Data as a Service (DaaS)

Key Elements of Data as a Service

Data as a Service providers do more than gather information. These providers then translate those data points into insights that can be used to validate assumptions about and gut reactions to the market. When done in conjunction with the organization’s vision, these insights can be visualized and mapped into action steps across the organization.

The result of this work is the transformation of big data sets into profit-building, intelligent initiatives. By drawing out actionable insights, organizations are empowered to tap into data sets and use that information to monetize those insights.

Monetizing Big Data

Monetizing data doesn’t mean selling data for cash. Instead, it involves drawing out deeper insights to deliver better outcomes for employees and customers. This process involves turning data into irrefutable, insulating value that can be exchanged for legal tender.

The process starts by taking data and doing a root-cause analysis to uncover the cognitive associations of a brand. Once done, Data as a Service providers can help you understand how those associations match your brand’s contiguous and overarching customer journey and experience. In doing so, you can monetize initiatives by fueling growth and driving more cash flow.

Mapping Data Across the Bow Tie Funnel

When it comes to tracking your customer’s behaviors, do you track acquisition or retention? The answer is both. Data as a Service (DaaS) providers help clients gather the data across both journeys and then leverage that data into a bow tie funnel. In turn, providers can identify key events and gain behavioral data insights about what drives customers to engage with a brand across the entire funnel.

DaaS providers help you find areas for growth by taking a methodical, strategic approach to gathering, mining and analyzing data in a way that delivers unbiased insights into what customers want. In short, outsourcing your data and analytics can help bring more alignment to your customer experiences.

Foundations of DaaS Operations

Here are the core foundations of how Data as a Service providers work.

Acquisition + Retention

It’s often assumed that tracking growth involves monitoring acquisition metrics such as Return on Ad Spend (ROAS), Return on Investment (ROI), the lifetime value of a customer to cost of acquisition ratio (LTV:CAC) and cost of acquisition (CAC). While these metrics are informative, they’re simply the output of what an organization does to gain a new customer.

Data as a Service providers incorporate retention metrics such as churn rate, repeat purchase rate (RPR) and active engagement rate (AER) to bring behavioral insights across the customer’s journey for reliable, sustainable growth.

Quantitative + Qualitative

Big data doesn’t always mean accurate data. Taming the fire hose of information can be difficult.

Humanizing journey analytics allows companies to take raw numbers and put context to those figures giving organizations an idea of what happening and why. This humanization and looking at numbers as more than just data points can help improve overall experiences.

Intelligent Data Loops

Infrastructure is only a small part of the data looping process. Insights come when organizations roll the data back in and close the loop. This continual data looping process includes visualizing your data and relating the findings to the business’s why. Until your data tells a complete and relevant story, you’ll struggle to extract strong insights and monetize it.

North Star Metrics

Finding the right North Star Metric takes extensive analysis, research and digging. The right frameworks put in place by a Data as a Service provider act as a guide towards uncovering the North Star Metric, as well as provide insight into how to leverage these metrics across your team and the market. These metrics then highlight how well an organization is leading the charge towards sustainable growth or sound alarm bells on a strategy that’s out of alignment.

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Data as a Product (DaaP)

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Data as a Service (DaaS)

Key Elements of Data as a Service

Monetizing Big Data

Mapping Data Across the Bow Tie Funnel