Reimagining Data as a Service: Unlocking the Full Potential of Data as a Service for Enterprise
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Qualitative data is perhaps one of the most critical parts of modern organizational strategies today, yet many enterprises don’t know where to start collecting it or how to collect it properly. Even more of a struggle is analyzing the qualitative data available to extract insights that can shape the trajectory of the business as a whole. With emerging technologies, such as Large Language Models and Generative AI breaking onto the enterprise scene with force, organizations today want to dive in and leverage these tools for maximum growth. There are more opportunities than ever to take data and speed the time to insights, but it all starts with having the right data to train these models on and the right strategic framework to extract the best insights to deliver higher ROI on your marketing campaigns, higher ROAS, lower CAC, higher LTV, and lower churn rates. Discover how to move beyond surface-level surveys when collecting qualitative data and the ways we’re helping clients integrate emerging technologies into their organization to get critical insights faster than ever. Read the full post here: https://www.rocketsource.com/blog/data-as-a-service-enterprise/
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Reimagining Data as a Service: Unlocking the Full Potential of Data as a Service for Enterprise
- 1. Reimagining Data as a Service for Enterprise Acquisition Retention Trending Marketing Performance Average CPA $62 180 Day Persistency 72% Retention 92% % of Budget 26.2% Net Membership 151,015 Total Spend $395,015 Cancellations 22% Ad Cost Performance Net Memberships Ad Cost Performance Swim Lane Performance Organic Paid Spend Lead Gen Sales Group Other Total Total Ads Cost Daily Net Memberships New Members New Leads New Members New Members New Members Net Members Net Members Net Members Net Members Net Members Net Members Retention Retention Retention Retention Retention Attrition Attrition Attrition Attrition Attrition Attrition Retention Net Members 1,980 6,151 4,180 3,978 852 17,141 47,132 325 1,250 5,151 21,155 19,251 $369 6.5:1 $82 CPA Budget Spend to Date CPA Budget Spend to Date CPA Budget Spend to Date CPA Budget Spend to Date CPA Budget Spend to Date CPA Budget Spend to Date $32,151 $12,515 $25 $91,150 $52,981 $55 $40,981 $11,901 $124 $7,915 $3500 $159 $18,910 $10,015 $85.1 $191,107 $90,912 Cancelled Members Retention Attrition Cancelled Members Retention Attrition Cancelled Members Saved Members Retention Attrition Retention Attrition Retention Attrition Retention 563 132 654 422 10.2% Cancelled Members 696 Cancelled Members 2,561 Total Cancelled 51 Saved Members 94 Saved Members 22 73 Saved Members 94 Saved Members 251 Total Saved 9.8% 5.2% 6.4% 9.8% 12.5% 89.8% 92.1% 95.8% 92.6% 90.2% 87.5% Paid Spend 40% Lead Generation 20% Organic 40% CPA ROAS Budget 12% 33% 42% 51% 72% 71% 78% 82% 83% 83% 189 Days 253 Days 210 Days 320 Days Target 200 Days Paid Spend Lead Generation Sales Groups Organic TCV:CPA Ratio Trend Average TCV 23.4% 6.3% Existing Memberships New Members Returning Memberships Renewals Call to Cancel Auto Cancel
- 2. Welcome to Data as a Service 2.0 Teams are desperate for a clearer idea of how to strategically adopt generative AI to tame big data, infuse human behavior into those big data sets, and properly disseminate the top insights to all teams. It’s this need that has reshaped what Data as a Service looks like. Welcome to DaaS 2.0 — collection, analysis, and actionable strategy. An insightful qualitative and quantitative data practice that extends across the bow tie funnel Extracting and disseminating actionable ideas from the insights so teams know how to effectively tap into data Translating observations into a data science approach to clean, analyze, and visualize insights from across your entire organization
- 3. What Modern Data as a Service Looks Like Enterprises cannot deliver a sublime customer experience without understanding empathy-based insights at every single one of the key moments of the client’s journey. Modern DaaS providers know how to collect behavioral insights and tap into generative AI to unpack the human experience behind the data points, so that you can move more strategically and effectively toward growth. Pains Motivations Solutions Measurements Cognitive Associations Pains Motivations Solutions Measurements Cognitive Associations Cohort First-Time Buyer Employee Customer EX / CX EMPATHY MAP Cohort Employee Customer
