Why Your Product Needs an Analytic Strategy

© 2014, Pentaho. All Rights Reserved. pentaho.com. Worldwide +1 (866) 660-75551
Michelle Bradbury
Director of Product Management, Pentaho
April 2014
Why Your Product
Needs a Data &
Analytics Strategy
Ben Hopkins
Product Marketing Manager, Pentaho

Pentaho
We Enable & Empower Data-Driven Businesses
Customer momentum
•  Over 1,200 commercial customers
•  Over 10,000 production deployments
Innovation through open source
•  Open, pluggable, purpose-built for the future
•  Sustained leadership in Big Data ecosystem
with technology innovation
Modern, cohesive business analytics & data integration platform
•  Full spectrum of analytics for all key roles
•  Embeddable, cloud-ready analytics
•  Broadest and deepest Big Data integration

Thinking about Analytics & Products –
3 Strategic Approaches
Near Term Long Term
“Time”
2 - Target new
opportunities with
existing data
3 - Reinvent value
propositions with
new data technology
“Impact&Effort”
1 – Enhance current
software products

Enhance current products

Introductory Example

①  Value of analytics functionality in software applications
②  Understanding your analytics audience & personas
③  Implementation considerations
Enhance Current Products

•  People find pictures intuitive
•  Lets your product tell a story
•  Competitive advantage
sales can use
Value of Analytics – Visual Differentiation

A table of information…

Or a visualization to tell a story…

•  Creating unique & valuable content
•  Raises barriers to product abandonment
•  Depth of usage & loyalty
Value of Analytics –
Customization Builds Stickiness

•  Data & insight drive decisions
•  Identify opportunities for improvement
•  Understand value of the software
Value of Analytics – Better Decisions

Understanding Your Analytics Audience
Director of
Sales
Supply Chain
Manager
Vice President
of Marketing
Financial
Advisor
Head of IT
Educational
Instructor
Corporate
Recruiter
Chief Financial
Officer
Manufacturing
Operations
Manager
Social Media
Specialist
Hospital
Administrator
Marketing
Operations
Analyst
Customer
Service
Representative
Project
Manager
Advertising
Executive
Network
Engineer

Personas & Needs – “The Executive”
•  Consolidated business information at
fingertips
•  Ability to drill down 1 or 2 levels
•  Don’t lose the macro vision in details
Needs & Requirements
•  User-specific branded corporate
dashboard
Recommendation

Highly Tailored Dashboard

Personas & Needs – “Middle Management”
•  Ability to filter information to their job scope
•  More intimate knowledge of lower level
data
•  Wants both visualization & detailed reports
•  Dashboards & visualizations with filters
•  Pre-canned reports for detail
Recommendation

Visualizations & Reports

Personas & Needs – “The Data Analyst”
•  Leverages detailed data to discover trends
•  Often presents or provides data to other
users
•  Stronger technical & quantitative skills
•  Custom analysis tools for use on controlled
data sources
•  Ability to easily share analytics content
throughout the organization
Recommendation

Custom Analysis

Importance of controlling data sources & access
Going beyond standard relational application data
Seamless analytics experience for the user
Implementation Considerations

What Makes a “Normal Deployment”?
Business
Analytics
Server
Metadata
Analyzer
Dashboards
Reporting
Integration to
Multiple Data
Sources
Data
Integration
RDBMS
Big Data
Other
sources
Transactional
data
Online
Data
Multi-tenancy
Support
Seamless SSO
Authentication &
Security/Role
Integration
Embedded Analytics
Content in Existing UI
Re-skinned interface

Target new opportunities with
existing data

•  Direct data monetization
•  New products & services for new markets
•  Applied business intelligence
‘Out of box’ opportunities to provide value
Business Model Innovation with Your Data

Gartner on data monetization:1
•  “By 2016, 30% of businesses will have begun directly or
indirectly monetizing their information assets via bartering or
selling them outright ”
•  “Start building information product manager skills and analytical
competencies in your organization.”
•  “Large retailers place their point of sales (POS) and other store
promotion data online for their business partners to subscribe to.”
Direct Data Monetization Opportunities
1.  From Gartner research report – “How Organizations Can Monetize Customer Data,” Analysts: Olive Huang, Douglas
Laney; Published 6 March 2014

