One of the most misunderstood metrics that is bandied around by domain owners is the term Earnings Per Click (EPC). Everyone assumes they understand what it is but very few people have come to grips with how it’s calculated. In this short series of articles, I will pull apart EPC and show how it’s calculated so you can be in the know.

I was inspired to dive into this topic largely because I read a thread on a forum recently and it was clear that there were a lot of misconceptions about EPC that needed to be cleaned up.

I need to apologise for some of the maths in this series. The domain monetisation industry lives and dies by numbers and there's just no getting away from them. I should also say that domain parking is very much alive and well. The main reason for this is advertisers want our extremely valuable traffic.

So let's get too it! We need to define Earnings Per Click in terms of a mathematical formula….it’s initially not that complicated so don’t panic.

EPC = Revenue  /  No. of Clicks

This seems pretty obvious but we need to dig a little further into the definitions of both Revenue and Clicks.

When you look at your stats for a domain at a parking company you are seeing the AVERAGE revenue the domain makes across a period of time. The shortest period of time that can be viewed is one day but it’s still an average.

I’ve seen domainers complain continuously about the fact they seem to earn a large amount on one day and a small amount the next for a particular domain. There is a second factor that comes to play in this averaging process.

A typically parked page has up to ten advertisements being displayed and generally speaking the advertiser at the top paid more for their position than the advertiser at the bottom. For some market verticals the discrepancy can be really large with the top advertiser paying a large amount per click and the bottom advertiser paying pennies.

Everyone seems to assume the demand curve for a keyword is completely horizontal and yet this couldn’t be further from the truth. In some cases, there is a sharp drop off in the price willing to be paid by the advertisers for the domain traffic. An example price/demand curve could look like the one below.

The sharp drop off means the EPC paid would fluctuate greatly depending upon where a user clicked on the page. Typically speaking the higher EPC advertisements are placed at the top of the page and the lower paid advertisements further down the page…..but with Google’s move to psychographic targeting of users this isn’t always the case (and this complicates things immeasurably).

There is a different shaped curve for every market vertical and sub-vertical for that matter. This will greatly influence the dynamic nature of the EPC rates.

In the example above, a low traffic domain means fewer clicks on the page and the averaging would not be felt as much. This would create the wild fluctuations in the EPC rate that many domain investors currently experience.

For example, let’s imagine there was a single click on the page that paid out $10, this would mean the EPC was $10. Compare this to six clicks that paid $10, $10, $5, $5, $1 and $1 that would then have an average EPC of $5.33. In the first example if there was a click of $0.10 of then there is a large decline in the EPC but if there was a single click of $0.10 in the second example the EPC moves down only a little to $4.59. It’s a simplistic example but it shows averages at work.

One of the many challenges that all parking companies must deal with is bot clicks or even worse, fraudulent clicks. These clicks should be stripped out otherwise advertisers would be paying for clicks that have no opportunity to generate revenue.

Because all parking providers apply different filters to their click traffic the “No. of Clicks” or denominator can vary greatly from one provider to another. This also means you can’t compare one provider’s EPC versus another provider.

So now we have an approximation for the EPC and the formula will look like.

EPC = (Total Revenue Over a Period of Time)  /  (No. Clicks x Parking Company Filter)

In the next article in this series I'm going to really dive into the mathematics that make up the EPC and prove why conversion is so important for all domain owners.

Many people talk about having quality domain traffic but what does “quality” actually mean? In this article, I’m going to attempt to unpack "quality” and from who's perspective.

Domain owners often confuse quality as being a measurement of the level of real human versus bot traffic. On the other hand, advertisers define quality as traffic that converts for them. Who is right and are these sensible definitions for quality?

Recognised versus unrecognised traffic is the ratio of the views over the URLs for a domain name. Remember views are what the parking companies report while URLs are the unfiltered raw traffic for a domain. This is also the measurement of how much traffic is effectively dropped by a parking company as they deem it either a bot or unacceptable for one or another reason. The assumption is the greater the ratio of views to URLs the better the traffic quality.

Let’s imagine I have a views to URLs ratio of one (ie. A perfect score). There are a number of other filters the traffic flows through before an advertiser deems a traffic source as containing high quality. Let’s break these steps down.

A user clicks on an advertising link.

A domain with a high Click Through Rate (CTR) suggests there is an appropriate match between the traffic (ie. Users) and what is being displayed. The user is enticed to click on an advertisement to find out more information.

