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HOW WE SCALED an Ecommerce store from $8,000 TO $82,600 USD in 35 DAYS!

In late 2019 a business reached out to us about scaling their online store. They weren't using Facebook as a traffic channel and was having trouble scaling up. Most of their sales came from low-budget Instagram Influencer promotions.

The shop had done about $8K within their first month but was having trouble scaling further only using influencers in their niche. This first $8K in sales was KEY for us to scale quickly- their pixel was already piling up useful targeting data and consumer behaviors.

Using a systems-based scaling method we took their store to from $8K to $82K in revenue in 35 days (from October 25 - November 30, 2019).

Below are 5 KEY strategies we implemented to scale HARD and FAST.


Platform: Shopify

Pixel Integration: Perfect Pixel (We use this app because it reports pixel data more accurately than the built-in Shopify Integration)

Industry: eCom - Niche Fashion

Item + Fulfillment Integration: Their warehouse.


The store had already earned ~$8K the previous month, so the Facebook Pixel had enough conversions to optimize for purchase.


- Optimization: WC/Purchase for all Ad Sets

- Most ad sets were on $5/day budget, excluding retargeting ads

- Age Range, gender, etc were based on Google Analytics customer demographics

- Items/Creatives: We tested all of the products using Instagram Influencers before testing on Facebook.

For the creative image, we used some variation of the main product thumbnail image on the store website. This allowed for consistent customer experience from Ad to product page.

We also ran MULTIPLE CREATIVE versions of the same product ad, which gave the items a longer revenue-gen lifespan.


KEY #1. Retarget EVERYTHING to convert previous site visitors

Generally speaking - Retarget ads are the highest ROI ad-type because they reach warm traffic. Ours usually have greater than 5.0 ROAS on average and are the most “evergreen” ad set type because the retargeted audience constantly refreshes.

To get the most ROI out of our retargeting, we set up a whole bunch of different custom audience & timeframe combinations. There’s no real science to determining which audience to use. We figured ATC no Purchase, ATC, and Time Spent 5% were the more obvious converting audiences, although it requires experimentation.

These are retargeting audiences we use:

ATC no Purchase - 28 Days

ATC no Purchase - 45 Days

IG - ATC no Purchase - 14 Days

IG - Facebook Post Engagement - 45

Days IG - Time Spent 10% - 14 Days

IG - Time Spent 10% - 28 Days

IG - Time Spent 5% - 14 Days

IG - Time Spent 5% - 28 Days

IG - Visit Top Item Category - 14 Days

IG - View or ATC no Purchase - 45 Days

NF - Facebook Page Likes

NF - Time Spent 10% - 14 Days

NF - Time Spent 10% - 28 Days

NF - Time Spent 5% - 14 Days

NF - Time Spent 5% - 28 Days

NF - View or ATC no Purchase - 28 Days

NF - View or ATC no purchase - 45 Days

NF - View or ATC no purchase - 14 Days

NF - Visit Top Item Category - 14 Days

NF Mobile - ATC no Purchase 14 Days

NF Mobile - Facebook Post Engagement - 14 Days

NF Mobile - Facebook Post Engagement - 28 Days

NF Mobile - Facebook Post Engagement - 45 Days

NF Mobile - Instagram Post Engagement - 14 Days

NF Mobile - Instagram Post Engagement - 28 Days

NF Mobile - Instagram Post Engagement - 45 Days

Notes: Overlapping time frames should exclude the others - segmenting this way allows for different optimizations on the ad set level at different times. Excluding previous purchasers is usually best practice to get the most ROI out of your retargeting ads.

DPAs and retargeting are simple, straightforward and it works. Just be sure to check in adjust your budgets based on performance (rebalancing).

KEY #2. Launch Tailored Lookalike Ads & Targeted Interests

After retargeting, our Lookalikes generally brought in the most consistent ROI.

These are the 5 core CUSTOM AUDIENCES we use to build LLAs (using the data collection setting, 180-day window):

1. Pixel Visit Item ( Visited an Item URL on our website)

2. Pixel Event ATC (People who added to cart)

3. Pixel Event Purchase (People who purchased an item)

4. Facebook Engagement All (Anyone who engaged with your Facebook page)

5. Email Subscribers (From email signups)

Build yourself a list of ALL high intent audience combinations and TEST - don’t just stick to the basics after you complete them.

Try combinations of multiple settings too. (EG. ATC + Pixel Visit Item - someone who visited a particular item and also performed an add to cart action = high relevance and buying intent).

For each audience, we use these LOOKALIKE PERCENTAGES:

1%, 1-2%, 2-3%, 3-4%, up to 9-10%

Note: If you’re just starting to scale and don’t have a large budget, start with 1%, 1-2%, and 2-3% (these tend to be the most similar to your current site visitors).