“Monetize” Use Case
What is it?
•  Provide enriched internal data sets as service to external
customers & partners
•  Leverage internal sources like sensor, location, & activity data –
and combine with external sources as well
Why do it?
•  Generate new sources of revenue by leveraging diverse data
•  This can provide intelligence to other industries, delivering better
understanding of customers & markets

Example - Telecom Company
Challenges
•  Bring together device usage data from mobile subscribers &
networks
•  Deliver value-added marketing analytics as service to 3rd
parties – including location, audience, & social insights
Benefits
•  Generating brand new revenue stream with technology
platform for controlling costs & maximizing margins

Example – Telecom Company

New product that helps retailers unlock value of data assets:
Another Example
The vendor provides an (anonymous) analytics service to
retailers on stores traffic – leveraging their existing networks
This data is already collected by wireless routers in retail
stores
Leverage rich data from the pings that smartphones send out
as they search for Wi-Fi networks

Reinvent value propositions
with new data technology

What is Big Data?
Characteristics
•  Variety
•  Velocity
•  Volume
Technologies
•  Hadoop
•  NoSQL
•  Analytical Database

Big Data is a Value Proposition Game-Changer:
Why does Big Data matter to me as a PM?
Leverage Prediction at Scale for Smarter Apps
•  Example – Run recommendation algorithms across millions of
users & pieces of content with near-instant performance
Create Products Using Diverse Data Sources
•  Example: Deliver intelligent products harnessing machine &
device data, log file data, social media data, & other
unstructured data
Future-Proof for Growth & Performance
•  Example: Solve scalability to tens/hundreds of millions of users
– i.e. why Yahoo, Facebook, Google & others created the
technology (out of necessity)

Why does Big Data matter to me as a PM?
Old Way:
Relational Only
•  Product serves a specific
functional purpose
•  Manage data in one or more
relational application database(s)
•  Application data often isolated
from other relevant data
New Way:
Relational + Big Data
•  Product is also prescriptive
regarding that function
•  Regularly ingests new data to
improve prescriptive models
•  App data is blended with multiple
other data sources, expanding
problem-solving potential

Consumer Personalization
Optimized Brand Experiences
Product Characteristics
>  Delivers real-time personalized shopping
experiences across the web - including
recommendations, promotions, & emails
>  Customers include large brands & retailers
Application Intelligence
>  Rebuilds webpages based on
aggregate consumer models &
recent individual behavior
>  Learns adaptively & adjusts product
recommendations up to 12x a day
Underlying Technology
>  Hadoop & related technologies, as
well as NoSQL for unstructured data
>  Advanced predictive modeling
>  Real-time infrastructure returns API
calls in milliseconds

GigaOm on Internet of Things:1
•  Synapse is creating a cloud platform
for data processing & analysis,
including real-time events
•  Their distributed architecture is similar
to that of consumer web companies,
like Netflix
•  Sample use case – Sensing whether
or not hospital workers wash hands
Sensor Analytics & Big Data
1.  From GigaOm: “Why the internet of things is big data’s latest killer app — if you do it right”, by Derrick Harris, 3/4/2014

Netflix
Architecture
(compared to Synapse)
From GigaOm: “Why the internet
of things is big data’s latest killer
app — if you do it right”, by
Derrick Harris, 3/4/2014

①  Check with your counterparts in Operations & Engineering to see if
your organization is using or planning to use Big Data technologies
②  If you are building a new product or company, evaluate whether a Big
Data architecture would be a good fit
③  Monitor how leading consumer & B2B applications are leveraging
these technologies on an ongoing basis
Big Data: So what can I do today?

Conclusion

Wrap-up: The 3 Approaches Reiterated
Near Term Long Term
“Time”
2 - Target new
opportunities with
existing data
3 - Reinvent value
propositions with
new data technology
“Impact&Effort”
1 – Enhance current
software products

•  How can analytics functionality meet needs for my users?
•  How can analytics create business & competitive benefits for my
organization?
•  Do I have valuable untapped data resources in my product or organization?
•  Why might Big Data technologies be relevant to my business?
Wrap-up: Things to Think About

Thank You
blog.pentaho.com
@Pentaho
Facebook.com/Pentaho
Pentaho Business Analytics
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