Creating a Single Source of Truth

Leverage all your data with powerful analytics in days, not months.

&

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

Meet the speakers

Erin FranzSenior Analyst, Alliances

Looker

Kevin NiparkoProduct Lead, Warehouses

Segment

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

Segment is your customer data hub.

Analytics

A/B Testing

Live Chat

EmailMarketinCRM

Customer

Support

Website

App

Analytics

EmailMarketing

MobileAdvertisi

ngAnalytic

s

Customer

Support

CRM

Analytics

Customer

Support

Server

Which means traditional integrations are complex and costly.

Before Segment...and after.

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

Segment Warehouses Product Overview

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

Data lives in many different places within your org.

Customer Events Transactional Data Third-Party Silos

website Mobile Server Server Server

Examples

SignupSong PlayedSubscription Started

InvoicesDeliveriesOrders

InventoryCRMCustomers Table

Decreasing cost of cloud technologies

https://aws.amazon.com/redshift/

Productization of the data pipelineWithout Segment

With Segment

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-hostedBYODB – 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

Tools that reduce time-to-insight

Dynamic schema | Tables for each event | Looker Blocks

Looker for Segment Warehouses: An OverviewFind, explore and understand all the data

Explore EverythingFind, explore and

understand all the data

Create StandardsDefine metrics with

Looker Blocks

Any SQL DatabaseAnalyze all of your data in Segment Warehouses

Build a Data CultureAnyone 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?

What makes Looker different?

100% In Database

Leverage all your dataAvoid summarizing or

moving it

Modern Web Architecture

Access from anywhereShare and collaborate

Extend to anyone

LookML Intelligent Modeling Layer

Describe the dataCreate reusable and

shareable business logic

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

+

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!

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.

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.

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

Let’s See The Demo!

Q & A

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.

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