Variable Sale Pricing & Facebook Ads

One of the readers of the blog was discussing his Facebook ad strategy and mentioned that he has to increase the sale price of the product due to expensive shipping.

This quickly reminded me of my personal experience with variable pricing and Facebook ads and I thought to write a bit about that.

When you start advertising a product on Facebook on a specified price point e.g $19 and have a ton of qualified events stored in your pixel and ad account, a change of pricing can be sometimes disastrous. When you record hundreds of add to carts, check-outs, and purchases at a $19 price point, you’ve trained the Facebook ad algorithm to bring you buyers who are comfortable to spend money in that range. Facebook looks into the historical purchase patterns of the buyers and their average cart value in order to serve your ads to the right audience.

An increase of pricing mid-way in the campaign with a lot of recorded data will have more negative impact as you’re not just going to have lower conversion rate due to the hike in price, but also because your ads will not be served to the right audience further reducing your conversion rate. Due to this reason, personally, I like to start my ads with the final sale price and not something lower.

Will A Robot Replace You?

It was father’s day yesterday. I sat down with my father and spoke for a few hours on various subjects. We briefly discussed a topic that reminded me of something I learnt way back in college. It’s a concept from physics. I was actually quite awful at physics so I apologize in advance if my interpretation is incorrect. But here it goes anyway.

In physics, “work” happens when a force is applied to an object such that it moves from A to B. If you exert the force, but the object doesn’t move, the work done is zero.

In regular life, we don’t think of work the same way. But I think we should. If our actions aren’t bringing about a change or a result, I’d like to think that the work done is zero. It doesn’t matter how hard you try, or how many hours you put in, because as long as you couldn’t move the needle, the work comes down to zero.

I feel that in normal life work should be measured as Force x Displacement and we should move away from our current definition of work as only force. In addition, we should make our best effort in order to have maximum displacement for the force we put in. If employee A works longer hours than employee B, but delivers the same value in the end, it may seem that A worked more, but in my opinion, they worked just as much as they pushed the object just as much. Here’s an interesting case-study.

Savannah Sanchez, a Facebook marketer, did an interesting video that I don’t completely agree with, but I find it interesting to share here today. Her thesis is that Facebook’s AI has gotten so advanced, that a human marketer working over 10 hours a week on an ad account was able to deliver just about the same ROAS that another ad account delivered which wasn’t touched at all during same period and was only optimized by Facebook’s algorithm. If you want to watch the video at the exact time, you can do so here. Or you could watch the full video below

The reason why I shared this here is because when a robot can deliver the same value, your working hours i-e force is worthless. It’s the displacement that counts, and if a robot can do that better than you, you’ll be replaced. Although, I don’t think that time has come yet but I know it isn’t far.

I’ve used Facebook as a marketing tool for about 10 years now, and to think that there’s no more human tweaking possible on Facebook any longer is an alien concept to me. 10 years ago, you could do a thousand tweaks and the system would play along. Now, it’s increasingly harder but I feel expert marketers i-e a small percentage of all marketers could still do better than the system. In a few more years though, I wouldn’t be surprised if that number shrinks to a mere fraction.

Facebook Driven Dropshipping Vs Amazon FBA

Facebook driven dropshipping & Amazon FBA are two completely different ways of conducting e-commerce.

So different, that even the choice of products are almost always exactly opposite of each other.

On Amazon, while selecting a product to sell you make your best effort to avoid selling a fad, craze or a trend. You look for years and years of history, up-to 5 years, and only then make a decision if the product is worthy of the launch. You’re looking to keep the review ratings up, returns low, and ideally you want to sell the same products for several years. You spend one time to rank your products, and then rely on getting a return on your investment with organic sales over a long period of time. Due to this, you can often also sell your listing or store for up-to 3 years of net profit.

With dropshipping, most sellers plan to do the exact opposite; selling a fad or a craze. You’re ideally looking for something that has a lot of wow factor. Ideally it shouldn’t be a trend before and is some new kind of gimmickry. You plan to sell $1 million worth of it in the first month, or first the quarter, and once that’s done, no one ever talks about the product again. Fidget spinners could qualify as one of the best-selling dropshipping products and of course they were a fad. Because you make all the money right there, you store often flips for nothing. There’s often no or little lifetime value of the customer outside of the first sale.

Dropshipping needs no inventory and you can make a ton of mistakes. Wrong product selection costs you $100 in Facebook ads. You can test 30 products, lose $3000, and make it all back on your 31st product on your first day. With Amazon FBA, you can’t make any mistakes. You are pre purchasing inventory with hundreds of units to avoid going out of stock and to satisfy minimum order quantity requirements. You’re often risking tens of thousands of dollars with each product launch.

Dropshipping will often better suit those who are cash-strapped and have smaller appetite for risk. Amazon on the other hand is for big boys.