These are the regions we currently use (Based on our data . Again - use yours for this part):


- UK

- Canada

- Australia

- Germany

- France

- Nordic (Denmark, Finland, Norway, Sweden)

- Northern Europe (Belgium, Ireland, Luxembourg, Netherlands, Iceland)

- Switzerland, New Zealand

- Worldwide (Excluding Tier 1 countries - USA, etc.)

* Include "English(All)" Language setting for non-majority English speaking countries

For each audience-percentage-region combination, we run 3 separate ads based on placement.

These are the PLACEMENTS we use:

1. Facebook NewsFeed ONLY 2. Instagram Feed ONLY 3. Instagram Stories ONLY

NOTE on LLAs: Sometimes they don’t spend properly, or not at all. We’ve found that simply deleting and recreating the ad set will often fix this.

You can also include the country target placement instead of leaving it blank - that helps LLAs spend normally.

Interest targeting is straightforward - Do the research and test everything, hold onto the interests that generate positive ROI.

KEY #3. DUPLICATE Profitable Sets and Raise Budgets on Low CPP

Do more of what already works by DUPLICATING all ad sets that are above a certain ROAS and CPP (cost per purchase) margin every single day.

Each store will be different. In this case, we use under $19 CPP and ROAS over 5.0 (something we discovered later)

Duplication is a low risk-approach to bumping up revenue because of the way Facebook’s algorithm works.

NOTE: Duplicating ads can cause under-delivery due to overlap. We overcame this by SLIGHTLY altering the duplicated audience size (i,e, Exclude an LLA percentage, increase the age range, etc).

KEY #4. “Revival” Ad Sets - When

The Facebook Ads Manager doesn’t always report purchases in real-time, so we often turn off profitable ad sets by before they report a sale due to reporting lag (7-day view / 1-day click).

The lagged data usually appears within 1-2 days, so to circumvent this - we go through our inactive sets every day and turn back on any set that should’ve been left on within our profitable parameters using both a 7-day timeframe and a 4-day frame.

KEY #5. Build a dedicated team for SUSTAINED SCALING

There’s more to life than manually setting up ads. It’s time-consuming and mega-boring. When scaling, this is the type of task to avoid doing on your own.

To save our time (and sanity), we trained a DEDICATED CAMPAIGN SETUP TEAM of virtual assistants. They’ve literally saved us hundreds of hours of manual data labor ( Campaigns setups, data entry, etc).

Our team currently sets up at least 2,400 ad sets per week per store (for established stores doing at least 200k revenues per month). This frees up time + energy to focus on the actual strategy and analytics.

Note: You could use software for automated setups, but they tend to lack flexibility.

Here’s the brief campaign setup process:

1. Each weekday- we send our VA team a list of campaigns to create that day in Asana. These campaigns are based on historically converting audience types + items. They’re given the post ID and any other relevant instructions.

2. Our VA team sets up the campaigns and switches the campaign to inactive.

3. A marketing manager checks the inactive campaigns to ensure correct settings, then turns them on.

Here is our hiring process:

A. Post a job on Upwork

B. Vet candidates - these are are some interview questions we ask:

- Can you tell us a bit about why you don’t currently work at your last job and why you stepped away from that job?

- What are the three most important attributes or skills that you believe you would bring to our company if we hired you?

- At times your workload may feel unmanageable. Describe a time when you recognized that you were unable to meet multiple deadlines. What did you do about it?

- Give two examples of what you did in previous jobs that demonstrate your willingness to work hard

C. Once we’ve found a new team member, the training process begins:

We have a complete database of task-specific training videos. We send the new hire all training videos related to the role. Topics may include how to set up interest campaigns, how to create LLA audiences, etc.

We now create these in Quicktime Player using the Screen Record + Audio function and upload them to a collective folder in DropBox.

Once trained, we have our VAs set up Facebook campaigns as unpublished and ensure accuracy. In order to quickly build your own uniquely tailored system - start with building the assembly line!


So - That’s the core essence of our scaling systems. Seek to understand how the ads interact with Facebook’s algorithms and apply. Remember: Data is your friend!

Since implementing this scaling formula, this particular store made about $1.1 Million USD in revenue year-to-date.

Sustainability and systems-design are KEY. One-shot-product winner scaling takes you back to square 1 over and over - a real store needs a product research team to keep the revenues flowing on tier 1, 2 and 3 level products.

Anywho - Thanks for reading. I hope you got some actionable value!


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Would you like to see more case studies and tips like this? Let us know in the comments. Please feel free to reach out about questions.


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