PPCHow to Estimate the Break-Even Point of Paid Search

How to Estimate the Break-Even Point of Paid Search

Is there a correlation between a price of a product or service and its CPC? Do keywords associated with high-priced products cost more? Use these break-even points to help determine the favorability of a successful investment in paid search.

A few months ago I wrote about the death of paid search and had to sustain the backlash of the paid search community through 38 comments and multiple “hate tweets.” I actually enjoyed the discussions and learned quite a lot from some of them.

The question that kept bugging me was if there’s a correlation between a price of a product or service and their CPC? Do keywords associated with high-priced products cost more?


Image Credit: Wikipedia

In the core of this question is the theory of economic equilibrium. Simply, in perfect market conditions, the price of products will be set at a level where supply and demand are equal and with no change in supply or demand, the price will stay the same.

The reason why this theory is important for understanding the relationship between product price and CPC is that if information was completely available to all parties in the market (a required assumption in this theory) then knowing the average cost-per-click (CPC) will allow companies to evaluate the effectiveness of paid search. In turn, companies will decide whether they want to invest in paid search, which will shift the demand curve, creating a new equilibrium price.

For example, if average CPC is low enough to allow positive ROI, more companies will participate in paid search campaigns, increasing the demand and consequently driving the average CPC up. When the price reaches a point of negative ROI, companies will stop their campaigns, decreasing demand and lowering the average CPC.

These shifts will occur until CPC will stabilize where both suppliers (Google) and buyers (advertisers) are satisfied with the return on paid search. That price point will be the point of break-even, where the investment in paid search (CPC) will match the return (sales at a certain price).

But why finding the equilibrium price of a channel is important or even interesting? Well, finding that price, and knowing the rest of the conversion rates of your funnel, will help you evaluate the potential effectiveness of a channel before you even spend a dollar on testing it.

Furthermore, knowing the equilibrium price can, theoretically, help you find arbitrages, places where the market is not at equilibrium and the price is lower than what it should (and will) be. Those arbitrages are opportunities to exploit imperfect market conditions to your benefit until supply and demand return to equilibrium and the price stabilizes again.

Researching the Equilibrium Price of Paid Search

In order to find the equilibrium price of paid search, I needed to find the break-even point.

To simplify, I assumed no overhead costs (no contractors, fixed costs, software costs, etc.) in my calculations, just pure CPC compared to revenue. I wanted to find out if it’s possible to predict the effectiveness of paid search as a channel based on a company’s price point. The math is simple:

$X * W% * L% * V% ≥ $CPC

  • Price of product or service = X
  • Close won rate (%) = W
  • Conversion rate from lead to opportunity (%) = L
  • Conversion rate from visitor to lead (%) = V
  • Cost Per Click = CPC

As long as the left side of the formula is equal or bigger than the right side, paid search is favorable. It seemed like I had a good start.

Using this formula, I can tell for any given price point what is the maximum CPC that I can afford before I start losing money on this channel. But putting together the formula is the easy part, finding the values for the variables needed to solve it, is the challenge.

So I embarked on a quick research to find the following variables:

  • Close won rate (%) = W
  • Conversion rate from lead to opportunity (%) = L
  • Conversion rate from visitor to lead (%) = V
  • Cost Per Click = CPC

One of the challenges with finding these variables is that they are extremely specific to industries. It’s hard to come up with a real average for these data points since the variation among the industries is so big.

Furthermore, when you look at individual companies, even within the same industry and market, you will find great variation that will prevent you from coming up with real averages (or at least statistically significant ones).

The solution is to look at optimal rates and not averages. Since my task was to find the price point in which paid search breaks even, I assumed that the entire funnel is optimized and the company achieved optimal results (within reason).

(Note: these figures relate to B2B organizations. With B2C, the funnel, conversion rates and overall marketing-sales process are different.)

Close Won Rate

This rate tends to vary the most because it’s based on the organization definition of an opportunity but it’s also extremely dependent on price.

I found several resources I could reference, but the one I liked the most came from CSO insights. In their annual industry benchmark report they asked companies “What percentage of your forecasted opportunities result in the following: No Decision, Loses, Wins.” The average for Wins was 38.8 percent. So I used 40 percent.

Leads to Opportunities

In SiriusDecision’s new Demand Waterfall model there are several stages for leads including Automation Qualified Leads (AQLs), Teleprospecting Leads (TQLs) and Sales Accepted Leads (SAL’s). For simplicity purposes and to make my model easier to calculate, I treat all leads as one bucket; a lead is anyone who submitted a form on a paid search landing page.

In most B2B funnels, this will be considered as an “Inquiry” or a “Known Name” therefore the conversion rate from that initial form submission to an opportunity, even if optimal, will still be relatively low.

I used Marketo’s benchmark numbers from their Marketing Automation ROI Calculator to calculate the optimal conversion rate from Lead to Opportunity and came up with 5 percent. To make paid search even more favorable, I used 10 percent.

Visits to Leads

The conversion rates of visits to leads vary greatly based on the source. Since we’re focusing on paid search, I was looking for data specific to paid search for B2B companies. I found three sources.

  • Optify’s B2B Marketing Benchmark Report. This report had paid search at a median of 1.96 percent, but the 75th percentile showed a 3.58 percent conversion rate.
  • AdWords Analysis (WordStreem Study) published by Jack Loehner. This study (no longer available on their website due to a change in Google’s API terms and conditions), looked at conversion rates for the top 10 industries, showed an average of 5.63 percent across all industries with the best performing industry (Internet & Telecom) at 6.27 percent.
  • MarketingSherpa’s 2012 Search Marketing Benchmark Report – PPC Edition. This report showed a median of 3.5 percent and an average (albeit huge variation) of 8.4 percent.


To make paid search favorable, I use the highest of the rates and rounded it up. I used 10 percent.


I found that using these conversion rates, to break even CPC needs to be .4 percent of the price of the product.

CPC = $X * 0.004


WordStream’s study also showed the average CPC per industry for the top 10 industries. I used those averages and the formula above to provide the price point for each industry at which paid search breaks even.


Use these break-even prices to determine if paid search is right for you. Remember though, that these break-even prices were calculated based on optimal B2B conversion rates. If your conversion rates are different (and they probably are), use them to evaluate paid search before jumping into it.

What About the Equilibrium Price?

Since the market conditions are far from being perfect, and at the heart of the imperfect market condition is the unavailability of information, it’s almost impossible to come up with the equilibrium price of paid search. CPC rates continue to fluctuate so keep an eye on your own break-even point and make sure you make the most out of each campaign.


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