#1 GTM AI Insider: 2025 AI Strategy Planning 2 of 8
Step 2: Conduct a Thorough Gap Analysis
A gap analysis is the bridge between setting ambitious targets and achieving them. It provides clarity on where your business currently stands versus where it needs to be. The idea here is to identify not just the obvious shortcomings but to understand the underlying causes so you can address them effectively.
What This Looks Like in Practice:
1. Assess Current Metrics
The first step in a gap analysis is to measure your existing performance. You need a clear, data-driven picture of how your organization or teams are currently performing in relation to the specific targets you’ve set.
Example: Assessing Current Sales Metrics for a 50% Revenue Growth Goal
Imagine you’ve set a target of increasing revenue by 50%. To achieve this, you aim to improve your sales conversion rate by 15% and increase average deal size by 20%. Before deciding on any changes or implementing AI, assess the current state of key sales metrics:
• Lead-to-Opportunity Conversion Rate: Measure how many leads are successfully moving through the funnel. For instance, if only 10% of leads are moving to the opportunity stage, there’s clearly room for improvement.
• Sales Cycle Length: If the average time it takes to close a deal is 90 days, assess where the bottlenecks are occurring. Are there delays in follow-ups, extended negotiations, or decision-making challenges?
• Win Rate and Average Deal Size: Look at your current win rate and the average value of each closed deal. For instance, if your average deal size is $25,000 and your goal is $30,000, you need to understand why you’re falling short.
2. Diagnose Root Causes
After assessing your current state, the next step is to identify the underlying causes of these gaps. This is where surface-level problem-solving often falls short—because you can’t fix what you don’t fully understand. Use proven techniques like the 5 Whys to dig deeper.
Example: Diagnosing Low Lead-to-Opportunity Conversion Rate
If your lead-to-opportunity conversion rate is low, ask a series of questions to uncover the root cause. Here’s a structured example using the 5 Whys technique:
1. Why is the lead-to-opportunity conversion rate low?
• Because sales reps are focusing too much time on low-quality leads.
2. Why are sales reps focusing on low-quality leads?
• Because the current lead-scoring model isn’t accurate enough to prioritize high-probability leads effectively.
3. Why isn’t the lead-scoring model accurate?
• Because it relies heavily on basic demographic and firmographic data rather than behavioral insights.
4. Why aren’t we using behavioral insights?
• Because we lack the tools to track and analyze how leads interact with our website, emails, and content.
5. Why haven’t we invested in those tools?
• Because there hasn’t been a clear business case for using AI-powered behavioral analytics to improve lead scoring.
Outcome of Root Cause Analysis
After completing this root cause analysis, you find that your lead-to-opportunity conversion rate isn’t just low because of poor follow-ups or sales performance—it’s low due to a weak lead-scoring model. The real solution, therefore, involves improving lead scoring with more robust behavioral data, supported by AI, rather than just telling reps to “work harder.”
Real-World Example: Conducting a Gap Analysis for Customer Retention
Suppose your revenue growth goal also relies heavily on improving customer retention. Currently, your churn rate is 15%, and you want to reduce it to 10% to contribute to the overall 50% revenue growth target. You start by assessing key customer retention metrics:
1. Assess Current Metrics:
• Churn Rate: Identify the current percentage of customers who are leaving within the first six months.
• Customer Lifetime Value (CLV): Look at your existing CLV metrics and how retention impacts overall revenue.
• Customer Engagement and NPS Scores: Measure customer satisfaction and engagement with your product or service. Low NPS scores may indicate growing dissatisfaction.
2. Diagnose Root Causes:
Using the 5 Whys technique, you find:
• Why is our churn rate high?
• Because customers aren’t seeing enough value after the initial purchase.
• Why aren’t they seeing enough value?
• Because onboarding isn’t tailored to their specific use cases.
• Why isn’t onboarding tailored?
• Because the customer success team lacks detailed customer insights.
• Why are insights lacking?
• Because we’re not gathering enough usage data to personalize onboarding.
• Why aren’t we gathering usage data?
• Because we don’t have a tool to monitor and analyze customer behavior effectively.
DING DING DING now we are getting somewhere
Outcome of Root Cause Analysis:
Now you’ve identified that the root cause of high churn isn’t just poor onboarding execution—it’s the lack of real-time customer insights. Your action plan could include implementing an AI-powered customer engagement analytics tool that personalizes onboarding based on usage patterns and customer behavior.
Practical Takeaways for Step 2:
• Assess Key Metrics Accurately: Don’t just measure surface-level metrics. Dig deeper to understand performance trends and patterns. This is crucial to building an effective AI strategy.
• Use Structured Analysis Techniques: Techniques like the 5 Whys help you go beyond symptoms and get to the root cause of problems. This avoids making superficial changes that don’t address the underlying issues.
• Focus on Actionable Insights: The goal of a gap analysis isn’t just to identify what’s going wrong—it’s to create a data-backed action plan that leverages AI strategically to close these gaps.
The Key Takeaway:
A thorough gap analysis is critical to understanding not just where you need to improve, but why improvement is necessary and what is causing the gaps. This lays the foundation for leveraging AI as a targeted solution to address specific issues. By doing this, you move from a reactionary approach to a proactive, strategic AI implementation that aligns with your business goals.
For more reading on this, I highly recommend following and reading this article from one of my friends and mentors, Mike Kunkle, who has his own methodology around this process called COIN-OP. Well worth the read https://www.linkedin.com/pulse/situation-assessment-framework-versatile-tool-mike-kunkle-pn20e/
PROMPT:
Copy paste this prompt into your chosen AI tool:
***ROLE***
You are a Strategic Gap Analysis Expert with 20+ years of experience in performance improvement and root cause analysis. You excel at identifying underlying causes of performance gaps using proven methodologies like the 5 Whys technique and creating data-backed action plans.
***Instructions***
If you understand, start by asking the user these questions in sequence:
1. "Please share the primary business goal and revenue target you defined in Step 1."
2. After receiving the answer, ask:
"What were the specific department targets and metrics you set for:
- Sales
- Marketing
- Customer Success
- Any other key departments"
3. After receiving these, ask:
"What timeline objectives did you set in Step 1 (both 6-month and 18-month targets)?"
4. Finally, ask:
"What value propositions did you define for each department?"
Only after receiving all this information from Step 1, proceed with the gap analysis.
[Rest of the prompt remains the same...]