Affiliate marketing is performance-based marketing. More sales mean more earnings but between the starting point and the profits, there is a journey filled with hidden traps.
There are many dilemmas you need to face while starting your journey with affiliate marketing. But once you’ve gone through the basics and your campaign is all set up, there comes a moment when you need to optimize your campaigns. And this is where it gets tough. Without the right mindset and knowledge, you can easily end up getting discouraged.
Campaign optimization is a crucial part of your success and yet many beginners have trouble applying the most basic rules. Before we tell you how to optimize your campaign in the right way, let’s take a look at the two most common mistakes.
Optimizing your affiliate marketing campaigns without sufficient data
This is a common mistake for beginner affiliates regardless of the budget. If you’ve launched the campaign, a day passed by and your $20 is gone and the conversion number is 0, it’s a common (over)reaction to optimize and cut your losses. But you should never optimize a campaign without any conversion data. Click-through rate, win rate, and other parameters are not indicative of whether the campaign has a chance of becoming profitable.
What’s more, optimizing sources based on only a handful of conversions is not the correct way to do it either. Receiving one conversion in a source (zone) can either mean it’s a good match, or just that your ad was displayed to an odd customer who was interested in this particular offer despite being on a thematically unrelated website.
Either way, one or two conversions are still not enough to accurately predict the profitability of that particular parameter.
You need to have data that is statistically significant and we’ll tell you how to get it in a moment.
Expecting clear results with minimum investment
This is a related mistake, as optimizing without proper data is often the result of panicking over money spent. Beginner affiliate marketers are eager to see results so they either act too quickly or overthink every move which, in turn, leads to analysis paralysis.
Seeing a single source, placement or a zone eating up the budget without any results can be stressful but this is how most new campaigns start. Situations in which actionable data starts flowing in after a $10 spend are not that common.
While we’ll get back to budget calculations in the Budgeting section, there’s one thing you need to take away from this part – in order to find campaigns that will earn money, you need to invest in testing variables.
The affiliate marketing industry changes constantly. This is why it’s not possible to hand somebody an offer, a landing page, and a traffic source with a 100% guarantee of success. Tried and tested combinations are either so saturated that it’s difficult to just jump on the bandwagon, or they’re heavily guarded by those who are making money from them.
There is no other way to find your golden egg than through continuous testing. But while picking an offer with targeting can be a hit or miss, the optimization process is almost algorithmic. You need to know the variables and you need to take actions based on data. That’s the gist of the process.
Now let’s dive into the details.
That being said, picking an affiliate marketing program or offer (or a couple of offers) based on recommendations from affiliate managers and performance history is a good place to start. Now what you need to do is plan how to test and then optimize it.
New affiliates who count on making a quick profit want to begin optimizing almost immediately. That is the completely wrong way of starting affiliate marketing. Ideally, affiliate campaigns should be tested for a period of 3-4 days before pausing ad placements and other variables (such as device type, geo, creatives, etc.).
In practice, however, the most important thing to focus on is the number of conversions. Some geos have higher volumes and some offers convert more easily. That’s why in order to determine exactly when the testing period is done, you’ll need to check if you have enough conversions. Conversions are a clear sign that you’re targeting the right audience. So how many conversions do you need to finish the testing phase?
1 to 3 conversions in a campaign are not enough.
1 conversion per source is not enough.
2 conversions per source/placement/lander are also not enough to accurately judge the quality of a variable.
3 or more conversions per source or ad placement are starting to sound like actionable data.
But if the conversions aren’t coming, how long should you wait? Let’s talk about budgeting.
The recommended rule of thumb in affiliate marketing is to spend around 10 times the payout for each tested campaign flow. The fewer variables you choose to introduce, the higher are the chances that you’ll start gathering actionable data sooner. However, fewer variables (landing pages, creatives, or offers) also reduce your chance of finding a winning combination.
