I have been following some fellow marketers run this strategy for a while and I had tested it out myself too a few weeks ago. I’ve seen decent results with it. Unfortunately, I didn’t have a lot of data to work with so I couldn’t test it at full scale but I believe in the concept for sure.
The strategy is called lookalike stacks and it’s dead simple to implement. You create 1% lookalikes of various options like 1% of view content, add to cart, initiate checkout and purchase and stack them together in 1 ad-set. You can do the same for 2%, 3% and so on.
At nearly $100 spent, purchase conversion value is $255 yielding ROAS of over 2.5
There are two reasons why I think this strategy works better than most other lookalike configurations.
Firstly, Facebook prefers broader audiences over narrow audience. When you let Facebook work with broader audiences, it has more room to play with, find buyers, and generate cheaper sales in turn. When you stack 1% of everything together, the audience size is much larger than 1% of individual lookalikes. It is often 2-3 times larger. Sure you could individually use 3% of purchase or 3 % of view content to achieve same audience size. However 3% is never going to be as good as 1%.
Secondly, best lookalikes are created when you not only use more qualified events but also have a large amount of data in them. For example, if you have 1000 ATCs and 100 purchases, your ATC lookalike is likely to be better than your purchase lookalike because Facebook had 1000 people to create lookalike from. Although purchase is a more qualified event than ATC, it will create a more qualified lookalike once there are large number of purchases in the data-set. When you create a stack, you’re able to leverage from the best of VC, ATC, IC, Purchase together in 1 ad-set. This kind of ad-set is the best of both worlds as it has both: lookalikes of most qualified events (IC, PUR etc), and lookalikes of events with most data in it (VC, ATC etc).
I hope I was able to explain myself just fine. If I didn’t, please feel free to ask me questions.
One of the things that people tell me is that when they run ads they get a lot of irrelevant traffic or leads although they are confident that their targeting is accurate. When you’re selecting a large interest with an audience size in millions, you’re obviously going to reach many irrelevant people just because of the sheer size of the audience.
One of the things that we do to improve this traffic quality as well as our conversion is to do case studies on the pain points and their solutions. For example, if you’re trying to sell a SaaS subscription, instead of trying to reach your potential customers directly with the ad of your product, you should do an ad of the case study.
If your product is an e-commerce product discovery tool, you should do a case study about “how a store owner made $37,000 with this product discovery strategy”. Once you run an ad for this case study, you’ll be able to collect very relevant clicks. You can then retarget this traffic with your product ad. You could also create a lookalike of this case study audience, and then run your product ad for them.
The more expensive your product is, the more number of case studies I recommend you to do.
Lately, I’m writing only about Facebook ads & e-commerce. That’s because since 1st January, we’re busy with the launch of our new store. We took a big part of 2019 off and planned to do some work from 1st January 2020. It has consumed us so far. But today is a good day because today we made it profitable.
In 12 hours, we have done $415 in sales. We’re projecting to close the day at $700.
Our ad spend for today is $154.81 which is about 37% of our gross sales. The net-margins are low right now but since we’re just getting started and the pixel is developing, we’ll see improvements with conversion rates over time. We also haven’t introduced any kind of lookalikes at this point in time.
These aren’t our desired results. We have to make up for the losses incurred with ads in the first 15 days. We need to optimize the ads after removing whatever segments aren’t converting to bring the costs down. We also then need to scale this campaign. If everything goes right, we should be able to do that in the next 7 days.
The reason why I’m not touching the ads right now despite that there’s room for improvement is because campaigns take time to optimize. Many people suggest not to touch your campaigns for 24 hours after you make them. While this could work if your campaign is completely off, I generally suggest 48 hours if there’s some sign of success. And so I’m going to let these go on for at least 48 hours and will not modify them.
After 48 hours, I’ll decide how to modify them by looking at breakdown data.
So if you want your campaigns to work, you need to protect them from yourself. Stay away for 48 hours, be patient. The cash might burn and it is going to hurt you, but the profit lies after that.
