With a centralized data store, the entire spectrum of analytics is at your fingertips. Using Looker & Segment, you can collect, store and analyze everything from click-stream and event data to transactional and behavioral data in your data warehouse. Some of the topics this webinar will include: -The advantages of a centralized data warehouse with Segment Warehouses -Creating a data model to get your company on the same page with Looker Blocks -Putting it all together: Best practices for making your data accessible to your end users

1. Creating a Single Source of
Truth
Leverage all your data with powerful analytics in days,
not months.
&

2. Housekeeping
• We will do Q&A at the end.
• You should see a box on the right
side of your screen.
• There is a button marked “Q&A” on
the bottom menu.
• We will be recording this
• We will send you the recording
tomorrow.
• We will also send you the slides
tomorrow.
RecordingQ&A
Tweet about this webinar using
#sourceoftruth

3. Meet the speakers
Erin Franz
Senior Analyst, Alliances
Looker
Kevin Niparko
Product Lead, Warehouses
Segment

4. Agenda
Creating a data model to
get your company on the
same page with Looker
Blocks
Q & A:
We will answer as
many as possible in the
time that is left.
1
3 4
2The advantages of a
centralized data
warehouse with Segment
Warehouses
Putting it all together: Best
practices for making your data
accessible to your end users

6. Segment is your customer data hub.
Analytics
A/B Testing
Live Chat
Email
MarketinCRM
Customer
Support
Website
App
Analytics
Email
Marketing
Mobile
Advertising
Analytics
Customer
Support
CRM
Analytics
Customer
Support
Server

7. Which means traditional integrations are complex and costly.

8. Before Segment...and after.

9. Now you don’t have to maintain a “spaghetti" of integrations.

10. Segment Warehouses Product Overview

11. Why do I want a data warehouse?
Increasing reliance on multiple data sources
Decreasing cost of cloud-storage options
(Redshift)
Productization of the data pipeline
Tools that democratize data access

12. Data lives in many different places within your org.
Customer Events Transactional Data Third-Party Silos
website Mobile
Server Server Server
Examples
Signup
Song Played
Subscription Started
Invoices
Deliveries
Orders
Inventory
CRM
Customers Table

13. Decreasing cost of cloud technologies
https://aws.amazon.com/redshift/

14. Productization of the data pipeline
Without Segment With Segment

15. Choose the best option for your company
● Saves companies engineering time
on maintaining databases.
● We provision their cluster with correct
security and permissions.
● Resize when disks get full.
● Vacuum to keep queries fast.
Previously Segment SQL
Segment-hosted
BYODB – Bring your own database
● Great for large companies already
managing data warehouses.
● Can join in any internal data they
already collect.
● Have complete control and visibility
into their clusters.
Customer-hosted

16. Tools that reduce time-to-insight
Dynamic schema | Tables for each event | Looker Blocks

17. Looker for Segment Warehouses: An Overview
Find, explore and understand all the data
Explore Everything
Find, explore and
understand all the data
Create Standards
Define metrics with
Looker Blocks
Any SQL Database
Analyze all of your data in
Segment Warehouses
Build a Data Culture
Anyone can ask and
answer questions
How is pipeline
for Q4?
Will we meet
our revenue
targets?
Which
campaigns
convert best?
Which rep is
converting
best?
Which customer
is at risk?
Can we speed
up our
operations?

18. What makes Looker different?
100% In Database
Leverage all your data
Avoid summarizing or moving it
Modern Web Architecture
Access from anywhere
Share and collaborate
Extend to anyone
LookML Intelligent
Modeling Layer
Describe the data
Create reusable and shareable
business logic

19. Looker Blocks for Segment
Universal User Id
Map disparate user
identifiers to track user
behavior
Session Creation
Define periods of
user activity for
analysis
Custom Modeling
Build on sessions in
LookML to capture desired
metrics
Explore!
Drill into and visualize
results to answer
questions
+

20. Building on Universal User ID Mapping
Track Users Over a
Visit
Consolidate Anonymous Ids
and User Ids
Cross Platform
Analytics
Consolidate Identifiers Across
Multiple Device Types
Track Users Over Time
Consolidate Identifiers Across
Many Visits
… then use this mapped user id to create sessions!

21. Creating a Session
Some metrics can come directly from events:
• Count of event types
• Event types over time
But generally, we care more about a user’s visit to a website/application. In
order to create visit metrics we need to create a session.
A session is simply a group of interactions that take place on a
website/application within a given time frame.

22. Example Session Design Pattern
Assuming we’ve already mapped events to users, we can find the difference in
time between each event using the below query:
Once we have that value we can set how much inactivity is necessary to
terminate a session, and begin a new one.

23. Building Sessions Unique to a Business
Custom Session Examples
● Longer or shorter time out window
● Sessions based on boundary events
● Sessions based on other metadata
Example Session Metrics
● New vs. Returning Sessions
● Bounced Sessions
● Session Duration
● Sessions by Traffic Source
● Session Funnel

24. Let’s See The Demo!

25. Q & A

26. THANK YOU FOR JOINING
Recording and slides will
be posted.
We will email you the links
tomorrow.
See you next time!
Next from Looker Webinars:
Driving Data Democracy:
Hadoop & Redshift with
Knewton on 3/16
Learn more about Looker &
Segment
Visit looker.com/free-trial or
segment.com/signup.

27. THANK YOU!
Take the survey:
https://looker.typeform.com/to/DlG9Zm