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ANALYST INSIGHT

GoodData’s Role in the Next Era of Analytics: Data Monetization

Published: October 2015 Report Number: A0192

Analysts: James Haight, Research Analyst;

Hyoun Park, Chief Research Officer

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What You Need To Know

An emerging stage of maturity for enterprise analytics is the act of data

monetization. Companies are recognizing the opportunity to identify

aspects of enterprise data that can translate into an ongoing and

revenue generating product or service. This is manifest both as

extensions of current services as well as net-new services.

In Blue Hill's interviews and research, we have identified GoodData as

a business intelligence (BI) vendor that has consistently supported the

complexities of data monetization as both a market leader and as a

pioneer. The genesis of these capabilities stem from GoodData’s roots

as a cloud-based analytics distribution platform for both

enterprise-wide analytics environments and for OEM analytic

environments where GoodData supports analytics at scale for a variety

of enterprise-grade applications.

For organizations that move beyond viewing data as just a source of

insight and take the next step to use data to directly drive revenue,

there is an opportunity to further the return on their analytics investments.

Understanding Data Monetization

Data monetization is a multi-step process to translate enterprise data and analytics into new products and

services. Blue Hill has studied a number of organizations that have successfully turned their internal data assets

into an outward-facing offering that provides both additional value to their clients and new revenue streams to

their firm. In identifying opportunities for data monetization Blue Hill observes the following steps taken by

successful organizations:

1. Identify your data assets, and assess which audiences would find value in these assets. Audiences could

be external, like customers, or internal, like branches or agents.

2. Define the ideal persona who would use the results of this data.

AT A GLANCE

Data Monetization

By taking a broader view of their data, organizations should move from merely exploiting the insights contained within their data to using it directly in product and service offerings. Organizations should consider the new role of the data publisher, whose responsibility is to productize and package data to use in existing or net-new products and services.

Business Opportunity

As organizations continue to place emphasis on a data-driven approach to business, there is an opportunity to monetize data assets to clients or other partners hungry for deeper insights.

Copyright © 2015 Blue Hill Research Page 2

ANALYST INSIGHT

3. Define your productization and presentation strategy. Is your intention to improve partner relationships

and drive loyalty? Or to increase Lifetime Value and reduce churn? Or is there indeed a product

development opportunity?

4. Identify how the analytic solution will evolve over time. Will you integrate new source data, or offer

data-discovery features to clients or create comparative benchmarks to motivate behavior? Assume that

you will iterate often.

5. Confirm security and data privacy requirements?

6. Start small, and work towards growing and compounding successes.

After an opportunity is identified and the initial groundwork is laid, organizations must move forward with

executing on their strategy and supporting its expansion. This includes the following processes:

Educate targeted personas on the use, security, value, and availability of data and analytics services

Train these personas on the use and value of these services

Develop segments and pricing models for data and analytic-guided services, and potentially, access to the

data itself

Build sales and support infrastructure to sell and deliver new service

Iterate either on a supply-side basis as new data services and analytic capabilities become available or on the

demand side as personas seek additional data-driven guidance and services

To develop this process, companies have to look at enterprise data in a new light. Rather than think about BI

developers or analysts, enterprises need to consider a new role: that of the data publisher. Like a content

publisher or product manager, the data publisher is tasked with unleashing the value of internal enterprise data.

However, the data publisher needs to be comfortable both with the early stages of data definitions, requirements,

security, and governance and the latter product-based aspects of data monetization.

GoodData’s Road to Support Data Monetization Strategies

Founded in 2007 by Roman Stanek, GoodData currently has around 300 employees and over 40,000 clients. Over

the past eight years, GoodData has grown from a cloud option for horizontal business intelligence reporting and

specialist for sales and marketing analytics use cases, to a top vendor for OEM analytics and data.

To reach this point, GoodData had to take on multiple challenges. First, GoodData had to sell cloud-based

business intelligence at a time when there was still considerable concern about putting sensitive enterprise data in

the cloud. Although today this concern has been largely eased between the rise of Salesforce and cloud

infrastructure vendors such as Amazon and Microsoft, the reliability and security of putting enterprise data into

the cloud was a tough question for CIOs in 2007. However, this allowed GoodData to be an early leader in

mastering cloud security measures such as integrated single-sign on for identity management and data

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ANALYST INSIGHT

encryption both at rest and in transit as well as offering benchmarking analysis between customers on their

shared infrastructure.

