tres Tronvold (Sprocket) presenting at Twin Cities Product Conf 2019.

1. 5 Principles:
using data science to create
great (human) experiences

2. A hearty welcome from
your friendly Sprocketeers.
Tres April Justin

3. We’re a data-loving
growth strategy firm. Using
analytics and imagination, we
help our clients:
1. Better understand their customers
2. Capture more value from existing customers
3. Innovate and grow in new ways

4. What the hell is data science, anyway?
The art of using data to drive
decisions, inform and power
processes, and enable
businesses to grow and move
forward intelligently.

5. Data Science + CX. The time is now.
1. It is no longer acceptable to not be a
‘data person.’
2. Companies who don’t fully exploit the
value of data will be at a severe
competitive disadvantage.
3. Most importantly, data is digital exhaust
from human behavior and a
human-centered lens unlocks its potential.

6. LET’S GET TO WORK

7. Jargon check.
Persona
Journey map
Machine learning
Natural Language Processing
"How might we" question
Beer

8. Introducing the 5 Principles.
1. Begin with humans and their needs
2. Context is critical
3. Make the experience more personal, easy,
and enjoyable
4. Don't leave customer value the table
5. You can’t analyze your way into the future

9. Let’s learn about the 5 principles
by talking about BEER.
LAKEBOARD
BREWING CO.

10. Principle 1.
Begin with humans and their needs.
• All good product experiences begin with
human needs
• Blend qualitative understanding with
available data and unsupervised machine
learning to paint a picture of your
customers/users
• Example persona template in your packet

11. 1. GOALS
2. NEEDS
3. BEHAVIORS
4. DESCRIPTORS

12. Qualitative insight, descriptive analysis, and machine
learning help you understand groups of customers/users.
Qualitative insight
Discover goals, needs, and
motivations. Gain deep
understanding of why
people do what they do.
Quantitative insight
Define “to what degree”
customers have certain
goals, needs, and
motivations.
Machine learning!
Let the machines help us find
patterns and like groups of
customers.
Personas
Research-based descriptions
of different customer types
with like properties.
+ + =

13. 13
deal making dana.
beer makes for good business.
60% Male
35-54 y/o
6+ annual occasions
“Sometimes business is done in the
boardroom, no doubt, but more often
deals get inked when everyone is relaxed.
Beer takes the edge off when the SOWs
come out.”
Job-to-be-done:
• Build relationships and advance business deals during the
course of a work week
Defining behaviors:
• Has 2-3 top breweries and bars he conducts business in
• Sometimes rents a room if hosting larger groups
• May go to breweries on the weekend, but primary day
parts are after work during the work week
Food options
Beer taste
EnvironmentKid friendly
Trendy

14. Natural language processing (NLP)
+
Machine Learning
=
Qualitative insight at SCALE

15. Let’s look at Facebook Portal.

16. We (politely) asked the machines to find us
10 clusters of positive and negative reviews.

17. 17
Here are three of the clusters
about particular features.
Easy integration with
Messenger
12%
“But this whole thing works so well for
my family because it's built on top of
Facebook Messenger.”
“Since practically everyone has
Facebook it's easy to get in touch
with people.”
Alexa is integrated.
11%
“Alexa works well on this device until all
three of my kids begin yelling
contradictory orders or random questions
at once, which makes Alexa shut down
(and I don't blame her).”
“It also makes it easy to have Alexa
already connected.”
High quality video calls.
25%
“The camera and video quality was
smooth and sharp.”
“Great camera follows you real
well.”
“It delivers great video and sound
quality.”

18. 18
wanted to do our own installation in our current home
wanted to change to a cellphone type system
wanted to feel a little safer
wanted to expand my system
wanted one that's updated
wanted a system that we could take with us
wanted to move and Frontpoint is wireless
wanted something that had mobile capabilities
wanted a temperature sensor and a smoke detector
wanted something a little more modern
wanted to add elements to the system
wanted to make sure that we got a good experience
wanted to have a home security because I was moving
wanted to go cellular
wanted to have a more up-to-date system
wanted the police to be notified immediately
Natural language processing and
JTBD are meant for each other.

19. Now back to Dana (and beer).
Check out what people are
saying about LakeBoard.

20. Principle 2.
Context is critical.

21. Principle 2.
Context is critical.
Plus up journey maps:
• Natural language processing of
online reviews
• Quantification of surveys and
existing analytics

22. Principle 3.
Make the experience more personal, easy, and enjoyable. (exercise)
1.Grab Dana’s persona, journey
map, and natural language
processing (NLP) results
2.Using post its, ideate 3 ways to
make the experience more
personal, easy, and enjoyable

23. Principle 4.
Don’t leave customer value on the table.
Think from BOTH a customer and
a commercial standpoint to
identify opportunities to make
the cash register ring.
• Connect personas with
transactional behavior
• Specify and quantify incremental
behaviors
• Avoid accidental beneficiaries

24. Principle 5.
You can’t analyze your way to the future.
Start creating the future!
• Innovation involves risk
• Mesh data with creativity
• Use our Experiment & Learn Sheet
to define an experiment now!

25. Start with a hypothesis…what do
you believe?
Define your experiment…what
will you do to test?
What metrics will you measure?
What does success look like?

26. sprocketcx.com/experiment

27. 5 Principles in Review.
1. Begin with humans and their needs
2. Context is critical
3. Make the experience more personal, easy,
and enjoyable
4. Don't leave customer value on the table
5. You can’t analyze your way into the future

28. Hit us up.
sprocketcx.com/FivePrinciples
hello@sprocketcx.com
@SprocketCX

29. That was fun.
Let’s do it again soon.
sprocketcx.com