If the user was interested in games and the page had mortgage advertisements, then there is a mismatch and the CTR would reflect a lower number.

This sounds pretty obvious until we consider that a couple of years ago Google changed their advertising from being context sensitive to psychographically targeting the end user. In other words, previously if a user went to beds.com they would see bed related advertisements. This has now changed so that if I go to beds.com, it may also display hotels for Bali because Google knows I’ve been searching for a good vacation spot.

This also means we can't judge the content of a parked page simply by going to it ourselves....which is a little disappointing because it was so easy in the past to match the traffic to the advertisers.

Advertiser’s Website Convinces User to Begin Buying Process

After clicking on the advertisement, the user is faced with the sales pitch to entice them to buy the product. This is completely out of the hands of the domain owner that sent the traffic but is an important part of the overall quality process from the perspective of the advertiser. The goal is to have the user begin the purchasing process by adding the item to their shopping cart.

User Pays for the Shopping Cart

The advertiser only earns money when the user puts their hand in their pocket and actually pays for the shopping cart. Without this singular event no advertiser would ever buy any advertising. This is one of the reasons why advertisers regard converting traffic as quality traffic.

If we were to take these steps and create a mathematical formula, then it would look something like this:

URLs X Parking Filter = Views

Views x CTR X Click on Specific advertisement = Traffic to advertiser website

Traffic to advertiser X % Who Complete Purchase action = Shopping cart filled

Shopping cart filled X % of people that pay = sale

This means that a sale is a fraction of the total URLs that first went to a domain name. An advertiser is often blissfully unaware of many of the intermediate steps and focuses their attention on their total sales divided by how much they paid in advertising. This provides them the gross return on their investment. This is a simplistic view but it will do for illustrative purposes.

The problem with this whole process is quality is being defined in terms of sales. What happens if the advertisers pitch attracts the wrong type of potential buyer? What if the sales pitch on the advertiser’s website is really poor? What if the advertiser’s website just looks horrible and has a clunky shopping cart system?

There are so many factors that go into the sales event that are out of the control of the domain owner so why should the domain owner suffer? Ultimately it’s because the advertiser is the one that pays the cash.

So what can a domain owner influence? The only thing they can do is potentially increase the CTR by better matching the contents of a page to the advertiser…..but as we discussed earlier this has largely (not completely) been circumvented by Google’s psychographic targeting systems.

What some domain owners have done in the past is pick up their traffic and move it one hundred percent to a direct advertiser that will hopefully value it. For example, this means taking your travel traffic and pointing it at a travel website.

This all makes some sense until you look at things from the advertisers point of view. Previously, the parked page and clicking process effectively acted as a filter for those people who were interested in the products/services being advertised. Why would you click on an advertisement unless you at least mildly interested? By pointing all the domain traffic this filter is no longer in place.

If the advertiser was paying Google $2 per lead previously then they will be forced to place a discount on this to accommodate the disinterested traffic. This is very likely to trend to the CTR for the domain. Which is another way of saying, “I don’t want to pay for the people that didn’t want to click in the first place.”

If the CTR was originally 20% then the advertiser will pay 20% x $2 = $0.40.  This may be greater than what Google less the parking company commission was paying the domain owner for the traffic. So it may still be worthwhile for the domain owner.

Advertisers may pay more than this figure because they are after volume. Essentially it’s paying a premium to the domain owner because the domain owner can provide a large amount of business. This is a potentially a great result for both parties.

The problem most domain owners have is they don’t control enough traffic in any single market vertical to make it worthwhile to establish these secondary relationships. The advantage with working with a traffic aggregator is they can pool the total traffic from multiple domain owners and send it to individual advertisers. It’s the economies of scale at work.

This all brings us back to the definition of quality. It’s clear there are different definitions depending upon whether you are a domainer or an advertiser. Ultimately for true direct navigation there is no such thing as quality but only results.

The single biggest challenge that domain owners experience is we have very little insight into what domain traffic converts and what doesn’t. If this was provided in our daily statistics, then we could truly value our traffic from an advertiser’s perspective. Maybe we'll get this one day but I wouldn't hold my breath!

After publishing the article, “Getting Dirty in the Domain Data”, earlier this week I ended up having an interesting discussion with a domain investor. I thought that it would be worthwhile continuing to pull apart the data from the previous post to help many domain investors understand why optimising traffic across multiple monetisation solution is so beneficial.

I will be referring to the data from the previous article so you may wish to read it if you haven’t done so already.

