Cost Per Lead Guide + Difference Between CPL, MQL, & SQL

CPL Calculation: Formula + Example

To determine the cost per lead, divide the overall marketing expenditure by the total number of leads acquired within a specific timeframe. You can calculate this metric on a high level for all marketing activities or at a granular level for specific channels or marketing campaigns.

Cost per lead is most commonly calculated for paid marketing efforts because the spend is more linear — dollars in equals leads out. When considering how much you should spend on ads, an example would be a $10,000 campaign you ran to promote a new ebook to your audience. Say you generated 200 leads by the end of the campaign. Your cost per lead formula would be:

$10,000 / 200 new leads = $50 per lead

While ad spend is the easiest frame of reference for CPL, you should also be able to calculate this metric for spend on content marketing, search engine marketing, including pay-per-click (PPC), SEO, and more.

Why CPL Is an Important Metric for Finance Teams

Cost per lead (sometimes called cost per acquisition or CPA) is an important metric for finance teams because it helps you drill down into the “why” behind your acquisition costs. While marketing leaders ultimately own this metric, finance leaders can use it as valuable context for collaborating with that side of the business more effectively.

Great marketing teams will always have a healthy dose of experimentation built into their plans. But that doesn’t mean you want the budget to get out of control. Knowing your CPL is vital for achieving a lower cost in lead acquisition, helping strike the right balance between cost-effective activities and high-upside strategies.

A few reasons to make sure you’re tracking CPL alongside other marketing metrics (other than improving marketing budget allocation) include the following.

Improve Sales Funnel Efficiency

A low CPL, especially in high-volume campaigns, indicates that your marketing efforts are aimed at the right target audience and generating leads at an efficient rate. Monitoring this metric helps increase your sales funnel conversion rates and can ensure that potential customers are moving through the funnel smoothly without unnecessary bottlenecks or delays. Effective sales funnel optimization not only targets new customers but ultimately results in more closed deals and increased revenue for your business — without necessarily sinking more dollars into your paid and organic marketing strategies.

Simplify Financial Forecasting & Planning

Knowing your CPL helps you create accurate financial assumptions that support stronger top-line models. Instead of building revenue forecasts on CAC assumptions alone, CPL and other funnel metrics help you create a stronger bottom-up model that includes more input from marketing leaders. The result is more realistic budgets, more strategic conversations about lead generation strategies, and more realistic growth projections.

Benchmark Performance for New Channels

One of the most common pain points in the finance-marketing relationship is the challenge of benchmarking expected returns on new channels. If you’ve only ever run Google ads but now want to move into ad campaigns on a review site like G2, how do you know as early as possible if things are going well? Knowing your cost per lead across existing channels will help you proactively assess the return on investment of the new channel. Marketing’s job is to optimize the campaigns in real time, but you can assist in data analysis during retros.

Differences Between Cost Per Lead, Cost Per MQL, and Cost Per SQL

The difference between cost per lead, cost per MQL, and cost per SQL lies entirely in the stage of the sales funnel they represent.

Your cost per lead represents the lowest form of qualified leads, when they first come in the door and you collect contact information. As such, this will be the lowest cost of the three metrics.

When marketing has determined that a prospect is a quality lead (depending on unique internal criteria), that prospect becomes an MQL. And when the potential customer is qualified enough to move to the sales team, it becomes an SQL.

The calculation for each metric is the same — total costs divided by the number of new leads/MQLs/SQLs generated. But as your conversion rates play out, the per-lead cost gets more expensive as you get closer to a deal.

How to Analyze Cost Per Lead with Mosaic’s Metric Builder

On the surface, cost per lead is a simple metric that helps you better understand the average cost to get someone into your sales funnel. But if you can unlock the true potential of all the data sitting in your ERP and CRM, you can dig much deeper into this metric and find strategic insights about your marketing engine.

Mosaic’s Metric Builder helps you customize your cost-per-lead calculations to get as granular as necessary to analyze your capital efficiency. Split your cost per lead by channel, campaign, customer segment, and anything else you can think of as you try to optimize acquisition spend.

While it’s been possible to get these granular calculations in spreadsheets before or through channel-specific platforms like Adwords, the process has been complex and disconnected. Mosaic automates data aggregation, so you’re always working with real-time actuals. And Metric Builder gives you a simple, no-code UI to create any metric imaginable with just a few clicks — all based on your unique datasets.

Want to learn more about how Metric Builder can help you analyze cost per lead and the other metrics that matter most to your business? Reach out for a personalized demo.