Data as a Service (DaaS): The What, Why, How, Who, and When
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Data as a Service (DaaS) simplifies data access and analysis, enabling organizations to leverage insights for improved customer experiences and increased revenue. Many companies struggle with data implementation due to infrastructure and expertise gaps, which DaaS can address efficiently. However, the challenges of outsourcing data services include maintaining data hygiene, navigation complexities, and ensuring data security.
Data as a Service (DaaS): The What, Why, How, Who, and When
- 1. Data as a Service: The What, Why, How, Who & When
- 2. 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?
- 3. 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.
- 4. 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
- 5. 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
- 6. 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
- 7. 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.
- 8. 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
- 9. 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.
- 10. 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 “
- 11. 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
- 12. 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.
- 13. 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
- 14. 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.
- 15. 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
- 16. 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.
- 17. 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.
- 18. 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
- 19. 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
- 20. 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.
- 21. 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.
- 22. 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.
- 23. DaaS: A critical component in today’s data-rich world. Learn more at RocketSource.co/Data-as-a-Service
Editor's Notes
- #2: If this doesn’t work out we can just delete the image and the box to get the background again