Super lookalikes isn’t officially a type of audience by Facebook. It’s just a term used by performance marketers to describe lookalikes made using top percentiles of the audience.
This kind of custom and lookalike audience is generally not publicly made available by Facebook but it’s kind of a hidden gem. If you don’t know about lookalike audiences, please check this out. And if you do, read ahead.
This is where you generally create or find your custom and lookalike audiences
But super lookalike audiences are created here.
Using the percentile option under activity in analytics section
You can create a filter to reflect the top percentile of your readers or buyers and save as custom audience
You can then use this custom audience to create lookalikes using the standard way. I call these super lookalikes.
Because results for super lookalikes speak for themselves.
Facebook has very advanced machine learning capabilities. More often than not, you’re better off reaching your customers for a cheaper cost by reaching a broader audience instead of a narrow targeted audience. But how is that possible? In theory, targeted audience should work better? But with strong ML, the broader audience delivers better and cheaper results provided that the initial customer dataset was correct.
But what happens if you get the initial data wrong? It puts their ML chase your customers in the wrong direction. Let me explain.
When building a Facebook page, growth is going to depend a lot on you first 100s or 1000s likes. Hence getting your first subscribers or customers wrong, can put you altogether in the wrong direction. I can think of 2 reasons why that could happen. Firstly, your upcoming page subscribers are likely to come from the network of your existing subscribers due to sharing and other engagement. And secondly, the engagement behavior of the first data set of subscribers with your content will define how engaging your page is and eventually define the placement of your page in the newsfeed and other Facebook algorithms.
So getting the initial dataset of subscribers/customers is extremely important. It is why I’m generally way more careful in the start when building a Facebook page or an e-commerce store through Facebook ads but later on take the liberty to test all kinds of traffic. It keeps my seed-data clean. The data that is going to be used to build the entire user-base later on.
If you have a question, please feel free to ask in comments.
I have yet to meet a performance marketer who has not fallen in love with Facebook’s LookAlike audience feature. If you provide minimum data (100 users) to Facebook about your leads or customers, it can find more potential customers for you that lookalike your seed data.
It doesn’t just sound sexy. It works. It works wonders. It’s the most amazing feature I’ve seen on any ad platform thus far. But you can make it even more amazing by following a simple trick.
If you have worked for even a few weeks in the internet marketing industry, you’d be aware that the advertising marketplaces work on bidding and competition. Since more and more people are trying to reach customers in US, UK, Canada, Australia & Europe, advertising is generally more expensive in these geos compared to Pakistan, India, Philippines, Mexico, Brazil etc.
And to take advantage of this location arbitrage, all you have to do is begin your ad campaign by targeting customers or audience in a cheap geo-location like Pakistan or India. Once you have 100+ leads or customers from one country, you can use that data to create LookAlike audience for any country including the US. This saves you serious costs in data acquisition which is often done by losing money. And you end up with a valuable data for very little ad spend that allows you to scale your campaigns in any country.
This is the second post of the three-part series that I’m publishing on dropshipping to help create awareness of what it is, and scaling strategies that we use in our company to rocket-fuel growth. This post is not for beginners and will make more sense if you have already started your dropshipping business or have some sort of digital marketing experience.
Since 2016, our company has been running several dropshipping stores in 3 different niches. Most of the growth comes from paid-advertising with majority budget spent on Facebook, Instagram and influencer marketing (also on FB & IG). We also spend about 20% of our ad budget on Pinterest and Google Ads. There is no reason why we spend less on the latter, we’re just more comfortable advertising on Facebook. It’s possible other dropshippers find more success on Google. So by all means I recommend that you explore it. Below I’ll list the top strategies we use in our company for growth.
#1 Product Hunting
I can’t stress enough the importance of product in your dropshipping business. Without a good product and creative, your chances of winning would seriously suffer no matter how good your ads are. I recommend that you spy other stores, AliExpress, Wish, Amazon and everything else that you can to get access to products before others. Most dropshippers use some kind of product spy tool which is often a paid subscription service. You can also search for products on social media platforms where they are being advertised.