- 4. It’s Never Been More Important to Strengthen Your Data Practices Data goes to the heart of every person who’s spending their hard earned money with you. But not all data practices are created equal or ethical. One way organizations have started to tap into data and AI as a means of increasing revenues is through targeted pricing — a practice that’s currently under investigation by the Federal Trade Commission (FTC). What motivates customers to buy — and why do they stay brand loyal? How to align different human behavior needs, wants, and desires How to effectively reinforce value constantly to customers
- 5. Adding Context With Qualitative Data Effective DaaS partners leverage insights to adjust strategies, save money, and build retention while understanding the macroeconomic backdrop. Rather than defaulting to discounts, there’s a distinct opportunity to keep profit margins higher by leveraging platforms, messaging, and experiences to communicate value, reach customers, and influence decision making beyond the price tag. Of respondents would splurge on their child’s must have back-to-school product Average spend on back-to-school items per child down just $11 from 2023 Of the back-to-school budget expected to be spent by the end of July to take advantage of the best deals
- 6. Challenges and Limitations of Legacy Data Practices When you zoom out on a modern timeline, it might feel funny to talk about legacy data strategies. Because this practice has moved at such a breakneck pace, many organizations have fallen into three critical traps: Siloed-based thinking Lack of actionable insights Surface-level takeaways that send teams in the wrong direction
- 7. Breaking Data Out of Silos Too often, teams work independently of one another. Even when an organization has a clear North Star Metric, siloed based communications often lead one team to work toward a different goal than another. Having a DaaS provider as a third party voice can help mitigate these internal conflicts and break down silo walls. As a result, teams will work in closer harmony while working towards unified goals. Data allows departments to come together on the same page
- 8. Making Data Actionable Data governance is crucial. With just one error, teams can be sent in the wrong direction due to inaccurate insights. Because of this risk, teams are often left in the dark, unsure of what insights they should leverage, or how to apply them to their existing roadmap. When data isn’t actionable, teams aren’t sure how to reduce cost of acquisition (CAC), increase lifetime value (LTV), or build retention both internally or externally. Applying actionable insights to results-driven roadmaps keeps teams on track for success
- 9. Applying Empathy to Insights Too often, data is taken at face value. Legacy data practices often don’t account for the people behind the responses. For years it was admirable to take a data-driven approach. Now, this approach has been deemed riskier because it can cause teams to use data to inform the wrong thing and think of data as an absolute. Insights-Centric Data-Centric Data-Driven Insights-centric cultures use data to answer the WHY Data-centric cultures use data to inform & validate; not drive decision making Data-driven culture goes sideways when data are used to inform the wrong thing, as an absolute, and as business first
- 10. Outdated Data Practices Threaten Nike One company that realized these risks of taking an outdated data-driven approach recently was Nike who reported 25 billion dollars lost in one day, along with 130 million shares exchanged in the stock market at the lowest share price since 2018. Nike’s Rocky Sales from 2023 - 2024 Sales to Wholesale Customers Sales Through Nike Direct 2024 Q4 2024 Q1 2024 Q2 2024 Q3 2023 Q4 NIKE INC. (NKE) PE RATIO -8% -6% -4 % -2% 0% 2% 4% 6% 8% 10% 12% 14% 2014 2016 2018 2020 2022 2024 0.0 25 50 75 19.6
- 11. Using DaaS to Build Effective Data Practices Modern organizations must marry both quantitative and qualitative data to drive strategic decision making. While quantitative data provides measurable metrics, having a qualitative data practice in place can help you go deeper to understand the psychological, emotional, and social factors that will help determine why people buy and ultimately why they become brand ambassadors.
