Discussions and blogs that relate to the monetisation of domain traffic.

Maximising Domain Revenue

Maximising Domain Revenue

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.

Escrow.com

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.

Winners

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!

Greenberg and Lieberman

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mgilmour
I agree.....we take that responsibility on at ParkLogic and aggregate all payments into a central single monthly payment. This is ... Read More
01 November 2016
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Getting Dirty in the Domain Data

Getting Dirty in the Domain Data

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.

Escrow.com

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.

URLs

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.

Winners

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.

Greenberg and Lieberman

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Wolftalker
Congrats on good detective work.
25 October 2016
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Part 9 - Portfolio Management - EPC/CTR May Not Be What You Thought

Part 9 - Portfolio Management - EPC/CTR May Not Be What You Thought

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!

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Part 8 – Portfolio Management – Traffic Domains

Part 8 – Portfolio Management – Traffic Domains

The current series of articles has really provoked some interesting discussions with a number of domain investors. What I have noticed is the high level of emotion that surrounds the whole domain traffic and optimisation debate. Many people have leapt to conclusions rather than look at the data and try to understand what it is saying.

Let me say once again that domain monetisation is not dead. The reason for this is genuine domain traffic contains valuable leads for businesses and advertisers are more than willing to pay for those leads. The goal of optimising your domain traffic is to best match the right advertiser to the right piece of traffic at the right time.

Like any industry, the advertising buying market is very dynamic with wide ranging payout levels at different times during the year, day and even sometimes second. So when I talk about optimising domain name traffic we need to really be as close to real-time as possible. Given the volume of data, the only way to route traffic to the highest paying solution is via algorithmic switching. So is all of this work really worth it?

I recently published some numbers over at the NamePros forum and I thought that it would be worthwhile digging into them here. For full disclosure I should state the data is from my company ParkLogic and we use algorithmic switching of domain traffic.

The data is real and was used as a part of the optimisation process for a particular client. Results for new clients will vary depending upon the optimisation levels and the domains in question.

ParkLogic Results

What the screen capture shows is if we saw at least 100% of the baseline traffic (ie. The same) then we provided a 184% uplift in revenue. At least 80% of the traffic we provided a 162% uplift and for the entire portfolio there was a 127% uplift versus the baseline. In other words, if we saw similar levels of traffic to the baseline data then we knocked the results out of the ball park.

The baseline data came from a portfolio that was currently being optimised across multiple monetisation solutions via Above.com. I have nothing against Above as ParkLogic provides an entirely different service compared to them.

Just for the record, there were some domains where the baseline outperformed our results. This could be for statistical variations across time etc. We would recommend to any client where the baseline outperformed ParkLogic to take those domains away from us and re-baseline them to ensure the results hold true. ParkLogic does NOT win for every domain ALL of the time (versus a baseline) but I can say that we DO send the traffic to the winning monetisation solutions at a particular point in time.

What the data clearly shows is when you apply a level of discipline to optimising a domain portfolio that we do then the improvement can be considerable. The problem is most people try to optimise their portfolio themselves and have convinced themselves that they are saving money in fees.

This is a false economy because the data clearly shows that any fee would be more than covered by the uplift. In addition, the fact that you now have all of your time available is a huge saving in itself!

I don’t normally toot my own horn but ParkLogic really knows its stuff. We’ve been optimising domain portfolios for nearly a decade and when someone comes along and says they’ve built their own optimisation system it’s hard not to roll my eyes. Over the years I’ve heard many approaches……everything from DNS round-robin through to an automated system that leaves traffic at one place for a few days and then moves it to another for testing. I hate to say it but all of them are sub-optimal.

As an example, let’s tackle something really simple, incorporating zero-click real-time bidding (RTB) solutions into the traffic stream. Essentially RTB platforms let you poll them for what they are willing to pay for a piece of traffic. So they may come back with 12 cents as an answer. If you look at the traffic for a domain you may have an earnings per click rate of 10 cents and immediately jump at the 12 cents…..that is actually a really silly thing to do.

What we need to understand is that the 10 cents that is being earned at parking companies is an average across a period of time (typically a day) while the 12 cents is at a point in time. In other words, the 10 cents could be made up of a 20 cent click, a 5 cent click and a 3 cent click which provides an average of 10 cents.