Sampling by Changing the DNS

Many domain investors sample different parking providers by changing the DNS. This method is fraught with many problems that largely stem from comparing results from single sources across different periods of time. Some of the challenges are:

1.      What are you measuring?
Revenue is not a good measurement of success as there will be different levels of traffic at different points in time. Since parking companies count traffic different you can’t rely on the produced Revenue Per Thousand Visitors (RPM) numbers.

2.      Data Distortion
When testing different parking providers over different periods of time you can get massive distortions in the data from seasonality in both the domains and the time of year. In the example from the previous article the domain had massive results in May to July due to it being a travel related domain.

3.      Traffic Leakage
There is a propagation delay each time you change the DNS and this creates more traffic leakage and no new information. In some extreme cases where the TTL (Time To Live) for the domain is long the DNS may not update for months for some users.

The Cost of Information

Some investors believe in splitting traffic equally across multiple solutions and then at some point in time sending all the traffic to the monetisation company that pays the most. This is one of the worst ways to optimise domain traffic and here is the reason why.

There are a lot of strategies around sampling but they basically boil down the single question, “What did the information cost?” In other words, if I was earning one dollar with one company and then sampled another company and found they were paying 90 cents then the information cost me 10 cents.

Minimising these "information costs" is crucial to optimisation. From the example domain, A.COM, in the previous article if we sample the traffic equally across the different parking companies then the portfolio would have earned $1611 versus $2217 or 38% less overall (ignoring direct advertisers).

Every domain needs its own sample regime. At the most simplistic level domains with less traffic should be sampled less often compared to domains with high levels of traffic. In each case, what you are after is a statistically significant result that allows you to decide where to route the traffic. If you don’t have a statistically large enough sample, then you’re guessing.

Real-Time Decision Making

All traffic routing decisions need to be made on a real-time basis. Based upon the data, decisions need to be made literally milli-second by milli-second. I can only speak for my company, ParkLogic, as we use dynamically changing data from multiple inputs to alter not only the routing decisions of traffic but what is displayed on the page and ultimately which advertisers are engaged.

As an example, we track over 250 different metrics for every domain every day and process this data to alter how the traffic is routed. Layered over the top of this daily data we then can then incorporate external dynamic data such as geo-based weather.

Everything must lead to a decision....otherwise it's just intellectually interesting but pointless.

Winning Solutions Constantly Change

If you sample other solutions (however you decide to do it) and then lock that solution in for an extended period of time, then you will be losing. The data from the previous article clearly shows that even for a single domain the winning parking company changes constantly (see below table).

For example, if we routed ALL the traffic through to Voodoo (average winner) and applied Voodoo's payout rates each month then Voodoo would have paid out $436 for the ten-month period. The domain actually earned $4531 for the same period of time (including direct advertisers). The reason for this was a combination of an advertiser paying a lot for the traffic in May-Jul and other parking solutions beat Voodoo the majority of the time.

This doesn't mean Voodoo is bad....as they actually did win for a couple of months. Remember the data is summarised on a monthly basis and can only testify to the fact that the same behaviour exists at the daily and even changes milli-second by milli-second.

Benchmarking Results Must be Done Simultaneously

I mentioned this point briefly when discussing the problems with sampling via DNS but it is important to reiterate it. Testing new solutions must be conducted at the same point in time otherwise distortions in the results will occur and incorrect decisions made.

Let’s imagine I used the domain’s revenue results in June as the baseline data and compared this to any new parking company in September. I could erroneously conclude that the new company was hopeless! Remember that A.COM (in the previous article) is a travel domain and has extraordinary performance in June.

Understanding Data

I’m in a discussion right now with a customer where about one hundred of their domains just aren’t performing. I’m not worried about this customer leaving ParkLogic as we are both working through the data to understand why their performance is down.

Too many domain investors immediately bail on their existing partner and whip their domains out somewhere else in the vain hope they will perform better. This syndrome has a saying, “The grass is always greener on the other side of the fence.” In other words, you will always think somewhere else is better than where you are.

My advice is don’t do a knee jerk reaction and move your domains. Sit down and dig into the data and really understand what’s going on with the traffic. We are in an industry that is built upon data and if you wish to get abnormal returns then it’s vitally important that you get your arms around it or work with a partner that can help you do so.

I hope the few items I’ve raised here in this article will help give you a fresh perspective on your own domain portfolio. Over the years I’ve found that earning more from domain traffic is not always the solution that investors are after. What they want to know is they are maximising their returns and there is proof that this is being done.

