Turning Data Into Dollars, Presented by Zach Gemignani

Copyright © 2014 by Juice Inc.

Turning data into dollars Juice Analytics September 2014


Today’s objectives

Explain the opportunity to monetize your data

Identify your opportunities to create data products

Understand the elements involved with bringing data products to market


5 Steps to Data Monetization

1. Data as a product

2. Data meets audience

3. Designing a data product

5. Launching a data product


Schedule

Introduction and examples Notes Discuss in small group

Share with allTopic 1

15 min 5 min 5 min 5 minTopic 2

Topic 3

Topic 4

Topic 5

20 min (Update on Apple announcements)Break

20 min (optional)Examples

10mIntro


TOPIC 1

DATA as a PRODUCT



DATA is the new OIL


Raw materials Finished product


Competing on Analytics (Analytics 1.0)


Analytics 3.0: Turning data inside out

Every organization—not just online firms—can create data and analytics-based products and services that change the game

Not just supplying data, but insights and guides to decision-making

Use “data exhaust” to help customers use your products and services more effectively

Source: International Institute for Analytics


Data products vs. traditional analytics

Research report

Internal External

Static summary

Interactive

Target audience...

Delivered as...

Reporting

Dashboards

Data productsInteractive, web-based solutions sold independently or delivered as part of another solution.

Web basedFeature-rich

Solve specific problems


The Data Monetization Opportunity

(1) The big-data revolution in US health care: Accelerating value and innovation, April 2013, McKinsey & Company

In healthcare alone, there is an estimated $300B to $450B in annual cost savings that can be

achieved through data applications (1)


Types of data products

New data product

Enhance an existing data product

Revenue generating

Value add to a product/service


LinkedIn: User engagement


US News: New revenue stream


Exercise 1: Data as a product

Brainstorming data product concepts for you or your organization. For each one, describe the problem it solves.

Data product concept What problem does it solve?


TOPIC 2DATA meets AUDIENCE


Data meets audience

Data product Target audience

http://businessmodelalchemist.com/blog/2012/08/achieve-product-market-fit-with-our-brand-new-value-proposition-designer.html

http://businessmodelalchemist.com/blog/2012/08/achieve-product-market-fit-with-our-brand-new-value-proposition-designer.html


What data could help them in their role?

How can your data best serve this audience?

Who is your target audience?1

2

3


Different data for different folks

Chief Marketing OfficerMarketing Analysts


What’s this calculated metric?

Enhancing your data

3rd party data sources

Predictive modeling

Calculated metrics


Benchmarks, comparison, and context


A data readiness checklist

Do you have rights to the data?

Can the data be accessed in an automated fashion?

Is there personal data that should be obscured?

Can the data be presented at a level of summarization/granularity that the audience will find most useful?

Does the data need to be cleaned or transformed to make it useful?


Example: Predikto


Exercise 2: Data meets audience

Fill out the table for each of your favorite 2-3 data product concepts

Data product concept Who is it for? How can the

data help?Is the data

ready?How to add value

to the data?


TOPIC 3

DESIGNING your data product


What goes into the design of a product?

Self-serve, not self-solve

purposeful design leading to action fit users workflow

guidance and storytelling

form follows function

right-sized

socialize-able


Designing for action

“I’ll get right on that”“good to know”“neat”

Interesting < Useful < Actionable


Guidance and storytelling


Volume

How will they use it?


Form follows function

timeliness

aesthetic

mobility

connectivity

data detail

data density

interactivity

collaboration

functionform paper Excel online app e-mail large

screen


Socialization: reaching your audience’s audience


Example: US Chamber of Commerce


Exercise 3: Designing your data product

For your one or two of your favorite product concepts, answer the following questions:

Concept 1 Concept 2

In what form would the data product be delivered?

How does the product fit into in the user’s workflow?

What specific actions can it drive?

How can you help users share the data/insights?


TOPIC 4

Go to market challenges


Selling

Agreeing

Delivering

Supporting


Volume

Selling


Selling

How will it be sold/distributed?

What’s needed to help sell it?

How will you explain it?


Volume

Agreeing


Agreeing

Existing customer agreement or new one?

How will billing occur?

Who needs to be involved?


Volume

Delivering


Delivering

How will user receive it?

Who is delivering?

How do we make delivery successful?


Volume

Supporting


Supporting

!

Who will answer questions, comments, etc.?

How will the product be maintained?


Example: Hall & Partners


Exercise 4: Go to market challenges

For your data product concept, list your biggest or most likely obstacle or challenge. For each risk, consider potential approaches to mitigate these risks.

Challenge Mitigation strategy


TOPIC 5

Launching a data product


Volume

Pick One


“Data isn’t like kids you don’t have to pretend to love them equally.”

Amanda Cox, NY Times


Volume

Think Lean


Lean Canvas

Volume


Volume


=Have conversations


Example: The Essential Economy


Exercise 5: Launching a data product

Provide a brief description of the data product that is most promising and describe the key features that represent the minimum viable product.

Data product description

Minimum viable product features


5 Steps to Data Monetization

1. Data as a product

2. Data meets audience

3. Designing a data product

4. Go to market challenges

5. Launching a data product


About Juice Analytics

Our B2B clients (from start-ups to Fortune 500) have launched profitable products with our design and technical guidance

Design and launch data products

Fruition: Data Product Platform

Data visualization components designed for non-technical end-users

Features for sharing and collaborating on data insights and analysis

A decade of guiding businesses through the process of designing, creating and launching new data products

Recognized thought leaders

Available early November


Data Product ExamplesDataSift - licenses data from Twitter to aggregate, process and deliver social data to enterprises about their brands. ADP - provides a monthly snapshot of U.S. nonfarm private sector employment based on actual transactional payroll data Payscale.com - links individuals and businesses to the largest salary profile database in the world. Glassdoor.com - Influence job seekers at the moment they are making the decision whether or not to work for you Indeed.com - Reports for economic forecasting or stock trading models. Compete.com - compare publishers to buy the most efficient traffic Alexa.com - compare publishers to buy the most efficient traffic Quancast.com - compare publishers to buy the most efficient traffic Zillow.com - Home values (real and estimated) for all houses in US ProjectHoneyPot.org - Black lists of IP addresses or email addresses used in fraud, Botnet activity or forum spam. FICO - Selling scores, such as click scores or any other scores. FICO was one of the first companies to do so. Skift - provide you with the latest intelligence on travel trends. SuperData Research - Data-driven market intelligence on online, mobile and digital games Factual - Data on over 600,000 consumer packaged goods in a UPC centric database with ingredients and nutrition information


Additional reading1. Data Jujitsu by DJ Patil.

2. The evolution of data products by Mike Loukides.

3. John Foreman blog - MailChimp data scientist

4. Juice Analytics.com Product Manager’s Checklist

Data & Analytics

Turning Data Into Dollars, Presented by Zach Gemignani