To explain that in practice, testing 3 similar offers with 3 landing pages and 3 creatives each, generates 27 possible combinations. While that number might sound like a regular day to a seasoned affiliate, for a beginner it might not be possible to do. Let’s not forget that for each conversion path (offer + creative + lander), you need a separate testing budget. Hence the number:
Depending on your budget, you should opt for more or fewer variables. It’s also recommended to start with lower payout offers (under $10) and avoid Tier 1 geos.
It’s worth remembering that the amount of money spent on testing and optimization before seeing green will vary for everyone. In a popular survey conducted by one of the forum members, over a hundred affiliates shared their numbers. The initial investment of survey participants varied from below $500 to above $5000.
You can find the thread and along with useful budgeting tips here.
Also, any source that brings conversions can and should be noted for future campaigns belonging to the same vertical or being thematically related. (Keep some notes and spreadsheets!)
Micro Bidding based on win ratio is your best friend when it comes to campaign optimization. The easiest way to modify a flow of traffic is to increase or decrease the bids for particular traffic segments taking into account how much of the available traffic you are already buying (win ratio).
However, to do it right, it has to be done incrementally. By increasing or decreasing bids for each individual source you can minimize the spend and maximize results. Keep in mind that if upon spending a certain set amount of money, the source is not bringing any conversions, it should be paused.
How does it work in practice?
When starting out, your campaign bid should be set according to the average rate for the type of campaign you’re running. Taking into consideration ad format and geo, ad networks offer a suggestion of average bid. This is the best option for the beginning because it ensures that you’re getting all kinds of placements. Some cheaper but lower quality ones and some more expensive but higher quality and more likely to convert. It’s not recommended to change the campaign bid while the campaign is running.
Imagine this situation: you’ve got 3 sources all buying traffic on the same bid. One (1) has a 30% win ratio and brought 5 conversions on ROI -30%, one (2) has a 95% win ratio and brought 1 conversion on ROI -90% and another one (3) has brought no conversions with a win ratio of 70% after a spend 10x greater than the offer payout.
What you should do in that case is:
Every metric of your campaign can be significant. While ROI and conversion rate are certainly the most important, others play a significant role too. When choosing what part of your campaign to pause or drop, you need to calculate how likely this campaign segment is to bring profits or keep bringing profits.
The easiest way to run a calculation is by using a free online tool.
Remember that the results of the test will most likely look like those below. While in some cases it will be clear you should cut or pause the variable, in other cases, it can be tough to decide.
Are you into mathematics, statistics, excel functions, and macros? You’ve come to the right place. If the Bayesian calculator isn’t enough, you can look into this thread and read how one of our forum members and veteran affiliates makes decisions based on binomial confidence intervals. His formula takes into account offer payout so it’s perfect for testing multiple offers.
Blacklisting can also have a more severe form, that is, excluding sources or publishers on the account level so you never have to buy any traffic from them again.
The point of making a whitelist is to minimize spending on variables that are not proven to work for a particular type of campaign. Alternatively, you can reach out to your traffic source and ask for a whitelist tailored to your affiliate program or offer. In that case, the whitelist contains chunks of traffic that have been proven to work for other affiliates running offers with similar specifications to yours.
While such a whitelist can be useful at the beginning, the more you test, the easier it will become to create your own whitelist. If you run a lot of related offers belonging to the same vertical or appearing similar in style or destined audience, you can and should make a list of the best performing sources and placement. They can be used to launch fresh campaigns or to re-launch successful ones with higher bids. Both options can be a form of either optimizing or scaling your affiliate marketing campaigns.
Either way, before pausing your original campaign and starting a whitelist campaign, you should first optimize by cutting sources and placements based on results calculated with the Bayesian A/B calculator and modifying bids based on win ratio.
Yes! It’s always good to split test creatives, landing pages, mobile vs. desktop, and other possible variables. The more you test the more likely you are to find the golden egg.
How many variables should I test at once?
As many variables your budget allows. Testing more variables is better but if you’re working with a tighter budget you should follow recommendations and limit variables enough so that you have the sufficient budget to properly test each one (recommended budget per combination is 10x the offer payout).
When to cut a source/target?