Anyone can have a good or bad month but knowing that there are systems and experts in place that are monitoring and understanding the results is really where it’s at. This is particularly the case if you must report to investors or a board. Having the data to confidently know that everything that can be done is being done often alleviates the concerns of the most aggressive directors!

We’ve recently been working with a client to better understand the underperformance of a number of their domain names compared to a few months earlier. What we discovered when we conducted an internal forensic analysis of the data was quite surprising.

The domain we will look at in this article has been renamed to A.COM for privacy purposes. Since the beginning of the year it has had a monthly revenue ranging from $183 to $1221 and a normalised RPM (revenue per thousand visitors) of $75 to a high of $488. So what was going on with this domain?

Upon closer inspection we found that A.COM was a domain from the travel industry. People were looking for the services the domain offered from May to July and this dramatically pushed RPM rates higher as advertisers competed more aggressively for the traffic during this time. In fact, the peak numbers were achieved by a direct advertising travel company.

So let’s imagine you bought the domain based on those very high July numbers? It wouldn’t be long before you discovered your investment was under water as the typical monthly revenue retreated to 20% of the peak! Our client isn’t unscrupulous so they would never do this…..but always remember, buyer beware!

So now we know we are dealing with a domain that is seasonal but the second question that needs answering is whether it is being properly optimised during the entire year? The only way to answer that question is to look at where the raw traffic was sent and examine the revenue it generated.

The first table below shows the traffic sent to the different monetisation providers (Ad networks are aggregated) over the period of twelve months.  Remember this is the raw unfiltered traffic and is not impacted by any filtering algorithms the different monetisation providers may apply before displaying the views in their interface.

The two letter codes at the tops of the columns represent the parking companies the traffic for this domain was sent through to. In order they are; Sedo Domain Sponsor, Voodoo, Bodis and Parking Crew.

The second table is the Revenue the traffic generated from the above traffic and the third table is the normalised RPM. Don’t forget the definition of a normalised RPM is the revenue divided by the raw traffic multiplied by one thousand. This metric will allow us to accurately compare one monetisation provider against versus another and know beyond a shadow of doubt who is performing the best.

For simplicities sake, I’ve removed all mention of the direct advertising networks from the Winner table and concentrated on the traditional parking solutions that were sent traffic.

Starting in January this year we can see that Voodoo was winning with normalised RPM (nRPM) of 68.94 and close on its heels was Parking Crew with $65.69. Logically, Voodoo received the lion share of the traffic followed by Parking Crew while Sedo and Domain Sponsor received enough for sampling purposes.

In February, circumstances have really changed with Sedo shooting to the winning position and snagging a lot more of the traffic for both February and Mark. And so it goes, month after month we can examine the numbers and see who is winning the traffic at every stage until we have the below table.

Sadly, for A.COM, Domain Sponsor wasn’t the overall winner in any month but it’s not uncommon to have one monetisation company not win for a long time and then suddenly spring up. What is clear in the tables of data is that the “winner” is constantly moving. I didn’t do the analysis but my guess is if I got down to the daily level then the flow of traffic between winners would be even more dynamic.

So how did this analysis help the client? They needed to report to their board with confidence that everything that could be done was being done to optimise their domain traffic to the highest paying solution at any point in time. This data proved this was the case.

The data also provided them with the necessary information to back-up the supposition that some domains fluctuate all over the place. It’s one thing to suggest seasonality or variability and quite another to prove that it’s the case. Once again, the data provided the necessary information to support this hypothesis.

The final question that needed answering was whether A.COM was actually performing less than twelve months previously. The answer was a resounding no. The RPM twelve months ago was $115 while now it was $146. What triggered the investigation was the previous month the RPM had dropped to $95. Remember it’s a seasonal domain, no one wants to purchase travel services at the end of summer. So this domain clearly experience a post-summer slump and then quickly rose out of it.

So analysis is a lot more than just mobilising a lot of numbers. It’s also about interpreting what they are telling you about a domain so you can understand whether you are actually getting the best performance at any point in time.

I’ve been asked a lot of questions by readers on the topic of traffic optimisation and I thought that it would be worthwhile diving a little deeper into some of the metrics that underpin all our traffic monetisation earnings.

To fully understand click through rate (CTR) we need to take a look at the formula.