- 12. Implementing a Qualitative Data Practice When a DaaS provider comes into your organization, you should be tapping into qualitative data to achieve these three elements for success: ● Understanding what motivates customers to buy and stay loyal ● Aligning wants, desires, and needs with acquisition and retention strategies ● Effectively and constantly reinforcing value Qualitative data practices uncover 360-Degree insights of customers and employees
- 13. What Does an Effective Qualitative Data Practice Look Like? Qualitative data starts by better understanding the Total Addressable Market (TAM) via insights-driven cohorts and personas. ACQUISITION RETENTION TRIGGERS FACTORS DISCOVERY ASSOCIATIONS ALT. ONBOARDING PURCHASE. EXPERIENCE COMMUNITY INTENTION 1. Finding the total addressable market across personas and data-driven cohorts 4. Unearthing an execution plan to kickstart the success of this qualitative data practice 3. Defining data science best practices for converting qualitative to quantitative data 2. Defining the most useful qualitative data for both acquisition and retention sides of the funnel
- 14. Leveraging Qualitative Data to Understand the Total Addressable Market’s Journey Qualitative data allows organizations to go beyond demographics and understand where each cohort is in their self-awareness journey. PROBLEM UNAWARE PROBLEM AWARE SOLUTION UNAWARE SOLUTION AWARE BRAND UNAWARE BRAND AWARE I have not experienced a moment in my life where I’d need what the organization offers. I have thought about this problem but am not sure the ramifications of not fixing it. I know what the ramifications are of ignoring the problem, but not sure of any solutions to help. I know the available solutions but am not sure of the benefits of each solution offered. When I think of these solutions, I think of Brand X and Brand Y. Other brands are unfamiliar. I’m aware of that Brand X offers the solution but have not made a decision about whether or not to buy yet.
- 15. Extracting Behavioral Insights from Data-Driven Cohorts What’s important about this framework is that each cohort in TAM will take a unique journey in their behavior to move through each stage of the journey. Effective qualitative data also looks at why each of these various cohorts are taking such different paths to purchase. This requires a deeper understanding of what’s happening across each of the awareness stages. PERSONAS A B C E D F G A C F G Sees an Ad Visits the brand website Enters lead generation funnel Receives lead generation email Reads reviews Makes a purchase YouTube affiliate video Reads reviews Visits the brand website Retargeting ad Makes a purchase Instagram affiliate Served direct sales ad Makes a purchase B E D COHORT COHORT COHORT Magazine YouTube Social
- 16. Qualitative Insights at Every Stage of the Acquisition Funnel Problem Unaware Problem Aware Problem Aware Solution Unaware Solution Unaware Solution Aware Solution Aware Brand Unaware Brand Unaware Brand Aware TRIGGERS FACTORS DISCOVERY ASSOCIATIONS ALT. Key life moments when a person becomes problem aware Emotional and logical triggers that cause a person to take action and research Platforms used to research and deep dive into finding a solution Subconscious questions about whether a brand is right for them or has what they’re looking for Brand alternatives that could provide a better solution
- 17. Insights-Driven Analysis of the Acquisition Funnel Putting the full strength of practice allows you to see the full strength of the possibilities available in each stage of the funnel. A DaaS partner can show you the opportunities that lied at each stage. TRIGGERS FACTORS DISCOVERY ASSOCIATIONS BRAND ALTERNATIVES Personas close to the brand Related but further from the brand Distant from the brand What brought you to ____ today? Run for 30 days - Price Focused Run for 30 days - Peace of Mind Focused
- 18. Qualitative Insights at Every Stage of the Retention Funnel Focus on removing any buyer remorse and encouraging buyer excitement Reinforce everything the buyer needs, both emotionally and logically, related to their purchase Continue reinforcing trust and building a foundation around the brand values Create a sense of community making every customer feel they belong Ask the customer to self-identify how they value the brand Problem Unaware Problem Aware Problem Aware Solution Unaware Solution Unaware Solution Aware Solution Aware Brand Unaware Brand Unaware Brand Aware RETENTION COMMUNITY EXPERIENCE ONBOARDING PURCHASE
- 19. Insights-Driven Analysis of the Retention Funnel DaaS providers integrate insights-driven ideas at every single stage of the journey. Through the findings of multiple data loops put into strategic motion, you can define the best qualitative data practices, quantify the qualitative insights, and tap into the insights results faster. Pay Success Page Completed Not Completed Reminder Activation Welcome Email Sequence Acknowledge Your Best Content Invitation Soft Sell Surveys Forums In-Person Events Complete Profile
- 20. Modern Data Looping From DaaS Providers Leads to Faster Time to Insights At a high level, there are five steps we walk through when designing a modern data loop and analyzing the results. Choose an appropriate conversion method Select data source & understand context Document and iterate the process Share and communicate the insightful analysis Validate conversion output 1 2 4 5 3
- 21. Selecting Data Sources and Conversion Methodologies Without assessing your data limitations, you’ll have a much harder time deriving accurate insights out of what’s collected. A modern DaaS provider is able to come in, analyze your full data loop, and pinpoint those limitations allowing for cleaner and more contextually clearer analysis. With that understanding and context, teams can then move to step two — leveraging a variety of conversion methodologies and platforms to convert and interpret the data points. Conversion Methods Binning or Discretization Categorization Quantiles Thresholding Z-Score Binning Ranking Principal Component Analysis Dummy Variables Heatmap/Color Coding Clustering Decision Trees Fuzzy Logic Domain-Specific Rules Visualization Based Methods Trends by Images Ranking and Ordering Arrange in Sequence Binary Conversion 0s and 1s Clustering and Machine Learning Grouping Patterns Fuzzy and Domain-Specific Methods Unique Criteria Binning and Categorization Grouping into Bins
- 22. Validating the Conversion Output Preserve Variability Ensure each category reflects the underlying variability of the findings. Avoid Information Loss Minimize the loss of important information during the conversion process. Bias and Fairness Ensure no new bias or unfairness gets introduced into the equation. Transparency Understand the conversion methods and potential biases or limitations. Check Consistency Ensure qualitative data represents quantitative data across the funnel. Validate Against Objectives Verify the data meets initial objectives and supports the intended analysis.