What you don’t want to have happen is the RTB networks take the 20 cent traffic and pay you 12 cents while leave the 5 and 3 cent traffic behind. This would effectively reduce the yield from the traffic. So after around 6 months of testing various methodologies we worked out a system for incorporating RTB networks in an effective manner.

I know this was a simple example but it does give a glimpse into some of the complexities around routing traffic to the highest paying solution. It also illustrates that if you get your maths wrong then you could lose your shirt!

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Part 7 - Portfolio Optimisation - Running a Traffic Test

Part 7 - Portfolio Optimisation - Running a Traffic Test

So you’ve just been to The Domain Conference in Fort Lauderdale and a monetisation company convinces you that you should run a test with them. Is there any real point and what is the best way to do this?

If you’ve ever moved your domains between parking companies by changing the nameservers then you will very quickly realise that there are so many variables to consider that the test becomes meaningless. For example, by routing the traffic at different periods of time, traffic volumes and domain market verticals all contribute to distorting the results.

In addition, if you move all of your domains across to the new company then from the previous article in this series we now know the best case scenario is they will win 35% of the time. Remember this number is for a properly optimised domain portfolio. If they win more than that then it’s only because your portfolio has not been looked after.

All monetisation companies know that they will perform well on some domains and not so well on others. Their goal is to hope and pray that overall the total amount they pay you will be more than your current parking solution.

From the domain investors perspective this is a really silly way of looking at things. What you actually want is to leave all the domains that win with the new company with them and automatically move all the domains that do worse away. This then maximises your earnings.

The ideal solution would be to keep all of your domains where they are and then send a percentage of the traffic to the new company for testing. This process allows you to accurately benchmark the new deal with a greatly diminished risk, compared to sending all of the traffic for your domains to the new company.

Earlier this year, one of ParkLogic’s customers had just returned from NamesCon and they were approached by a couple of the parking companies to run a test. Rather than move all of the domains away from ParkLogic they had a chat with me and we then routed a portion of their traffic to special accounts setup for them at the new companies.

They then were able to assess down to the cent on each domain whether the new deals were any good or not. In the end they moved everything back to their ParkLogic controlled accounts as they performed better than the specially setup ones. I should say that we were very happy to facilitate this process for our client as we regard it as one of the services we provide.

This structured process provides domain investors and any of their investors the confidence that everything that can be done is being done to maximise earnings. There’s no “grass is greener on the other side of the fence” as we absolutely know what the grass looks like and tastes.

Ultimately what you need to assess is your stomach for risk or in other words, how big a percentage is good enough? We typically find that forcing around 20% of the traffic for each domain over a couple of weeks (time depends upon traffic levels) gives a good enough sample. If the new company wins then you should move 100% of the traffic across to them…..and this is what we do. If a few weeks later they don’t perform as well then we automatically migrate the traffic back to the winning solution.

So after going through this process, what constitutes a win for the new company? You can’t use revenue as the traffic will have varied for the domain and distort the result. The only measurement that you can use is the normalised RPM.

Remember, we discussed this in a previous article. A normalised RPM involves measuring exactly how much raw unfiltered traffic we have sent for a particular domain to a particular parking company. We then measure get the revenue generated from that traffic. For a domain, mathematically this looks like:

(revenue at a parking company) / (total traffic sent to the parking company) x 1000

This then means that for every domain we will typically have the normalised RPM for every monetisation solution at any point in time…..yes, that’s what we do. In fact, we collect around three hundred different metrics for every domain every single day.

So when we were assessing for a client whether the new companies were performing better we we’re not looking at the revenue. We are looking at the normalised RPM because this metric tells us if the grass is actually green or brown. Given the process we also know the colour of the grass for every solution at any point in time.

So let’s imagine you’re not with ParkLogic and you don’t have any baseline normalised RPMs. For many clients we typically integrate their current monetisation account into the system. They change the nameservers to ParkLogic and we then route 100% of the traffic back to their existing provider.

By going through this process there won’t be a drop in revenue and it allows us to establish a baseline normalised RPM that we can measure any new solutions against. We then test a portion of the traffic elsewhere to see if it will perform better at other solutions. The whole time we are keeping an eye on the normalised RPM. It isn’t long before we see an uplift in the overall revenue.

This is the proper way to conduct a traffic test as it provides definitive performance data that is accurate. I hate to say it but any other methodology will largely be guesswork which is likely to end up with a suboptimal result.

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