CTR = (total number of clicks) / (total views) x 100%

Both of the measurements used in the CTR formula are subject to various levels of filtering. For example, is the “total number of clicks” the actual number of clicks on advertisements or the number of clicks on advertisements within a specified time frame? Or is it actually the number of clicks within a specified time frame for a particular IP address? Or is it the number of clicks within a specified time frame for an IP Address/Cookie combination?

Different companies will count clicks differently and there isn’t really much we can do about this. I have unpacked views in previous articles but it basically boils down to:

Views = (Raw Traffic) x Factor

The factor is a wide range of filters that are applied to the raw traffic by monetisation sources to strip out everything except traffic that is actually monetisable. Since there is no industry standard definition for views this metric will vary greatly from one parking company to another. This does not mean that any of the parking companies are behaving in a fraudulent manner but it does mean they count things differently.

So given the fact that both metrics used in calculating the CTR are completely subjective is there any point in looking at the CTR? Let me say that comparing the CTR between companies is a lesson in futility but comparing the CTR over time for a domain within a single company is actually worthwhile.

The CTR is actually a measurement of user intent. If a domain has a low CTR then it invariably means the parked page has little relevance to the desires of the traffic visiting it. So from an optimisation perspective we want to match the traffic to the page results as accurately as possible. In many respects Google gets this pretty right but there are always cases where Google gets it completely wrong and keyword optimisation comes into play.

With the introduction of CAF (Custom Ad Frame) by Google a number of years ago it essentially means that Google now serves the parked pages. You only need to do a “view source” to see that this is the case. What Google did was mimic the various parking provider’s templates and then they serve the pages themselves. The CAF strategy was driven by Google trying to stamp out fraudulent traffic – and they largely succeeded.

What this also means that when you set a keyword Google largely views it as a serving suggestion. Setting a keyword does not guarantee that Google will use that particular keyword for your domain.

Many years ago some domainers quickly realised that by setting mortgage keywords for all of their domains they would get awesome earnings per click but really low CTR. The huge EPC rates more than offset the decline in CTR. This is one of the reasons why Google doesn’t completely allow you to set keywords anymore…..they want to provide a better user experience (ie. CTR).

Earnings per click (EPC) is exactly what is says, how much money do you make for each click.

EPC = (Total Revenue) / (Total Views)

This formula seems pretty obvious until you begin to dig into “Total Revenue”. The total revenue for a domain is influenced by many different factors, including:

• Google tags at the parking level to encourage parking companies to maintain quality
• Sub-tags where a group of accounts at a parking company will be evaluated on their quality
• DRID (Domain Registrant ID introduced by Google at CAF time) – are you a good player or not?
• Clawbacks (often known as advertising credits)
• Account adjustments

A lot of these different metrics are wrapped up in the phrase “smart pricing”. In other words, has your domain/account been smart-priced up or down? This will all contribute to influencing the EPC.

But at its core, what is EPC? EPC is the measurement of advertiser demand on the Google advertising exchange. It’s a position on the supply/demand curve where if there is less supply the EPC goes up or if there is less demand for the same volume of traffic the EPC rate goes down.

If you ever see an EPC rate that suddenly jumps up, then it’s typically the result of a marketing manager putting the decimal point in the incorrect spot for a bid. Don’t get too excited, just enjoy the increase and expect it to fall off as their budget is quickly consumed…..with any luck you won’t get a clawback!

What we should also appreciate is that advertisements higher on a parked page get paid more than those lower down the page. The spread in EPC rates down the page will really depend upon the number of advertisers bidding for the traffic (think of it like market depth with shares).

Don’t forget that EPC is implicitly a measurement across a period of time. When you look at your parking company stats the lowest level of data you can view is the EPC rate for a day. I’ve said this before but it’s important to recap…..what you are viewing is an average EPC rate. This is vital in understanding how to optimise domain traffic.

So ultimately what domain investors want is a high CTR (user intent) and a high EPC (advertiser demand). The best way to achieve this is to examine the data, "suggest keywords" and then revisit the changes you've made......which is a LOT of work.

In my time as the vice-chairman of the Internet Industry Association of Australia I had the privilege of chairing the committee for setting the online advertising standards for our nation. There is one thing that I learned from that experience, fully understanding the definitions driving the metrics is mandatory if you wish to grow your online advertising based business.

Anyone that earns money from monetising their domain traffic should spend a considerable amount of their time not just looking at their numbers but interpreting what they mean. The only way you can do this is to understand the definitions. I hope this article has helped you out on your journey…..BTW, definitions can also change over time….so beware!