HOW TO SET UP FOR SUCCESS WITH PREDICTIVE ANALYTICS

https://keen.io @keen_io

WHO WE AREMaria Dumanis - @zelashoe Data Modeling Architect, Keen IO Helps enterprise customers model data that enables them to answer specific questions

Peter Nachbaur -@peternachbaur Analytics Platform Architect, Keen IO Early Vikeen, helped design and build the platform.

KEEN

: having or showing an ability to think clearly and to understand what is not obvious or simple about something. ref - Merriam Webster

WHAT IS KEEN IO?

SMART DEVICES

MOBILE APPS

WEBSITES

TEAMS

CUSTOMERS

ANYWHERE

CLOUD DATABASE + ANALYTICS APIS

events insights

page loaded ad viewed link clicked purchase completed article shared error returned video played

count sum min max

average median

percentile funnel

extraction streaming

Be proactive and not just reactive - prevent or promote outcomes

Understand HowHow will you acquire and collect the right data?

How will you analyze and transform it to be used with predictive models?

Champion - You need to ensure that you have someone on your team that understands why you are doing what you are doing and will enable you to do what you need to do

Stakeholders - You need to understand who your stakeholders are to ensure that they can voice what type of information they need to make informed decisions

Diverse Team - You need to have a team with various domain expertise to ensure that the many components that allow you to perform analytics can interact with each other

Creating a Team

Know what data can be collected

Architect the model to provide you answers to your questions

Optimize query performance

Performance is Important

Data ModelingTracking Signups

• User Ids, Geolocation, User Referral, Acquisition Cost, Cohort

Tracking Page Shares

• Cookie IDs, Shared URL, Topic Tag

Video Plays

• Duration watched, Time of Day

Know Your ToolsKeen is great at modeling event data over time

Relational DBs are great for capturing the present state of entities

Hadoop is great for joining and crunching Keen and Relational DBs together

Deciding which analytics tool/API to use

Combining data from various data sources

Maintaining data integrity and minimizing duplication

Sending data as soon as it’s available

Understanding data privacy and who is allowed to access it

Enriching data if needed/possible

Scaling to accommodate business/product growth

Enabling integration with previously collected data

Collection Challenges

Once you have all this event data,

then what?

Figure out what the data is already telling you.

Agree on your business problems.

Identify how a specific prediction could help.

Be sure to define success.

Build a pipeline to feed your predictive algorithm.

Unleash the beast!

Iterate, iterate, iterate.

With great power comes great responsibility…

Predictive Analytics cannot exist in a vacuum.

Peter Nachbaur Analytics Platform Architect pwn@keen.io @PeterNachbaur

QUESTIONS?

Maria Dumanis Data Modeling Architect maria@keen.io @zelashoe