CLV, more than Win Rates, Must Factor into your ICP Analysis and be your Northstar metric. Here's Why

November 18, 2024
CLV, more than Win Rates, Must Factor into your ICP Analysis and be your Northstar metric. Here's Why

A broad range of SaaS GTM thought leaders, including Gartner, Demandbase, and many others, emphasize the need for holistic, data-driven ideal customer profile (ICP) research that prioritizes Customer Lifetime Value (CLV). The truth for >90% of SaaS companies is that your CFO and finance team are calculating aggregate CLV metrics episodically for quarterly board meetings, but those calculations are not considered in their GTM execution. Instead, the primary business metric used for data-driven ICP analysis is Win Rates. 

Using CLV to identify ICPs is significantly more effective than relying solely on win rates because CLV provides a fuller picture of customer impact over time. 

While win rates only show the likelihood of closing a deal, CLV captures the revenue each customer will likely deliver during their entire relationship with the business. Focusing your ICP Segment selection on CLV allows GTM teams to optimize their execution for profitability. CLV goes beyond just the probability of closing a deal—capturing the full revenue potential of an account, which paints a much clearer picture of long-term profitability.

Take an iceberg as a metaphor. Win-Rates are like the ice above the waterline, while CLV considers the complete mass of the iceberg above and below the waterline.  

Using CLV instead of Win Rates brings more depth and insights to ICP segment identification. Here are a few of the most critical considerations:

Holistic: CLV considers a customer's entire revenue potential, helping teams target accounts with the highest profit potential rather than just the highest win probability. This results in identifying customers who contribute more to long-term growth.

Cost Efficiency: By targeting prospects in ICP Segments with high CLV, GTM teams can allocate resources more effectively. They can focus on acquiring and retaining high-value customers, which is often more efficient and cost-effective than focusing on quick wins with lower long-term value.

Strategic GTM Focus: CLV helps GTM teams align around customer accounts that support sustainable growth and predictability in revenue—key to optimizing resources and enhancing team alignment across sales and marketing.

In contrast, Win Rates can inadvertently steer teams toward accounts that are easier to close but may not align with the company's long-term goals, potentially wasting resources on low-value accounts.

While CLV is the most critical stand-alone metric for helping identify and prioritize your highest-value customer segments, you must factor in what it costs to acquire those customers to determine the relative profitability of those ICP segments. 

Enter customer acquisition costs (CAC) into the picture. Comparing the CLV to CAC is your optimal way to prioritize ICP segments based on profitability. The CLV/CAC ratio measures the profitability that is sourced from each dollar of sales and marketing investment.

From a SaaS industry benchmarks perspective, a 3:1 CLV:CAC ratio indicates a "healthy" and strong ICP segment. Any ICP segment below that 3:1 ratio is sub-benchmark and warrants investigation into what's driving down the ratio. 

So why aren't more GTM teams using CLV and CLV:CAC ratios in their ICP segmentation research and prioritization? The simple answer is that generating CLV and CAC metrics at a segment level is a major FP&A investment and requires an x-functional investment of resources and time.   

The team at AlignICP believes that GTM teams must prioritize capturing and using CLV as a primary calculated metric to discover and prioritize a B2B SaaS company's ICP segments. Without it, it's difficult, if not impossible, to identify your ICP segments, which, in the most extreme cases, are cancerous to your business. 

Contact us to learn more about operationalizing CLV in your account-based GTM to create more efficient growth.

----

Compass image credit