The second challenge that GoodData had to overcome was breaking through the 15-20% adoption rates that are

standard across internal BI deployments. Otherwise their scalable cloud-deployment model would be

under-utilized. This challenge meant that GoodData had to create a valuable and engaging analytics experience

for line-of-business employees beyond just those formally trained in BI. They needed to create a solution that

supported easy implementations, upgrades, and configurability for clients, so that clients could make critical

business decisions.

Third, GoodData had to evolve past the market of providing departmental analytics and take on the OEM

white-label BI market. This area saw considerable competition from veteran BI vendors such as MicroStrategy,

Information Builders, Actuate (now OpenText Analytics), Jaspersoft (now owned by Tibco), and Pentaho.

To support all of these demands, GoodData had to become a truly cloud-based solution. The company needed to

provide a one-to-many experience where GoodData could simultaneously update its BI platform on a bi-weekly

basis to maintain a competitive advantage while maintaining stable functionality for a wide variety of OEM

clients and providing the customization necessary to support each one. At this point, GoodData has shown its

ability to support over 50,000 different customer environments on a single and consistent analytic platform.

Through this evolutionary process, GoodData has developed a cloud-based business intelligence and analytics

platform that supports a wide variety of enterprise data environments while providing a great deal of flexibility.

At the same time, the business world is moving towards a world of ‘Moneyball’ as emphasis is placed on

data-driven business insights and data is used to support assets or services or to be directly provided as a service

in and of itself. In effect, this combination of cloud-scale analytics, personalization, and focus on cloud-based

business models has made GoodData an expert provider in a new, emerging practice: BI for data monetization.

GoodData's Role in Supporting Data Monetization

One of the basic rules of business is that a successful endeavor requires the right people, processes, partners, and

tools. To support the multi-skilled role of the data publisher and the multi-stage process of data monetization,

companies must choose appropriate partners and toolkits designed to support these people and processes.

Blue Hill notes that GoodData has experience in monetizing data across a wide variety of industries. In

supporting highly scalable, highly personalized, and branded analytic environments, GoodData has supported

over 300 different embedded product implementations, which has led to a strong skillset in developing and

supporting the analytic framework for new products.

Although high-revenue and high margin industries such as financial services, healthcare, and insurance present

significant opportunity to unlock valuable data, there is a broad spectrum of use cases that can contribute to

meaningful impacts. For example, Blue Hill has also seen GoodData's success in supporting specific customers

across a diverse set of industries such as Marketron in the media industry, ServiceChannel in the retail and

restaurant industry, and Mindflash in the corporate training industry.

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ANALYST INSIGHT

Blue Hill Recommendations

For executive management: Create a strategy for identifying organizational data that matters either to your

customers or your industry. Consider the potential value of using this data either to actively guide internal

business activities or to provide new services to clients for improving customer retention and overall customer

lifetime value. Every customer, product, asset, and service produces data of some sort. For all the money that has

been spent on business intelligence, databases, and data integration, very few resources have been put into

actually translating all of that data into the two outputs that truly drive business growth: top-line revenue

opportunities and bottom-line total cost of ownership. This opportunity exists to optimize existing products and

services, streamline existing processes, and to create new externally facing products.

For IT, analytics, and data management personnel: Those seeking to take the next step in their careers up the

CIO or CTO office need to understand data monetization. The first half of this job is firmly in the traditional realm

of IT, but the second half of value identification, pricing, product development, and product iteration may be new

concepts for those who have focused on either architectural design or operational support. Nonetheless, analytic

pros own the first half of the data monetization skillset and will be needed as companies move past the hype of

"data-driven" decisions and towards a reality of maximizing the value of enterprise data. This means both to

understand the data tools available and to know the partners and resources available to support a full range of

data monetization capabilities.

For product and revenue professionals: Data monetization isn't as easy as just putting a price tag on existing data

and going out and selling it. Often, the true monetization of data occurs in enhancing existing services or by

creating an appropriate data infrastructure based on new data sources, integration, analytics, and guided

visualizations that have not traditionally been in your organization. Don't ignore the analytic side of data

monetization in rushing to become the next Data-as-a-Service or data-enhanced, next-generation product. It's easy

to create a dashboard and call it "Big Data" or "Analytic Insight," but true insights require a well-considered data

supply chain that goes from secured and curated sources to data aggregation to metadata definitions to analytics

to guided end user data discovery. If any of these parts are missing, the data monetization value chain is broken.

