Data as a Service (DaaS): The What, Why, How, Who, and When

Data as a Service:
The What, Why, How, Who & When

Since Software as a Service was introduced in
the 1990s, a slew of other offerings have
emerged in the “as a service” family—including
Data as a Service (DaaS).
DaaS takes on the heavy lift of making data
more accessible to users. According to the
Gartner Hype Cycle, DaaS is climbing the
familiar peak and is predicted to have some
serious staying power.
What is Data as a Service?

Data as a Service providers wrangle the
overload of information available to companies
today, and then analyze and visualize data-
centric insights.
DaaS is a healthy combination of data science,
strategy, and structure to make datasets
understandable and actionable.
Elements of Data as a Service.

The importance of operationalizing data is
something most companies no longer
question. However, many still fail to
implement data analytics because of a
lack of infrastructure (56%), expertise
(46%), and buy-in from the board (37%).
Data as a Service is the solution to
companies trying to face these challenges
alone.
DaaS Simplifies the Complex.
Network
constrained by
bandwidth
No knowledge
to analyze
and use data
Analytical
engines can’t
handle data
Board members
concerned with
the risks of data
No understanding of
how to acquire data
IT lacks ability
to design
around data
No where to put
data once
collected
No business
owner
Source: eMarketer

Improving customer experience (CX) is one of
the highest and most coveted benefits of Data
as a Service.
According to research by Econsultancy and
Adobe, 65% of respondents said that data
analysis was very important to improving
customer experiences for client-facing
marketers. 41% of B2B professionals said the
same thing.
Benefits of DaaS.
Source: eMarketer
Improve Customer Experience
Higher Revenue
Increased Customer Retention/Loyalty
More Customers
Improve Products/Services
Better Pricing Strategy
Higher Profit Margins
Higher Customer Lifetime Value
Higher ROI
Other

When we look at monetizing data fronts,
it’s about finding ways to create more
effective initiatives that not only improve
on customer experiences, but the
business as a whole.
It’s through data analysis that
companies are able to drive profits by
making and acting on more insights-
centric decisions.
DaaS Makes Data Profitable.
Source: eMarketer

Any data driven initiatives should be geared
toward getting deeper insights in order to
personalize the customer’s experience.
One company excelling at personalization with
humanized data is Stitch Fix. Using over 85 data
points, Stitch Fix tailors their product to each
customer’s individual preferences. It’s this
personalization that has earned the attention of
Mary Meeker two years in a row.
Personalized Customer Experiences.

Advanced Analytics
DaaS takes a systematic approach to collecting and analyzing data. This approach is
known as data looping and requires a variety of roles and skill sets to do effectively.
Roles in the World of DaaS.
Application Development
Collaboration
Creativity
Data Analyst
Database Management
Domain Expertise
Programming
Systems Integration
Visualization
Advanced Analytics

To see the biggest results from the insights
pulled from the data, organizations need to get
the buy-in from teams and executives company
wide.
Data visualization takes data and uses it to tell
the story that will gain that buy-in and get teams
to understand how initiatives are impacting their
role, department, and the company as a whole.
Visualizing Data.

Data visualization enables you to gain buy-in from your team, investors, stakeholders, and
executives, which is a critical advantage to working with a DaaS provider.
Gaining Buy-In.
Data as a Service turns complex data into something more
viable and accessible that can be used to make a massive
impact on the bottom line.”
- Buckley Barlow, Founding Partner, RocketSource
“

The way you visualize your data can determine
the amount of buy-in you achieve and the depth
of insight you deliver to your teams.
An effective DaaS provider will be able to
visualize data that will show you where to spend
strategically and how to see the biggest profits
as a result of your data-centric initiatives.
Making Visualized Data Insightful.
Convergence/Divergence
Projected ROI

Insights are only valuable if you put them into action and use the data at your disposal to
make revenue-driving changes.
Data mapping is the process of making these insights actionable. By mapping out your next
steps, you have a clear idea of where you must make strategic changes to see the biggest
impact and ROI for your data-investment.
Making Data Actionable.