- 23. Communicating Insightful Analysis DaaS providers add color to the black and white picture of plain data by visualizing and communicating the crucial findings. Effective communication is a huge challenge among organizations gathering data from a variety of sources and collection methodologies and combining them to deliver the right information to the right people in the last mile of analysis.
- 24. Creating a Clear Roadmap From a Data as a Service Analysis Until now, we’ve covered using the modern bow tie funnel and data looping process to extract and understand critical insights. But Data as a Service partners should not stop here. True partnerships equip teams with a clear roadmap for how to take those findings and apply across the 3 Ps of an organization — people, processes, and platforms. Process Platform People
- 25. People: Onboarding a Supportive Team to Work Alongside Your DaaS Partner Many organizations aren’t operating with this ideal structure yet. Hiring a DaaS provider is meant to step into your current organizational structure and train your internal team to become modern leaders. Knowing what that structure looks like can help you discern what your organization needs and how a DaaS provider can support you in getting there. People Insights Leadership ● Behavioral Strategist ● Behavioral Economist ● Behavioral Data Scientist Data Managers ● Qualitative Data Manager ● AI/ML Manager ● Private Cloud LLM Manager Data Collection ● PM Survey Coordinator ● Survey Design Specialist ● CX/UX ● Field Interviews
- 26. The Importance of Framework Alignment To drive organizational buy-in, it’s crucial that all of the key players are aligned on every element of the DaaS partnership. This is what we call framework alignment. Awareness Stage Customer Journey Funnel Behavioral Data Data Maturity Model 1 2 3 4
- 27. Processes: Intelligently Adding Generative AI Into Your Data Practices Rather than relying on AI to do all of the analysis, we believe in methodically handing over parts of the data sequence for analysis, and then injecting a human analysis throughout the process. Stage 1: Gathering and Discovery Stage 2: Define Strategy and Scope Stage 3: Create Low-Fi Wireframe Stage 4: Gap Analysis Stage 5: Build Reports Stage 6: Quality Assurance Stage 7: Formal Release and Training Business questions are evaluated to determine whether the answers will come in the form of reports or deeper analysis, and whether the questions can be answered with existing data. We work together to find the metrics of success, stakeholders that will use the report, and ultimately the insights that this dashboard report should deliver to enable business growth We propose a dashboard to visualize the end state of the report to assure the alignment of the stakeholder and engineering. Additional resources can be recommended at this stage. The wireframe and data model is handed over to BI/ENG, at which point they will identify any gaps. If no gaps, engineering can proceed to develop flat tables to support cards within the report. Once the data reports are available, the reports can be built in a data visualization platform. Once the reports are built, all metrics and numbers should be compared to the raw data from the original source to ensure accuracy. This includes checking segments of data over different spans of time. After the reports have been validated, trainings can be released to the stakeholders.
