Testing Ad Location Is Powerfully Beneficial

The Benefits of Testing Ad Location

1. BETTER AD COMBINATIONS ON ALL PAGES = More Money

This is probably the one everyone is most interested in, right? Showing ads in the right place, at the right time, can double your monthly ad income.  But why is this?

Testing ad locations or – putting it more correctly – ad combinations (which combination of ads to show a user in certain scenarios- which could be different on each page of a site) is fundamental in determining a site’s ability to generate strong ad earnings.

Everyone knows that it is important to show ads that are prominent enough to make maximum ad revenue but many don’t understand how important it is to avoid spamming away users. Additionally, it is very important to understand how users actually use your site and interact with the ads available.

Every user on a site interacts with it differently and different locations may influence each user in a different way. When you start to think of it this way, testing ad location becomes kind of intimidating. How is it possible to truly optimize in light of all these factors?

ad position testing equals more ad earnings

In our research (that has included over 21,000 sites), we’ve found that testing ad location testing is extremely powerful and actually solves the ‘UX vs Monetization’ problem. The problem being how do you maximize both with our taking away from the other.

Testing thousands of ad combinations (where the ads are located on each page and how ALL those ads affect the total session income), is the only accurate way to keep ad income on an upward trend and keep user experience protected. This level of testing truly is able to account for all factors and can allow sites to balance UX and monetization.

ad location - testing ad positionWe’ve been able to prove this out over time. There are simply to many combinations and variables to account for in traditional A/B (or manual) ad location testing models. Site owners must employ a form of multivariate testing.

Automated testing means you can leverage vast amounts of user data and never have to rely on personal opinion to decide upon where the ads should go… (which is how 99% of websites still choose their ad positions).

testing ad locations

2. You’ll have Science on Your Side

With the +21,000 sites we’ve collected data on, we’ve found that testing ad location for session based optimization always beats RPM-based optimization. What does this mean?

The reason ad testing has become an absolute necessity is because a lot of publishers – even sophisticated corporate publishers with substantial digital incomes – still hold onto the mistaken belief that optimizing revenue is done by boosting page yield (trying to increase RPM or eCPM).  This, unfortunately, is totally wrong.

RPM-based optimization is fundamentally flawed because it treats all pages with equal weighting and is based on the assumption that if you get the maximum ads on every page, then you’ll always be making the most that you can from a website. Site owners know deep down this is true.

This is a fairly popular opinion, but it’s a totally false assumption.  Take a look at the math HERE – it’s easy to see why this doesn’t work.

testing ad location

To summarize this point more simply:

Users who see too many ads too early in a user session are more likely to bounce away from the site.  

test ad location

Visitors who bounce away from your site engage with fewer ads overall.  Fewer ad views overall means fewer ad dollars and reduced income, instead of boosted income.

So, how is it possible to balance user experience metrics against ad income?  The answer comes from scientifically testing and improving ad combinations and recording the users’ responses to those changes. This cannot be achieved accurately ‘by eye’ / guesswork.  Testing is the only way, because all sites are different.

Most importantly, testing consistently. It is vital that multivariate testing be performed on a consistent basis to ensure that the site remains optimized. This must be done using some form of ad testing automation because a human is physically unable to do this level of testing in a timely manner.

test ad combinations to stop earnings drop

3. Testing Ad Locations Boosts Ad Quality = Happier Advertisers 🙂

Good science (when you’re making decisions based on good data with statistical confidence), dictates that testing ad location is dynamic and never ending.  Getting ads in better positions over time means engagement improves and the traffic quality – from an advertisers’ perspective – is good (in other words, they want more of those ads and will pay more for them too!)

Great ad testing measures earnings & user experience together.  We’ve found that to do testing well and boost ad quality, you need to find and optimize the combinations of ads that maximize revenue by taking into account thousands of variables.