Is the spend higher than 10 times the payout rate? If yes, cut it, if not, put it in the Bayesian calculator.
When should I make a whitelist?
You should always be on the lookout for well-performing sources/placements. Keep them in your notes or in a spreadsheet. As for starting a whitelist campaign – if enough variables are bringing steady daily profits that you're happy with, you can launch a campaign targeting only those variables (placements, geos, landers, etc.).
That is not to say that the tried and tested solution can’t work forever. They can. But as an individual, whether it’s a side hustle or your main source of income, you need to find a balance between paving the way and sticking to safety. And however weird some method appears, if it works for you, you should stick to it.
There are many dilemmas you need to face while starting your journey with affiliate marketing. But once you’ve gone through the basics and your campaign is all set up, there comes a moment when you need to optimize your campaigns. And this is where it gets tough. Without the right mindset and knowledge, you can easily end up getting discouraged.
Campaign optimization is a crucial part of your success and yet many beginners have trouble applying the most basic rules. Before we tell you how to optimize your campaign in the right way, let’s take a look at the two most common mistakes.
Common mistakes in campaign optimization
Optimizing your affiliate marketing campaigns without sufficient dataThis is a common mistake for beginner affiliates regardless of the budget. If you’ve launched the campaign, a day passed by and your $20 is gone and the conversion number is 0, it’s a common (over)reaction to optimize and cut your losses. But you should never optimize a campaign without any conversion data. Click-through rate, win rate, and other parameters are not indicative of whether the campaign has a chance of becoming profitable.
What’s more, optimizing sources based on only a handful of conversions is not the correct way to do it either. Receiving one conversion in a source (zone) can either mean it’s a good match, or just that your ad was displayed to an odd customer who was interested in this particular offer despite being on a thematically unrelated website.
Either way, one or two conversions are still not enough to accurately predict the profitability of that particular parameter.
You need to have data that is statistically significant and we’ll tell you how to get it in a moment.
Expecting clear results with minimum investmentThis is a related mistake, as optimizing without proper data is often the result of panicking over money spent. Beginner affiliate marketers are eager to see results so they either act too quickly or overthink every move which, in turn, leads to analysis paralysis.
Seeing a single source, placement or a zone eating up the budget without any results can be stressful but this is how most new campaigns start. Situations in which actionable data starts flowing in after a $10 spend are not that common.
While we’ll get back to budget calculations in the Budgeting section, there’s one thing you need to take away from this part – in order to find campaigns that will earn money, you need to invest in testing variables.
The affiliate marketing industry changes constantly. This is why it’s not possible to hand somebody an offer, a landing page, and a traffic source with a 100% guarantee of success. Tried and tested combinations are either so saturated that it’s difficult to just jump on the bandwagon, or they’re heavily guarded by those who are making money from them.
There is no other way to find your golden egg than through continuous testing. But while picking an offer with targeting can be a hit or miss, the optimization process is almost algorithmic. You need to know the variables and you need to take actions based on data. That’s the gist of the process.
Now let’s dive into the details.
How do you properly optimize your campaigns?
It’s worth keeping in mind that not every campaign will be possible to optimize into profitability. Some offers might not work with a certain traffic segment and some untested offers might simply not be good enough to work regardless of the circumstances.That being said, picking an affiliate marketing program or offer (or a couple of offers) based on recommendations from affiliate managers and performance history is a good place to start. Now what you need to do is plan how to test and then optimize it.
1. Testing
The key point to remember is that testing does not equal optimization. Actually, testing comes before optimization. While testing entails nothing more than letting your budget be spent on paid traffic, optimization makes use of the gathered data. Only after you’ve tested are you ready to begin optimizing.Testing ≠ Optimization
New affiliates who count on making a quick profit want to begin optimizing almost immediately. That is the completely wrong way of starting affiliate marketing. Ideally, affiliate campaigns should be tested for a period of 3-4 days before pausing ad placements and other variables (such as device type, geo, creatives, etc.).
