PPC Management
What is CPC?
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.
Results
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.
resource:http://searchenginewatch.com/article/2255282/How-to-Estimate-the-Break-Even-Point-of-Paid-Search
