Optimization is a art form, I like to use the analogy that if you give 3 accountants the same exact information for taxes you will inevitably get 3 separate numbers in the end wit the same laws all being CPAs, it like that for optimization it not an exact science, you will have to develop you own skills and style that works for you - Brian
Now we begin with the fun stuff.
The secret sauce to making money is optimization.
This is what separates the men from the boys in terms of making profit.
You can have the best ads and landing pages in the world and you'll find that people like to "swipe" them.
But what makes you unique is how you optimize and run traffic.
This is not something people can't spy on.
This is why you don't see many people talk about optimization except maybe if you're paying them.
There's been times along the way when I've lost money out of gate on a campaign and was unsure what to do next.
With practice you'll find ways to make that campaign profitable through optimization.
This skill you will develop will take a campaign that is losing to one that is making money.
The majority of your campaigns will start out unprofitable.
When you first launch a campaign, you're going to use all your knowledge and spy tactics to hopefully get something that's close to working.
The truth of the matter is though, if you don't get the data to back up your theories then you really don't know.
The first thing you need to do is launch a campaign.
Then you're most likely going to lose money while you're "buying data"
Then you analyze the data
Then you split tests or run experiments to get your campaign profitable
Which one looks like it's more profitable?
In your campaign they're going to want to look at a lot of different parts and compare what is making the campaign make money or making the campaign lose money.
Let's imagine you're an appliance salesman and you're not getting very good results when you're first starting out.
You can test different ways of closing the sale.
You can test different approaches when you walk up to people.
You can even test your clothing you wear to see if that makes a difference.
There's an aggressive approach or laid-back approach for example.
What you're doing is you are testing to see what works and what doesn't. That's the key and in affiliate marketing you must keep testing.
The name of the game here is to test and get profitable before you run out of money.
A big newbie mistake is to think you're going to be profitable from the get-go and immediately run out of money.
Losing money is not something that you need to worry about you need to consider that it’s a tool to buy data.
We mentioned earlier the need to put a budget aside for testing and not become attached to that money.
You will find overtime that you build campaigns not discover them.
Throwing stuff against the wall and hoping it sticks is not the way to approach affiliate marketing.
You're not really learning anything. If you happen to hit a profitable campaign it was sheer luck and most likely competitors will be doing the same thing.
You're not mastering a niche. You're going to want to master a niche and become one of the top affiliates in that.
The top affiliate in every niche makes the most money.
Don't overlook potential gems. We've had campaigns that started off on profitable and turned into a 100k months.
Optimization is where you just test out certain parts of the campaign until you figure out what the audience really wants and slowly over time it will become more profitable.
Here's an example
My top 3 Optimization Rules
Test one variable at a time as a newbie
Think of your high school science class.
I can remember a pretty simple test A vs. B. If you test too many things you really don't know what's causing the change
Let's not overthink this. Remember earlier we said test the offer the best offer test the landing page while keeping everything else the same.
More advanced affiliates can do things with different software, like multivariate testing. We talk more about this in advance training.
2. Make sure your data is valid statistically.
If you roll the dice 2 times and you land on 1 both times does that mean it's going to hit on one every time?
The answer is obviously no.
If you roll the dice enough times you'll see a 6, 5, 4 etc and likely average one 16% pf the time. (1 divided by 6)
This is what we call statistical significance. With enough rolls you will start to get an accurate data sample.
We need to make sure when we run that we are getting accurate data and a large enough sample.
3. You need to focus on what is having the biggest impact.
Companies like Amazon test things like call to action buttons on a grand scale.
For affiliate marketing purposes, something like the call to action button could have a difference, but more than likely something like a good headline or hook will make a lot bigger difference.
Focusing on what is going to make the biggest difference from the beginning start to narrow down your split test.
You want to create a systematic list overtime starting with say the offer, headline, the image, the landing page. Not necessarily in that order but over time to develop this skill set.