Conclusions and Key Takeaways

To strategically prepare for the future, companies must learn how to effectively monetize their data. To do so, it is

not good enough to simply put data and analytics tools in place: nearly every organization has already done this.

It is far more important to develop a scalable way to support every employee, customer, partner, and product as

the Internet of Things will increasingly require every object to have its own centralized data used to enhance

customer experiences. Companies that look for quick fixes that are not highly configurable and have not

supported the level of data traffic needed to sustain regular business transactions will ultimately be at a

disadvantage in the race to data supremacy that all companies now face. Based on over 300 actual examples of

data monetization, a cloud-based analytic platform, and the proven ability to support a vast array of both

generalized and specialized business models, Blue Hill recommends GoodData as both a market pioneer and

market leader in the emerging era of data monetization.

Blue Hill Research is the only industry analyst firm with a success-based methodology. Based on the Path to Success, Blue HillResearch provides unique and differentiated guidance to translate corporate technology investments into success for the three keystakeholders: the technologist, the financial buyer, and the line of business executive.

Unless otherwise noted, the contents of this publication are copyrighted by Blue Hill Research and may not be hosted, archived,transmitted or reproduced, in any form or by any means without prior permission from Blue Hill Research.

For further information or questions, please contact us:

ABOUT THE AUTHOR

Hyoun ParkChief Research Officer

Phone: +1 (617)624-3600Fax : +1 (617)367-4210

Twitter: @BlueHillBostonLinkedIn: www.linkedin.com/company/blue-hill-research

Contact Research: research@bluehillresearch.com

Copyright © 2015 Blue Hill Research www.bluehillresearch.com

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@hyounpark

www.linkedin.com/in/hyounpark

bluehillresearch.com/author/hyoun-park/

Hyoun Park is the Chief Research Officer of Blue HillResearch where he oversees day-to-day research

operations, delivery and methodology focused on vendorand technology selection. In addition, Park covers

analytics and enterprise mobility technologies as a notedadvisor, social influencer, and practitioner. Park has been

named as a top 10 Big Data, analytics, and mobilityinfluencer including quotes in USA Today, the Los AngelesTimes, and a wide variety of industry media sources. Over

the past 20 years, Park has been on the cutting edge of web,social, cloud, and mobile technologies in both startup and

enterprise roles. Park holds a Masters of BusinessAdministration from Boston University and graduated with

a Bachelor of Arts in Women's and Gender Studies fromAmherst College.

James Haight is a research analyst at Blue Hill Researchfocusing on analytics and emerging enterprise technologies.

His primary research includes exploring the business casedevelopment and solution assessment for data warehousing,

data integration, advanced analytics and businessintelligence applications. He also hosts Blue Hill's Emerging

Tech Roundup Podcast, which features interviews withindustry leaders and CEOs on the forefront of a variety of

emerging technologies. Prior to Blue Hill Research, Jamesworked in Radford Consulting's Executive and Board ofDirector Compensation practice, specializing in the hightech and life sciences industries. Currently he serves onthe strategic advisory board of the Bentley MicrofinanceGroup, a 501(c)(3) non-profit organization dedicated to

community development through funding and consultingentrepreneurs in the Greater Boston area.

Blue Hill Research is the only industry analyst firm with a success-based methodology. Based on the Path to Success, Blue HillResearch provides unique and differentiated guidance to translate corporate technology investments into success for the three keystakeholders: the technologist, the financial buyer, and the line of business executive.

Unless otherwise noted, the contents of this publication are copyrighted by Blue Hill Research and may not be hosted, archived,transmitted or reproduced, in any form or by any means without prior permission from Blue Hill Research.

For further information or questions, please contact us:

ABOUT THE AUTHOR

James Haight

Analyst

Phone: +1 (617)624-3600

Fax : +1 (617)367-4210

Twitter: @BlueHillBoston

LinkedIn: www.linkedin.com/company/blue-hill-research

Contact Research: research@bluehillresearch.com

Copyright © 2015 Blue Hill Research www.bluehillresearch.com

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@James_Haight

www.linkedin.com/in/jamesthaight

bluehillresearch.com/author/james-haight/

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