For a typical Fortune 1000, just a 10% increase in data accessibility will result in more
than $65 million additional net income. But DaaS is about more than financial gains.
Advantages of Data as a Service:
Lower costs, faster paths to innovative ventures, more agile
decision making, data-driven cultures, and lowered risks are
just a few of the successes we’ve seen when working with
our clients.”
“
- Jonathan Greene, Founding Partner, RocketSource

Companies are flocking to artificial intelligence
(AI) because of its ability to efficiently and
effectively interpret data and find patterns that
can predict future behavior.
It’s these predictive analytics that enable
businesses to find new opportunities to lower
costs and increase ROI.
Predictive Analytics Reduce
Costs.

Orangetheory, a high-end gym, used artificial
intelligence to find patterns in their data and
predict behavior from various cohorts of buyers.
By using AI, they were able to reduce their cost-
per-lead by $12, helping spur their growth to
over 1,000 studios in 15 countries.
How Orangetheory Reduced
Costs With AI
Launched
A1 Platform

When you run an intelligent operation, you’re
better able to make data-centric decisions,
reducing your risk and enabling you to execute
on new paths faster.
Chicisimo is an app that grew to 4-million users
in three years by analyzing human behavior.
Using their datasets, they pulled out valuable
insights that let them quickly update their
onboarding process and boost retention rates.
Execute on New Paths Faster.

58% of people don’t make data-driven decisions in business and instead base regular
decisions on gut feel. This gut reaction leads to biased insights, which can prevent growth,
specifically through experience initiatives.
Collecting Unbiased Insights.

By democratizing data, you
provide your teams the tools
needed to move to the next level
in their roles within your
company.
A DaaS provider will make your
data more accessible and
digestible, helping you to drop
silo walls and see significant
changes across the all
departments.
Breaking Down Silo Walls.
Sales and Marketing
Research & Development
Supply Chain/Dist.
Workforce Management
Other Corporate Functions
Capital-asset Management
Other Operations
Manufacturing
Travel
Logistics
School
Sector
Advanced
Industries
Media
Telecom
Consumer
Retail
Financial
Services
Professional
Services
HealthCare
Systems
High
Tech
Materials,
Energy

Although data sets are complex, your DaaS provider should be able to showcase why it’s
worthwhile to start mining unstructured data and tapping into customer and employee
insights.
Proving Your Data Investment Pays Off:
Data as a Service answers the question, ‘Is our investment in
data and analytics paying off?’”
“- Buckley Barlow, Founding Partner, RocketSource

The Challenges of Outsourcing Data Services.
Giving a third-party provider access to something as critical to your business as
your data comes with its fair share of challenges too:
● Data Hygiene. You must consider the operational nuances of collecting and
handling Big Data in order to ensure it remains clean.
● Complex Navigation. You must work with a DaaS provider that
understands the intricacies involved in navigating complex datasets.
● Data Security. Data security is paramount and requires that all data
transmission and storage is handled with care.

Adding a Team to Your Internal Structure.
When integrating a third party team into your internal structure, you want to take things
in stages:
Start Small:
In the beginning, give your new DaaS
provider things they can’t break, such
as data visualization projects.
Stay away from anything with code or
from handing over the keys to any
database architecture.
Then to Back End Projects:
Only once a DaaS provider has been
tested and vetted should you give
access to your back office.
Ultimately, your DaaS provider will work
arm-in-arm with your IT department,
business intelligence team, and more.
Move to Front Facing
Projects:
Progress to working on front-facing
projects, such as conversion rate
optimization (CRO).
Give your DaaS provider access to your
funnel and let them work their magic
optimizing it.

Who Should Outsource Their
Data Analytics?
Small Businesses. To avoid analysis
paralysis and get the most actionable
insights.
Mid-Tier Companies. To properly
analyze the information flowing in as the
business and data grow.
Large Corporations. To drop silo walls
and structure the wealth of data pouring
in every day.

DaaS: A critical component
in today’s data-rich world.
Learn more at
RocketSource.co/Data-as-a-Service

Data as a Service (DaaS): The What, Why, How, Who, and When

Recommended

More Related Content

What's hot (20)

Similar to Data as a Service (DaaS): The What, Why, How, Who, and When (20)

More from RocketSource (20)

Recently uploaded (20)

Data as a Service (DaaS): The What, Why, How, Who, and When

Editor's Notes