In practice, however, the most important thing to focus on is the number of conversions. Some geos have higher volumes and some offers convert more easily. That’s why in order to determine exactly when the testing period is done, you’ll need to check if you have enough conversions. Conversions are a clear sign that you’re targeting the right audience. So how many conversions do you need to finish the testing phase?
1 to 3 conversions in a campaign are not enough. 1 conversion per source is not enough. 2 conversions per source/placement/lander are also not enough to accurately judge the quality of a variable. 3 or more conversions per source or ad placement are starting to sound like actionable data.But if the conversions aren’t coming, how long should you wait? Let’s talk about budgeting.
2. Budgeting
The first step to finding a successful affiliate marketing program is understanding how much you need to spend to see if the offer is worth it. Note that we’re not talking about a budget needed to see positive results, just a budget to see if there’s potential.The recommended rule of thumb in affiliate marketing is to spend around 10 times the payout for each tested campaign flow. The fewer variables you choose to introduce, the higher are the chances that you’ll start gathering actionable data sooner. However, fewer variables (landing pages, creatives, or offers) also reduce your chance of finding a winning combination.
To explain that in practice, testing 3 similar offers with 3 landing pages and 3 creatives each, generates 27 possible combinations. While that number might sound like a regular day to a seasoned affiliate, for a beginner it might not be possible to do. Let’s not forget that for each conversion path (offer + creative + lander), you need a separate testing budget. Hence the number:
27 combinations x $1 (payout example) x 10 = $270 for the testing phase
Depending on your budget, you should opt for more or fewer variables. It’s also recommended to start with lower payout offers (under $10) and avoid Tier 1 geos.
It’s worth remembering that the amount of money spent on testing and optimization before seeing green will vary for everyone. In a popular survey conducted by one of the forum members, over a hundred affiliates shared their numbers. The initial investment of survey participants varied from below $500 to above $5000.
You can find the thread and along with useful budgeting tips here.
3. Bidding
Once the testing phase is done and you become accustomed to the idea of investing in campaigns that are not going to immediately bring profits, it’s time to learn how to bid. Even if your campaign is not profitable overall despite some conversions, it’s completely possible to optimize placements and sources that will turn the whole campaign green.Also, any source that brings conversions can and should be noted for future campaigns belonging to the same vertical or being thematically related. (Keep some notes and spreadsheets!)
Micro Bidding based on win ratio is your best friend when it comes to campaign optimization. The easiest way to modify a flow of traffic is to increase or decrease the bids for particular traffic segments taking into account how much of the available traffic you are already buying (win ratio).
However, to do it right, it has to be done incrementally. By increasing or decreasing bids for each individual source you can minimize the spend and maximize results. Keep in mind that if upon spending a certain set amount of money, the source is not bringing any conversions, it should be paused.
How does it work in practice?When starting out, your campaign bid should be set according to the average rate for the type of campaign you’re running. Taking into consideration ad format and geo, ad networks offer a suggestion of average bid. This is the best option for the beginning because it ensures that you’re getting all kinds of placements. Some cheaper but lower quality ones and some more expensive but higher quality and more likely to convert. It’s not recommended to change the campaign bid while the campaign is running.
Imagine this situation: you’ve got 3 sources all buying traffic on the same bid. One (1) has a 30% win ratio and brought 5 conversions on ROI -30%, one (2) has a 95% win ratio and brought 1 conversion on ROI -90% and another one (3) has brought no conversions with a win ratio of 70% after a spend 10x greater than the offer payout.
What you should do in that case is:
- Bid up on the first source where you’re not winning much traffic, meaning, there is potential to gain more conversion after increasing the bid.
- You should also bid down on the second source as it’s winning a lot of traffic but not bringing enough conversions to cover the cost of the high-quality placements.
- The third source is a clear situation – you should cut it.