The 20% Budget Rule For Facebook Ads

If you’ve previously run Facebook ads, or have watched some of the content to learn to do so, you may know about the 20% rule. If you don’t, here is what it is; many people recommend to bump your budgets by 20% a day in order to scale your ads without ruining or reseting the optimization.

This isn’t broscience as there’s a “last significant edit” column in the ads manager and any bump in budget greater than 50% triggers the last significant edit and resets the optimization. This is even more trouble-some for CBOs which you often really want to scale as they have several ad-sets and audiences that are ready for larger budgets after you’ve proven your original thesis.

Alex from GetNotissed has worked a simple work around for CBO scaling which seems to work in most cases and I’ll explain that in a bit. The 20-50% budget raise without triggering reset is a guideline given directly by Facebook. However, the fact that we associated a time-window with it was how we perceived that guideline. In other words, you can do multiple 20% raises each second to reach your desired budget in a minute instead of doing 20% raise/day.

So you can go from spending $100 per day per CBO to $500 per day per CBO, without triggering a reset, in 1 minute instead of 9 days as long as you do multiple edits of 20% each. Be sure not to directly raise your budget from $100 to $500 which obviously will trigger the reset.

In my personal test, the theory worked great but I’d still not advise making extreme budget raises using the 20% per second rule.

Making Use of Mobile Deep Linking As A Marketer

One of the common problems all marketers face especially on Facebook is that your ads always open within the Facebook’s native in-app browser. While that works OK for many use-cases e.g an e-commerce landing page, it is an awful friction in many other cases.

For example, if you’re trying to send users from Facebook to your Instagram page, despite the fact that both apps are owned by one parent company, the page would still load in the in-app Facebook browser instead of the Instagram app. Which means if someone had to follow you, he would need to login to Instagram within the native browser, which is never going to happen.

To solve this you can simply use what is known as deep linking. We use URL Genius to do this.

Here’s a regular Instagram link to my page.

Here’s a deep-link to my Instagram.

If you are reading this blog in Facebook’s or Twitter’s in-app browser, you’ll see that the deep-link opens my page in the Instagram app which is how I’d really want this to happen.

Similarly, if you’re a Youtuber and trying to promote yourself on Facebook, a regular Youtube link on Facebook will never get you subscribers because of the in-app browser friction. A deep link however will solve this problem.

There could be a million use-cases. I hope you guys find this helpful.

Facebook Announces “Shops” – Native Shopping Experience on Facebook Family of Apps

Only 2 days ago I wrote this piece about e-commerce being the real fuel of the internet. I feel more confident about it today than I’ve before as Facebook diversifies away from ads and inches closer to the e-commerce space.

When we ran our network of content sites that leveraged Facebook’s influencer marketing, I realized that we were working against the force. That each day, Facebook would do something to cap, limit or control our business or business model in a certain way. I knew that they will take over the business model. So much out-bound traffic making tons of ad-revenue all outside the Facebook platform.

They let us run for a while, for a long while, because their users engaged very well with the content. But eventually they launched instant articles to get a piece of this pie. A native facebook article reading experience where Facebook serves the ads and also takes a cut.

They did the same with the videos. In the early days of Facebook, Youtube videos appeared as embedded content on the platform and not as links. As they started to prioritize their videos on the platform, they started treating Youtube videos as regular links. Eventually they launched in-stream ads, a video monetization program just like one for Youtube.

Now they are doing this for e-commerce. Every day 100s of new D2C brands are launched. Their primary source of customer acquisition has been Facebook. It is estimated that most indie e-commerce brands acquire over 50% of their customers through Facebook advertising. While Facebook already takes a massive chunk of the revenue generated (often 40-50%), having more control by hosting native e-commerce experience on the pages could mean more revenue for the company, better user experience & higher conversion rates.

Just like instant articles, each product would need to be approved by Facebook now when you import the catalog.

How do I perceive this news? troubling. I know this will improve user experience but Facebook already practices more control than I appreciate and the counter-party risks continues to increase.

While you practiced full autonomy over your woo-commerce and Shopify stores, now you’ll be on the mercy of Facebook. In the worst case scenario, which by the way is often the normal case scenario for me, no longer will I only lose ad accounts, I could also lose my “shop”, because of course my “shop” has to adhere to Facebook’s TOS. If the AI, which isn’t very fond of me, constantly throws ban hammers for allegedly violating advertising policies, why wouldn’t it do the same for the shops.

Here’s how Facebook’s Shops look like

Facebok’s Infamous Ban Hammer & The Best Case Against AI

Facebook’s robots are great at finding customers. You can create a CBO with 10 ad-sets targeting 10 different things, 5 creatives for each of the ad-sets and the robots will start optimizing on the first day to get you purchases before you’ve even spent $50. That’s great, isn’t it?

