Unifying Your Go-to-Market Strategy with the Data Model: A Comprehensive Guide

Manish Katyan

Discover the power of the Data Model to harmonize your sales, marketing, and customer success efforts. From identifying your target market to driving account expansion, the Data Model covers every stage of the customer journey, ensuring a cohesive and data-driven approach to achieving your revenue goals.

June 7, 2024

In many organizations, sales, marketing, and customer success operate in silos, each tracking different goals, using different technologies, and following different data standards.

This fragmentation can hinder the effectiveness of your go-to-market (GTM) strategy.

To overcome this, teams must develop four key components:

  1. A central framework for GTM.
  2. A central view of the customer and the impact they experience.
  3. Key performance indicators (KPIs) for your customer journey.
  4. Coordinated execution across the entire team.

Enter: The Data Model

The Data Model for recurring revenue companies, often represented by a bowtie, ensures functional unison across the revenue team, aligning everyone towards the same destination.

While other methodologies cover parts of the customer journey, this Data Model encompasses the entire journey, from prospect to lifetime value.

Originally conceived by Jacco van der Kooij of Winning by Design and taught in Pavilion’s Revenue Architecture course, this customer-centric model maps specific stages of the customer journey.

Each of the nine stages has clearly defined customer objectives and exit/entry criteria, creating milestones for each stage.

These milestones ensure you can then build the right people, processes, and data signals to support the outcomes that must be achieved.

The nine stages of the Data Model bowtie are:

1. Target Market

Description: Show all potential companies that are a good fit for your product.

Data Source in Salesforce: Use the Accounts and Leads objects. Look for fields such as industry, company size, geographic location, and other firmographic data to identify potential fits.

2. Demand Creation

Description: Show all companies that have shown a desire to solve the problem that your solution addresses.

Data Source in Salesforce: Use Lead and Contact records with engagement data such as email opens, clicks, website visits, or event attendance.

3. Demand Capture

Description: Show hand-raisers showing intent to buy (meetings scheduled, demo or pricing requested, MQLs).

Data Source in Salesforce: Use the Leads and Opportunities objects. Look for activities like meeting requests, demo requests, or marketing qualified leads (MQLs).

4. Buyer Readiness

Description: Show engaged customers, evaluating your solution to purchase (SQLs, Product Trial).

Data Source in Salesforce: Use Opportunities and associated stages, as well as records of product trials or proofs of concept (POCs).

5. Sales Pipeline

Description: Show customers working with your GTM team to buy your solution.

Data Source in Salesforce: Use Opportunities and Pipeline stages. Track opportunities from initial contact to closed won/lost.

6. First Impact

Description: Show customers who have experienced the core value of your solution for the first time (“aha” moment).

Data Source in Salesforce: Use Customer Success and Support records, post-sale follow-ups, or usage data from integrated product analytics tools.

7. Recurring Impact

Description: Show customers who regularly experience the core value of your product.

Data Source in Salesforce: Use ongoing Customer Success and Support records, along with integration from usage analytics tools.

8. Customer Retention

Description: Show customers who have renewed their contract with you.

Data Source in Salesforce: Use the Contracts or Opportunities object to track renewals and customer success metrics.

9. Account Expansion

Description: Show customers who have purchased additional components of your solution.

Data Source in Salesforce: Use Opportunities to track upsell and cross-sell activities. Look at records of additional purchases or upgrades.

Three primary metrics are tracked for each of the 9 stages:

  1. Volume: How many customers are needed in each stage of the customer journey to hit your revenue target.
  2. Conversion rate: How frequently customers convert at each stage of the journey.
  3. Time: How long it takes for the customer to move from one stage to another.

Together, these metrics provide a formulaic yet flexible methodology for driving customer value at all stages of revenue generation.

Benefits of the Data Model

1. Fostering Collaboration Across Departments

The traditional siloed structure of sales, marketing, and customer success departments often hinders the integrated execution of GTM strategies.

The Data Model introduces a unified revenue goal that aligns these departments towards shared definitions, metrics, and objectives.

This alignment dismantles operational silos, creating a culture of collaboration and shared success.

Imagine your GTM teams as a world-class relay squad, each member running in perfect sync, passing the baton efficiently.

This level of coordination is what the Data Model brings to sales, marketing, and customer success departments.

2. Gaining a Holistic View of the Customer Journey

The customer journey is no longer a linear path but a dynamic, multifaceted experience.