#2 Influencer Marketing
Influencer marketing is often always an easier method to find success with dropshipping. To some people it looks more complicated because it involves reaching out to many people, testing their audience and sometimes losing money to less-engaging audience. You may also end up finding accounts with large amount of bot followers, causing total capital loss for the campaign.
The reason why I say it is the easier option is because once you make connection with the right influencers, this is basically an on-going, long-term money making opportunity. You can keep trying new products in the same niche with the same influencer and you can continue to get sales.
Influencer marketing is often also lesser competitive compared to the platform ads where everyone is competing, whether in a dropshipping business or not. This also means that once you have right influencers, you’re likely to have a much higher profit margin compared to running ads on any platform.
#3 Pixel Training & PPE Ads
Without pixels installed on your store from Facebook, Google (and any other platform you choose to advertise on), you’re never going to be able to run successful ads. In short, pixel is a small snippet of code provided by ad platforms that you can install on your stores. Once installed, the pixel establishes a connection between the store and the platform. For example, FB pixel will exchange data between the actions committed on your store and FB ad platform.
The pixel fires whenever a user initiates any action on your store whether it is view content, add to cart, initiate checkout or purchase etc. All user behavior and action data is stored in your pixel. As long as the pixel keeps getting fired, it continues to create an audience profile for you. The more sales you have, the more easily the pixel can help you find better audience. Without pixel training, your campaign is unlikely to do well for you.
First strategy that we commonly use to train pixel is running influencer marketing campaign to get quick, cheap sales. These sales help pixel understand our audience.
The second strategy that we use is running PPE (Page Post Engagement or simply Engagement ads). Engagement ads are cheaper than conversion ads. You get quick social proof, you get quicker, cheaper clicks and this can be a nice way to train and prepare your pixel for your actual campaign.
#4 Horizontal Scaling
After generating a few sales from influencer marketing and PPE ads, we start running website conversion ads. We create a large number of ad sets with a unique targeting angle for each ad set.We generally run these ad-sets on a small budget. This allows us to scale our campaign through many targeting angles. We also end up testing many targeting options. Setting a small budget for each ad set means you’re not trying to win all bids and so you don’t over-spend. Instead you scale horizontally, running many $20-$50 ad-sets. This way you can continue to lose bids (save money) as well as spend more budget (scale) your ad campaign.
#5 Vertical Scaling (with Manual Bids)
Once we have found our top winning ad-sets we also want to scale them vertically. What that means is we ideally want to increase budget for these ad sets. There are generally 2 methods of how this can be done.
Using the first method, you can increase budget for winning ad sets by 10-20% every 2-3 days. This is obviously a slow process and can sometimes not work as expected because ad-sets try to re-optimize every-time they are updated.
The second method is scaling through manual bids. This means that the budget can be exponentially and immediately increased. But we put a cap on what we’re willing to pay for each sale. If the ad-set fails to get a sale, it stops spending. We have had success running $5000/day ad-sets using this method. So this is a fool-proof method to scale vertically. You win, or you don’t spend.
#6 Lookalike Ads
Lookalike is a magical AI technology by Facebook which allows you to run ads without any targeting options. Once you have generated more than 100 sales from a single country, you are eligible to create lookalike audience. This is the quickest, dumbest, simplest way of scaling your ads by letting Facebook do your job.
#7 Retargeting
The simplest explanation of retargeting is not leaving money on the table. A lot of clicks to your website are going to result in missed sales, abandoned carts or simply window shopping. You can reach these high-intent buyers again. Just run retargeting ads, emails & SMS to convert these missed leads for almost negligible price.
Conclusion
A lot of this information is going to sound tough especially if you’re a first time advertiser. But who said running a 7-figure business was going to be easy. The good news is, you can simply start with influencer marketing and learn your way up. The better news is, this is a very low cost business to begin with. You can start with as little as $2000 and make your way up to 7-figure. And the best news is, we have seen it happen first-hand.