When Facebook’s AI gets mad at you though, its quite like Skynet from the Terminator. It tries to erase you and it goes to great lengths to do so. Let me explain that one.

What happens when you use a credit card on Facebook that was issued in your name but by a different country than the one you’re residing in? You’re accused of credit card theft of course. Then you go to great lengths to justify it but it doesn’t work. Then after a few days of efforts, you make it work. But doesn’t matter if you’ve made it work even, cause that’s strike # 1 and AI is going to be tougher with you.

What happens next? One of your ads is rejected for “circumventing Facebook’s advertising policies”. You appeal it, and the ad gets approved. Doesn’t matter though, cause that’s strike #2.

And just like that, before you know it, you lose you business manager. Because you as a person was the cause of trouble, you also lose your personal ad account. In addition you lose your ability to advertise on Facebook or add or remove anyone or anything in any business manager.

If this sounds bad, let me tell you what else happens.

Any pages that you have previously advertised on Facebook get penalized too including the one for this blog that you’re reading. It doesn’t matter if the advertising was done months ago, you still get the hammer. The page gets zero reach syndrome.

Oh Facebook, why does it always have to be this way? Am I always going to feel this way about you?

How Facebook Machine Learning Prioritizes Users In Audiences

Facebook’s machine learning is meant to do 1 job. The job is serve your ads in the cheapest price possible.

What this means is that if you run an engagement ad and select a worldwide audience for it, Facebook will get you the engagement from the cheapest geo-location which could often be Philippines or India or another country like that.

Similarly, if you run a conversion ad and put in a large amount of countries in your audience section, Facebook will start prioritizing your traffic towards countries that are likely to convert but also where cheaper impressions can be served. So you’d see a large ad spend being done in Brazil or Mexico or Kuwait etc.

Many times, marketers want to sell their products or services worldwide but also have a preferred or prime geo-location which they want to serve first or primarily or in majority.

If you want to sell your goods or services in US and your goal is to have 50% buyers from US but also have some buyers across the world, you should ideally segment your ad-sets. What this means is you should create a separate ad-set for US and another one for rest of the world.

As a media buyer, it is no longer your job to find buyers. That is something Facebook does for you. Your job is to understand how Facebook’s machine learning works, which does it’s job well, but is far from perfect. As a media buyer you’re supposed to identify its shortcomings, and create your ads in a manner to get the best our of their machine learning.

How Facebook Campaign Objectives Work – A Case Study

It is a matter of common sense for years that Facebook tags groups of people from within an audience for various objectives. What this means is if you run an ad for “cooking” interest that may have 100 million people in the audience, and your campaign objective is engagement, Facebook will only show your ads to users tagged as engagers from within the 100 million audience size.

Similarly, if you run a conversion ad on the same interest of “cooking”, Facebook will show your ad to “purchasers” from within the 100 million audience.

But there’s more to the story.

A friend of mine asked me whether he should select campaign objectives that are cheaper in nature for really warm audience. For example, he wondered if “reach” or “engagement” ads should be run for custom audiences of people who have added the products to cart or initiated check out etc.

I told him that this probably won’t yield better results than the conversion objective since Facebook doesn’t just work by tagging users but takes many other data points in consideration. So I ran a test. And here are the results

Click on the image to see full version
  1. Both the audiences are 100% identical. RT Reach has campaign objective of Reach. RT has campaign objective of Conversion.
  2. The CPM of reach objective is 1/10th. It was 10 times cheaper to run the reach ads on my warm audience.
  3. Despite the warm audience, CTR was 1/3rd for reach ads.
  4. Despite lower CTR, more clicks were generated for reach ads. (10 times more impressions and 1/3rd CTR = 3 times more clicks)
  5. Despite more clicks and cheaper CPC (0.11 for reach & 0.28 for conversion), cost per ATC, cost per IC, cost per Purchase was much higher for reach ads.
  6. Cost per purchase for reach ads was nearly 2.5x of cost per purchase of conversion ads.
  7. Reach ads saw ROAS of 0.76 while conversion ads saw ROAS of 2.22


While Facebook could be taking thousands of data points in consideration, I want to highlight the basis of why the reach ads underperformed.

Campaign objective doesn’t just tag users, but also decides whether your ads will appear early in the newsfeed or down below capturing higher attention vs lower attention of the same warm users.

It may also take into account the time of the day for when each individual purchaser makes a purchase. By running reach as campaign objective you’re reaching your “purchasers” at a time when they won’t initiate a purchase.

The conversion objective could take individual placements and platforms in account for each individual user etc.

In summary, the campaign objectives do not just work by “tagging” various groups within the audience but also take into consideration many other data points.

Building Lookalike Stacks, And Why They Work

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.