By Carlos Vidal, Manager, Lead Generation Practice, SBI
In part 1 of this series, we established the value of installing a closed loop contact-to-contract lead measurement process. We promised to explore in a series of follow-on articles, three metrics that are key to this new process. In this second installment we focus on optimizing Lead Generation Spend.
Most organizations establish metrics for evaluating lead cost effectiveness. These metrics typically capture a lead’s fully loaded cost, but they do not account for lead development time or lead revenue. By introducing the time and revenue variables into their lead calculations, organizations can determine not only which leads generate a positive ROI, but also which sources produce leads that move most quickly and reliably to closure. Lead sources include Trade Shows, Print, Direct Mail, word of mouth, Paid Search, Web forms, etc..). By gauging the effectiveness of a lead’s source, organizations can better allocate their demand generation marketing spend.
Some Lead Spend Metrics
Three of the most widely used metrics for evaluating lead effectiveness are:
• Cost per Opportunity (CPO)
• Cost per Marketing Qualified Lead (CPMQL)
• Cost per Lead Inquiry (CPLI)
These metrics attempt to measure different aspects of marketing spend related to a specific lead source. By adjusting them to account for revenue and time, you can improve the measure of Lead Source Effectiveness. To illustrate, let’s focus on one as an example of a commonly tracked metric, CPO.
Cost per Opportunity (CPO)
CPO = Cost to produce all leads from a Lead Source
# of Registered Sales Opportunities from those Leads
Drawbacks in ‘Standard’ approach to CPO
1. It does not reflect the cost to close the opportunity (only for the cost of opportunity creation). This is important because some sources provide leads that take more effort to close (i.e. on-site visits, pilots, RFP).
2. It does not reflect the average revenue derived from a source’s leads. This is important because sources differ in the revenue they produce (consider this the Glengary Glen Ross factor).
3. It does not reflect the time it takes to close a lead. This is important because some sources provide leads that take longer to close than others. For example, military contractors usually know what they want to buy for a project from prior experience and just need a firm quote, but their funding request could take months to approve.
A new Way to Measure and Optimize Spend
The three drawbacks can be resolved in an improved formula for Lead Source Effectiveness (LSE) of a specific lead source.
LSE = __Average Revenue per Lead __ x 251 selling days
CPO + Avg. Closure Cost per Lead Avg. Time to close Lead
In this new approach, revenue, closure cost and lead turnover are all addressed.
So what have we gained?
We have transformed an unenlightening demand generation metric into a diagnostic tool to aid in decision-making.
The Payoff
Marketing Executives can use metrics like LSE to re-direct investment dollars to those lead sources that generate the most revenue, the most quickly, with the least amount of sales expense. This insight can also help refine your Ideal Customer Profile (ICP). For instance, your ICP might require revision after you determine the true cost of leads for a specific industry segment or buyer type.
The payoff for using LSE (in lieu of CPO) is huge. The only challenge is that it requires cooperation between Marketing and Sales to ‘close the loop’ of demand generation analytics.
Our next article in this series will focus on compressing the buying cycle through correlating content access to the buying cycle.
Carlos is a Principal at Sales Benchmark Index (SBI), a strategic advisory firm that helps executives understand how well their sales forces are performing relative to peer group and World-Class levels. SBI is differentiated through the use of empirical data -- a repository of over 11,200 companies, across 19 industries, 11 years of history and over 315 sales metrics. Through SBI’s sales benchmarking services a company can use comparative data to identify improvement opportunities available by leveraging best practices of World-Class companies.
2 comments:
The LSE Formula above has a formatting issue which places the denominators very close to each other.
To remove any doubt, please refer to this version:
LSE = (Average Revenue per Lead / (CPO + Avg. Closure Cost per Lead)) X (251 Selling Days / Avg. Time to close Lead)
Any qualified comments on the LSE report in Microsoft Dynamics CRM? It seems kind of worthless, only allowing predefined source categories instead of real campaigns.
Post a Comment