The missing foundation to your GTM strategy.

GTM strategy without data strategy cannot scale.

Highlights:

• [Hot Take] You can no longer afford to ignore your customer data strategy. But what does that really look like? Join the conversation in our Slack community.
• [Forbes feature] Our wonderful RevOps, Jessica (JP) Zangre , and customer Chris Thompson at Conga got a shoutout in “Inside the Mind of The Chief Revenue Officer”
• [Podcast] Rick VARGAS , Marketing and Revenue Ops veteran, discusses the missing link in intelligent automation: unified data.
• [Blog] Is Salesforce Data Migration the Right Step for your Business Success?
• [Webinar] How to Navigate M&A and Multi-CRM Complexity on Tuesday, May 2nd at 12pm PDT

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No one makes a B2B business without a GTM strategy.

No one scales a B2B business without a customer data strategy.

…Disagree?

Think about it this way: what’s the difference between (A) a founder selling with a spreadsheet of contacts, manually updating the relationship progress and contact info in a few columns, and (B) modern B2B sellers?

The technology they use (and likely some automated processing).?

But that technology is only as good as the data within it.

Your GTM tech is only as good as your customer data.

What’s the difference between a GTM strategy and a customer data strategy?

1. GTM Strategy: TAM, OKRs, KPIs, Messaging, Positioning, Personas, Pricing & Packaging, Channels, Tactics, Teams (and their Training & Enablement), Partners, Customer Journey Map, Handoff Processes.
2. Customer Data Strategy: Funnel Metrics, Customer Journey & Unified Data Model, Data Architecture, Data Governance, Data Quality, Security, Accessibility, Reporting & Analytics - and most importantly: the operational data your GTM teams need to use every day to drive revenue and customer satisfaction.

It is absolutely true that GTM strategy is much more central and foundational than Customer Data Strategy.

But it is equally important to understand:

You cannot scale GTM without a real, managed, expert customer data strategy.

Often these two domains only meet at reporting, which is problematic. What about the model? The plan? And the execution? Let’s lay it out:

1. Model: What is our customer journey? What data objects and fields will represent those? How are they related?
2. Plan: What strategies, tactics and systems will we deploy to bring that model to life with our market?
3. Execution: What data collection/capture points, system integrations, automations, and processes will be present in our customer experience along the journey?
4. Analysis: What metrics and KPIs will we use to determine success or failure of Execution against the Plan?
5. Iteration: Make improvements to the Plan, add new channels, markets, or products, shift targeting away from underperforming segments.?

Everyone wants to be strategic. But analytics does not equal data strategy.

Or as Rick Vargas put it on this week’s podcast: “Intelligence in business comes from layering the data science and analytics pieces into your everyday processes and automations – which requires trusted, unified data.”?

This is why you can no longer afford to ignore your customer data strategy.

GTM and RevOps experts recognize this truth: you cannot succeed at scale without customer journey modeling that feeds a data strategy.

Cheers,

Evan Dunn

Director, Growth Marketing