How to Diagnose GTM Issues in a Scaling SaaS Business

Summary

The video discusses a structured methodology for diagnosing issues with recurring revenue growth in SaaS businesses, following five key steps - define the problem, collect quantitative and qualitative data, identify causal factors through models like the growth, data and go-to-market models, conclude the root cause via techniques like the five whys, and outline an implementation plan. It provides an example case study and real-world insights, advising starting small with agile iterations focused on customer impact, supported by a coalition of willing leaders.

Takeaways

• 😀 Diagnosing problems thoroughly is critical before jumping to solutions - spend 55 mins on diagnosing for every 5 mins on solutions
• 💡 Use quantitative data (metrics) and qualitative data (interviews, call reviews etc.) together to get the full picture
• 📊 Benchmark performance and conversion rates against industry standards to identify issues
• 🔎 Analyze data trends over time to spot potential problems early
• 🕵️‍♂️ Use models like the Growth Model, Data Model and GTM model together to uncover root causes
• ❗️ Going upmarket to enterprise requires new processes and skills across the org
• 💰 Misalignment between GTM model and rising ACV is a common challenge during scaling
• 😥 Symptoms like poor rep performance and high churn point to underlying root causes
• 🤝 Build a coalition focused on customer impact before trying to make incremental changes
• 🚀 Take an agile approach - start small, iterate quickly, measure impact

Q & A

What is the first step in diagnosing go-to-market issues according to the presented model?

The first step is defining the problem by collecting quantitative and qualitative data from different focus areas like go-to-market model, processes, technology, enablement, skills etc.

What three common problems were mentioned that companies face in the scale-up phase?

The three common problems were - not having a common data model, launching too many go-to-market motions too early, and not having a repeatable process nailed down.

What is the benefit of using both quantitative and qualitative data?

Using both types of data together provides the complete picture. Quantitative data provides facts and efficiency while qualitative data provides context and insights to generate hypotheses.

What technique did they recommend to identify root causes?

They recommended using the 5 Whys technique to drill down to the root cause by repeatedly asking why for each problem identified.

What issue did they uncover related to sales rep performance?

They found that 80% of revenue was coming from only 35% of the reps, indicating a skill gap among the broader sales team.

What change was required when moving upmarket to enterprise sales?

Moving upmarket requires implementing new processes and ensuring the team has the skills to handle longer sales cycles, complex stakeholder management, executive engagement etc.

What go-to-market model components were misaligned for the use case?

The ACV was $75k but they were using a 2-stage motion optimized for much smaller ACV deals, so sales roles, CS roles etc. were not equipped for enterprise selling.

What implementation advice was provided related to improvements?

Start small with incremental improvements, avoid too many changes at once. And focus on building a coalition aligned around customer impact before diving into solutions.

What benchmarking data source did they recommend?

They recommended Bench Site, an open source database of conversion rate benchmarks that can provide comparison to industry peers.

How can they assist with a goto market diagnostic for your company?

They offer a 4-6 week goto market analysis engagement costing around $50,000. They can also facilitate workshops to build internal alignment at an introductory price of $2,500.