- 28. Taking External Forces Into Account Many external forces are not considered when developing processes, but are always influential, such as key trends, industry forces, macroeconomic forces, and market forces all impact data operations at large. Each of these elements must fit into the equation at some point of your analysis in order to get a more accurate view of what’s happening and what’s possible for your organization. https://amzn.to/3ULWcVn Foresight Regulatory Trends Technology Trends Societal and Cultural Trends Socioeconomic Trends Competitive Analysis Market Analysis Macroeconomics Suppliers and Value Chain Actors Stakeholders Competitors (Incumbents) New Entrants (Insurgents) Substitute Products and Services Capital Markets Global Market Conditions Economic Infrastructure Commodities and Other Resources Market Segments Needs and Demands Market Issues Switching Costs Revenue Attractiveness Key Trends Macro Trends Industry Trends Market Forces
- 29. Platforms for Strong Data Operations With a DaaS Partner The proliferation of new and emerging platforms is enough to make even the savviest of leader’s heads spin. It’s hard to make sense of all these available tools. There’s no possible way every organization could use each of these tools. Nor is it possible that every tool is perfectly suited for every business. That’s why, at RocketSource, we remain staunchly tech agnostic. Look at all of those platforms - just for marketing!
- 30. Leaning Into Emerging Platforms Bringing a DaaS provider into the equation allows you to adopt AI platforms in the right way, alleviating complexity and increasing business value. Don’t go straight for the shiny new AI platforms but instead take a methodical approach to decide which types of AI tools can be infused into processes to speed time to insights without eliminating the human touch. Descriptive Diagnostic Predictive Prescriptive Cognitive Without AI Business Value Complexity With AI
- 31. Extracting Business Value From a Data as a Service Partnership To start identifying a clear roadmap rooted in data and insights, you need to first understand the data maturity of your organization. Trigger Reactive Proactive What/Where When/How Why Will Automation: Activities and systems are automated invisibly to improve performance to reduce human error and improve reliability. We want to evaluate performance within our marketing mix, sales ops, and operations. We want to evaluate a change in performance over time and apparent correlations. We want to understand the external and internal key drivers of consumer behavior in the decisions to buy and stay. We want to product how emerging trends will impact business financial health if they continue. We want to understand how micro events within our organization and workforce can be optimized. Metrics are pulled manually either within a single channel or into spreadsheets for analysis. Additional charts and decks are built to illustrate metrics in motion to relevant teams. One-off studies or activities are run to answer why, usually only following an abnormal spike, crisis, or issue. Mean-based data is pulled together from various sources to inform action for a fixed window of time. Ad hoc engagement data is captured and observed to inform the integration of business units to drive growth and reduce costs. Data points are joined into an automated system to report for specific analyses. Dashboards are standardized to inform teams of their historical performance in the organization. Insights are democratized at a regular cadence to evaluate product-market fit, anticipating market forces. Several distance measures and data arrays are measured with ML to proact known trends and optimize performance. Automated systems leveraging AI/ML ensure alignment in people, processes and platforms to efficiently execute the business model. HINDSIGHT INSIGHT FORESIGHT
- 32. Go-to-Market Strategies for Customer Acquisition and Retention As an organization, the desired action is often to move potential buyers from problem unaware to solution aware, acquiring new customers as cost effectively as possible. With data and insights, your team can pinpoint where customers are churning out of your bow tie funnel, which we outlined above, and how you can course correct to acquire and retain more of those people before they churn. Would exchange their data for better brand experiences. Expect an AI-driven experience that is personal Of respondents insist on keeping their data private (was 61% prior to ChatGPT becoming prolific). Expect an AI-driven experience that is relevant Expect an AI-driven experience that is environmentally friendly
- 33. Improving Behavioral Data Collection from Digital Experiences There are a plethora of data collection tools, but DaaS providers aren’t employed to answer isn’t which tool is better than the other. They’re there to help you find the right tools for your organization so that you can most effectively personalize customer and employee experiences, and equip you to drive your ability to drive full Account Based Marketing (ABM) strategies. Google Analytics 4 and/or Adobe Analytics: Offers advanced tracking capabilities and insights into user behavior across websites and apps. Google Tags: Facilitates streamlined tagging and tracking for comprehensive data collection. BigQuery: Provides powerful data warehousing and analytics, allowing for efficient storage and querying of large datasets. Google Looker Studio and Tableau: Allows teams to visualize data and contextualize the takeaways to provide meaningful insights to teams.