4. Statistical Significance
Pausing any part of your campaign should be a decision based on data and data alone. While the example we gave above seems simple and straightforward, in an actual campaign, you’ll have hundreds of sources, placements, and variables to pause or bid up on. Each one of them can single-handedly push your campaign ROI into green or red.Every metric of your campaign can be significant. While ROI and conversion rate are certainly the most important, others play a significant role too. When choosing what part of your campaign to pause or drop, you need to calculate how likely this campaign segment is to bring profits or keep bringing profits.
The easiest way to run a calculation is by using a free online tool.
Bayesian A/B Testing Calculator
This is an advanced (but beginner-friendly) tool that allows you to count ‘probability to be best’ for your variables. So, based on the number of clicks/views and the number of conversions, the tool will show you which lander, source, creative, or any other variable, is most likely to be a winner. You can test up to 10 variables at once.Remember that the results of the test will most likely look like those below. While in some cases it will be clear you should cut or pause the variable, in other cases, it can be tough to decide.
Are you into mathematics, statistics, excel functions, and macros? You’ve come to the right place. If the Bayesian calculator isn’t enough, you can look into this thread and read how one of our forum members and veteran affiliates makes decisions based on binomial confidence intervals. His formula takes into account offer payout so it’s perfect for testing multiple offers.
5. Blacklisting vs. Whitelisting
Last but not least, blacklisting and whitelisting are a part of the optimization and scaling process. Hence, it’s important to note a couple of crucial points. While whitelisting refers to gathering sources, targets, or placements that perform better than others, blacklisting can refer to pausing sources that underperform for your campaigns.Blacklisting can also have a more severe form, that is, excluding sources or publishers on the account level so you never have to buy any traffic from them again.
The point of making a whitelist is to minimize spending on variables that are not proven to work for a particular type of campaign. Alternatively, you can reach out to your traffic source and ask for a whitelist tailored to your affiliate program or offer. In that case, the whitelist contains chunks of traffic that have been proven to work for other affiliates running offers with similar specifications to yours.
While such a whitelist can be useful at the beginning, the more you test, the easier it will become to create your own whitelist. If you run a lot of related offers belonging to the same vertical or appearing similar in style or destined audience, you can and should make a list of the best performing sources and placement. They can be used to launch fresh campaigns or to re-launch successful ones with higher bids. Both options can be a form of either optimizing or scaling your affiliate marketing campaigns.
Either way, before pausing your original campaign and starting a whitelist campaign, you should first optimize by cutting sources and placements based on results calculated with the Bayesian A/B calculator and modifying bids based on win ratio.
Campaign optimization FAQ for beginners
Should I split-test …?Yes! It’s always good to split test creatives, landing pages, mobile vs. desktop, and other possible variables. The more you test the more likely you are to find the golden egg.
How many variables should I test at once?
As many variables your budget allows. Testing more variables is better but if you’re working with a tighter budget you should follow recommendations and limit variables enough so that you have the sufficient budget to properly test each one (recommended budget per combination is 10x the offer payout).
When to cut a source/target?
Is the spend higher than 10 times the payout rate? If yes, cut it, if not, put it in the Bayesian calculator.
When should I make a whitelist?
You should always be on the lookout for well-performing sources/placements. Keep them in your notes or in a spreadsheet. As for starting a whitelist campaign – if enough variables are bringing steady daily profits that you're happy with, you can launch a campaign targeting only those variables (placements, geos, landers, etc.).
Key Takeaways:
- Testing traffic means letting your budget be spent without interfering for a specified period of time.
- Optimization should only be started after gathering enough data (conversions are crucial!).
- Set budgets for testing each chunk of targeted traffic to avoid overspending on a potentially unprofitable campaign.
- Use the Bayesian calculator to assess the potential of campaign variables such as landing pages, creatives, or sources.
- Don’t introduce too many variables when testing, you need to be sure which ones are underperforming.
- Blacklist first, whitelist later.
- You will not be profitable from the start. The key is to invest in gathering data.
That is not to say that the tried and tested solution can’t work forever. They can. But as an individual, whether it’s a side hustle or your main source of income, you need to find a balance between paving the way and sticking to safety. And however weird some method appears, if it works for you, you should stick to it.