The Data Model provides a fresh, pragmatic view by mapping out specific stages, each with clearly defined objectives and criteria.

This granular visibility allows GTM teams to measure performance across the entire customer lifecycle, ensuring data from every stage is collected, analyzed, and used to optimize customer success.

This approach enhances customer satisfaction and drives sustainable revenue growth through upsells, cross-sells, and renewals.

3. Proactive Problem-Solving and Decision Making

Being reactive is no longer sufficient. The Data Model equips GTM teams with a framework of leading indicators, enabling them to anticipate challenges before they impact the bottom line.

By tracking volume, conversion rates, and time across different stages, teams can quickly identify areas for improvement and adjust strategies accordingly.

This ability to pivot in real-time becomes a significant competitive advantage, helping organizations remain agile and resilient in the face of change and competition.

Implementing the Data Model: Overcoming Challenges

Change Management

The path to implementing the Data Model includes navigating change management challenges.

To overcome these, creating a central framework with clearly defined milestones is crucial.

This involves specifying objectives and criteria for each stage of the customer journey, ensuring all teams share an understanding of goals and success metrics.

Conflicting Definitions and KPIs

Aligning GTM teams under a unified strategy can be challenging due to conflicting definitions and KPIs.

Achieving alignment starts with creating a central framework that clearly defines milestones, objectives, and criteria for each stage of the customer journey.

Engaging all GTM teams to develop these definitions and ensuring they are grounded in the customer experience helps adopt a unified approach to the GTM strategy.

Data Misalignment

Leveraging the full capacity of the tech stack is crucial for tracking the right KPIs.

By using a variety of data types—engagement, intent, process, usage, and buying data—organizations can gain a holistic view of their GTM operations.

This approach moves beyond superficial signals and metrics by diving deeper into the customer journey to identify meaningful patterns and opportunities for optimization.

Bridging the Gap to Action

The true value of the Data Model lies in its ability to guide teams from insight to action.

By integrating milestones, data, and timestamps, organizations can uncover the root causes of challenges and opportunities within their GTM strategy.

This comprehensive framework supports not just diagnostic analysis but also prescriptive measures, enabling teams to adjust tactics in real-time to achieve their revenue goals.

Embracing Continuous Evolution

Adopting the Data Model is not a one-time event but a continuous journey of adaptation and improvement.

Regular review and iteration of milestones and criteria ensure that the model evolves alongside the organization, remaining relevant and effective in driving GTM success.

How RevAmp Integrates with the Data Model

Enhancing Sales Strategy

The Data Model is particularly effective for companies with 50-1000 employees and $10M-$100M in revenue, offering a structured approach to align sales, marketing, and customer success around a common goal.

By mapping out each stage of the customer journey with clearly defined objectives and metrics, your sales strategy can become more focused and efficient.

Seamless Integration with Existing Tools

RevAmp is designed to integrate seamlessly with your existing tech stack, including CRM, MAS, CX, and Product Analytics tools.

This integration facilitates the collection and analysis of data across the entire GTM bowtie, enabling your organization to monitor and optimize each stage of the customer journey in real-time.

Improving Demand Generation

The Data Model enriches your demand generation strategy by offering a systematic way to measure and enhance lead generation and conversion metrics.

By leveraging RevAmp’s integration with your digital channels and sales tools, you gain deeper insights into the effectiveness of your BDRs and the impact of your content.

Addressing Customer Retention and Expansion

The Data Model emphasizes a holistic view of the customer journey, extending beyond acquisition to include retention and expansion stages. For RevOps professionals in B2B recurring revenue companies, this means identifying opportunities to enhance customer lifetime value.

By tracking metrics such as conversion rates and time to conversion across the entire journey, RevOps can pinpoint areas for improvement in customer engagement strategies, driving higher retention rates and identifying expansion opportunities within the existing customer base.

Summing Up: A Unified Path Forward

The transition to a unified GTM strategy via the Data Model is both a challenge and an opportunity.

While implementation may require navigating complexities and aligning diverse teams, the effort transforms the way GTM organizations approach their market.

By breaking down silos, leveraging data, and focusing on continuous improvement, companies can turn potential hurdles into stepping-stones towards achieving a cohesive, efficient, and highly effective GTM strategy.

This collaborative approach drives revenue growth and fosters a culture of unity and innovation, setting the stage for long-term success.

The Data Model is a pragmatic way to reduce GTM risks, provide better data for decision-making, and enhance customer experiences from leads to growing your customer base.

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