why your product needs an analytic strategy

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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

“Impa

ct &

Effo

rt”

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


Value of Analytics – Visual Differentiation A table of information…


Value of Analytics – Visual Differentiation 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

DashboardsReporting

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

“Impa

ct &

Effo

rt”

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

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