- 34. Tapping Into Data as a Service for Account Based Marketing If you don’t have a solid data practice, you can’t execute on the final output. Until recently, leveraging data was somewhat labor intensive. Proper data collection processes that tap into behavioral data and bring teams closer to deeper insights can help bring in higher quality leads, build retention, and close more deals. Find Top Opportunities Understand Your Cohorts Personalize Engagement Organizational Collaboration Defined Behavioral Data Tracking
- 35. Telling Data Stories through Data Visualization Effective data storytelling is essential for ensuring stakeholders understand and implement insights. Acquisition Retention Trending Marketing Performance Average CPA $62 180 Day Persistency 72% Retention 92% % of Budget 26.2% Net Membership 151,015 Total Spend $395,015 Cancellations 22% Ad Cost Performance Net Memberships Ad Cost Performance Swim Lane Performance Organic Paid Spend Lead Gen Sales Group Other Total Total Ads Cost Daily Net Memberships New Members New Leads New Members New Members New Members Net Members Net Members Net Members Net Members Net Members Net Members Retention Retention Retention Retention Retention Attrition Attrition Attrition Attrition Attrition Attrition Retention Net Members 1,980 6,151 4,180 3,978 852 17,141 47,132 325 1,250 5,151 21,155 19,251 $369 6.5:1 $82 CPA Budget Spend to Date CPA Budget Spend to Date CPA Budget Spend to Date CPA Budget Spend to Date CPA Budget Spend to Date CPA Budget Spend to Date $32,151 $12,515 $25 $91,150 $52,981 $55 $40,981 $11,901 $124 $7,915 $3500 $159 $18,910 $10,015 $85.1 $191,107 $90,912 Cancelled Members Retention Attrition Cancelled Members Retention Attrition Cancelled Members Saved Members Retention Attrition Retention Attrition Retention Attrition Retention 563 132 654 422 10.2% Cancelled Members 696 Cancelled Members 2,561 Total Cancelled 51 Saved Members 94 Saved Members 22 73 Saved Members 94 Saved Members 251 Total Saved 9.8% 5.2% 6.4% 9.8% 12.5% 89.8% 92.1% 95.8% 92.6% 90.2% 87.5% Paid Spend 40% Lead Generation 20% Organic 40% CPA ROAS Budget 12% 33% 42% 51% 72% 71% 78% 82% 83% 83% 189 Days 253 Days 210 Days 320 Days Target 200 Days Paid Spend Lead Generation Sales Groups Organic TCV:CPA Ratio Trend Average TCV 23.4% 6.3% Existing Memberships New Members Returning Memberships Renewals Call to Cancel Auto Cancel
- 36. Acquisition Retention Trending Marketing Performance Average CPA $62 180 Day Persistency 72% Retention 92% % of Budget 26.2% Net Membership 151,015 Total Spend $395,015 Cancellations 22% Ad Cost Performance Net Memberships Ad Cost Performance Swim Lane Performance Organic Paid Spend Lead Gen Sales Group Other Total Total Ads Cost Daily Net Memberships New Members New Leads New Members New Members New Members Net Members Net Members Net Members Net Members Net Members Net Members Retention Retention Retention Retention Retention Attrition Attrition Attrition Attrition Attrition Attrition Retention Net Members 1,980 6,151 4,180 3,978 852 17,141 47,132 325 1,250 5,151 21,155 19,251 $369 6.5:1 $82 CPA Budget Spend to Date CPA Budget Spend to Date CPA Budget Spend to Date CPA Budget Spend to Date CPA Budget Spend to Date CPA Budget Spend to Date $32,151 $12,515 $25 $91,150 $52,981 $55 $40,981 $11,901 $124 $7,915 $3500 $159 $18,910 $10,015 $85.1 $191,107 $90,912 Cancelled Members Retention Attrition Cancelled Members Retention Attrition Cancelled Members Saved Members Retention Attrition Retention Attrition Retention Attrition Retention 563 132 654 422 10.2% Cancelled Members 696 Cancelled Members 2,561 Total Cancelled 51 Saved Members 94 Saved Members 22 73 Saved Members 94 Saved Members 251 Total Saved 9.8% 5.2% 6.4% 9.8% 12.5% 89.8% 92.1% 95.8% 92.6% 90.2% 87.5% Paid Spend 40% Lead Generation 20% Organic 40% CPA ROAS Budget 12% 33% 42% 51% 72% 71% 78% 82% 83% 83% 189 Days 253 Days 210 Days 320 Days Target 200 Days Paid Spend Lead Generation Sales Groups Organic TCV:CPA Ratio Trend Average TCV 23.4% 6.3% Existing Memberships New Members Returning Memberships Renewals Call to Cancel Auto Cancel
- 37. Unlocking the Full Potential of Data as a Service for Enterprise Learn more at RocketSource.com/Blog/Data-as-a-Service-Enterprise