Here’s a list of the variables that Ezoic A.I. uses to make ad location decisions:

  • The effect that other ads on the same page have on all the other ads (same page)
  • The size of each ad
  • Position on the page (above the fold/below the fold/sidebar/below menu etc)
  • The previous ads seen by a user earlier in their user session
  • Their geographic location
  • The effect that ad color (AdSense Text ads) might have
  • The traffic source (where a visitor was before they came to your site – visitors from Google/Facebook optimize differently.
  • Time of day / day of week
  • Device / viewport size
  • RTB / Yield optimization factors (eCPM of the ad)
  • Viewability Score
  • Ad type – display vs native vs In-line and how they dilute one another’s performance.

and perhaps most importantly:

  • Which page the ad is appearing upon (how interested the user is in this page has a huge effect on ad earnings / ad quality to the advertiser)

As you can see – it’s a mammoth task to attempt to work this out manually – or trying to A/B test.  It’s a matrix of decision making that feeds into boosted earnings, boosted UX and, ideally, both metrics at the same time.

Ad quality relies on boosting visitor engagement or ‘intent’.

Visitors who are really reading and engaging are better for your advertisers.  One of the biggest factors in ad testing is making changes according to ‘traffic source’.

Optimization for ad quality improvement is a constantly moving target.  For Example: A desktop user in London, on a Sunday evening, arriving from a Google search term, reading ‘Article A’, will need a different ad combination to a mobile visitor located in New York, on a Monday Morning, arriving on the page from a Facebook post to ‘Article B’.

example of why sites need dynamic locations
Article page (which page a user is reading), traffic source, geographic location all have a marked effect on what ad combination should show.

There is no reason why all visitors should see the same ad combinations. Each user should get an ad combination that complements the page they are reading and enhances their overall user experience, taking into account upstream traffic sources, device size, geographic location and any other factor that can boost user engagement and ad earnings.

4. Testing Ad Locations Cures Ad Blindness

Google’s advice to digital publishers to overcome ad blindness is by blending, contrasting and complementing ad colors:

ad location testing ad color
This is of course fine.  But we’ve found that this will only get you so far.

It’s much more powerful to do those tests AND test ad locations and sizes in combination.  But, for those of us who are busy – this all sounds like a lot of work.  The main reason most people / businesses don’t keep going with testing is that it is a super-laborious process if you’re doing it manually.

ad location

If you’re not measuring ad performance throughout a user session, then making changes for ‘overcoming ad blindness’ – it’s going to be a thankless task.  Automated ad testing solves all these issues and means you can spend more time creating content.

5. Testing Ad Locations Generates Huge Amounts of Data

That data can be used to improve your content generation (which means happier users and even more money!)

Knowledge is power! Testing ad locations automatically means you’re about to know which articles or pages make you the most money, and which get you the most engagement from your site’s visitors.  When you have that data – you can create more and more popular content.

Testing ad location will give you results that show you income per session for different landing pages.  Knowing that you produced a poor article with a high bounce rate and low engagement rate will help you improve as a producer of content.

If your writers get a bonus each time they produce a viral hit – that can help you retain star writers.  All of this is possible only IF you have the data.

ad location
Which Article should you promote next in your newsletter?   Ad Testing data will tell you the bounce rate, page views per visit, session duration, traffic source/utm code, geo location and the all important EPMV (earnings per thousand visits).

Most publishers do not measure the engagement of each article or how much ad income it makes.  The data from testing Ad Combinations shows you which articles make you the most money.

Some articles are inevitably going to be more engaging than others – having the ‘right’ ad combinations or ad locations on the page will enhance the user’s experience of that article AND boost ad earnings.  Which writer on your team produces the highest yielding articles?  That’s something that’s important to know.

Summary – 5 Benefits of Testing Ad Locations (or reasons why you should adopt dynamic ad locations)

Generate more money by testing ad location. You can create scalability from using a scientific/math approach to testing for overall income improvement.  It’s good to have fresher ads and better ad quality which in turn boosts eCPM’s.  It is also beneficial to always show the correct ad for the screensize, which reduces ad blindness.  And finally, and maybe most uniquely, ad testing generates a ton of useful data that you can use to help curate your content strategy.