Generally, when you have a larger budget you can run more tests
Let's look let's look an example of a $1,000 a month budget. Tracking tool cost $49 a month, your hosting will cost you about $49 a month.
That leaves you $900 to test with. If you're running on expensive traffic like Facebook you could be paying $2 per click and that's only about 450 clicks.
It will be tough to pull a significant split test and optimization with only 450 clicks.
So, some options are look traffic and lower your cost per click, or increase your budget.
Let me give you some examples of split test in affiliate marketing.
1. I like to start with age groups when I advertise.
When I'm promoting a New Year's Event or Halloween event I start with age groups to figure out which one's the most profitable.
The above example is a super basic split test ages 25 to 30 verses 31 to 35.
The control variable = I would keep the same or the controlled variable are the images and ad copy.
The independent variable = are the ages on testing (what I changed).
The dependent variable = this is the value that changes when you get the new data. For example you're going to want to look at the click-through rates, the cost per click, and the profit.
In My New Year's example event sample, I'm testing:
That pretty much covers my age demographic for the event. Of course, there might be some youngsters that try to sneak in with a fake ID, or some couples that are older than 35, but the bulk of my attendees will be in that age range. (I know from past experience)
So far in my recent campaign the 26 to 30 range is winning the race.
One important thing to remember here is if you're not making money at this stage that is okay.
You are trying to find which segment is the most profitable. Once you determine that you can test other variables such as ad copy, angles, offers, landing pages, Etc
All this in an effort to get the campaign profitable.
In the above example I may spend the majority of my money on conversion traffic in the 26 to 30 age range. (Conversion Traffic is the most expensive traffic typically, these are potential people that are the most likely to convert)
See it's really not that complicated.
2. Testing mobile campaigns operating systems
I've launched many mobile campaigns depending on the offer typically Apple or Android will perform better.
I can remember running a mobile antivirus campaign that performed very well on Android, but did not perform well on Apple.
Recently I ran a direct link campaign that performed very well on Apple and lost money on Android.
Definitely, something you should split test on mobile campaigns.
In your click tool tracking software you will be able to separate out your operating systems and filter out the ones that are not making money.
There are literally hundreds of optimization tests you can do.
As a beginner focus on these three:
Split test the offers
Test out different landing pages
Try different ads and angles
These are typically your most important elements for all your new campaigns.
At the end of the day it's going to come down to how much budget you have versus how many tests you can run.
We obviously have a large budget team I have spent the upwards of $20,000 to find out if a campaign has potential to be profitable.
The more offers you test the more chances you have of getting a campaign that is profitable.
Is this all making sense?
If you have a limited budget your plan has to be strategic.
List of Optimization Variables
This is one section that gets a little bit more complicated.
We launched campaigns before where I've lost a hundred percent off the gate but we were seeing some conversions. So at the point we know that the offer is valid.
Let's look at the list of things we can test, obviously there are more things here that I'm going to mention:
Site IDs / Site placements
Work on the elements of the most important and that should be the order for your split test.
Depending on the traffic source, your testing priority may change, Facebook is much different than a lot of Mobile Traffic sources.
Example on Facebook you can test males vs. females but on a mobile network you can’t.
My mindset when I optimize campaigns
We had a recent example that I want to share with you, one of my media buyers was testing offers on ClickBank with Facebook traffic.
He found an offer that was about minus 100% ROI out of the gate.
He stuck with it for about 4 days until he had it breaking even.
In one week it was making $2,000 a day, and now we have it in multiple business managers making around $5000 a day.
That was with very little split testing, and we are improving on that every day.
The first day like I mentioned before, we were testing the offer.
We had some conversions so we knew the offer had potential.
We changed some things with the images and the ad copy.
We actually started with some test - direct linking to the Video Sales Letter(VSL) and then we ran some tests with landing pages.
All the direct link how many pages were working, but over time we found the landing page was more effective.
Once we figured out that was the best option we started split testing components of a landing page.
Well the result at the time of this writing, well we crushed the $300K month!!