September 08 0 335

$83 000 in 1 Month with a New Shopify Store Using Facebook Ads

Today we are sharing a case study from Lokesh Yadav, an eCommerce entrepreneur who was able to generate close to $83 000 in sales in a single month with a new store. However, this result wasn't an overnight success, it came from a process that took him a lot of time to develop.

Read along to understand his actionable process and the procedures he followed to choose the product, create the store, market, and finally scale to $82 520 in 30 days.

Lokesh says, "There are 3 things that determine the success of any product you launch when it comes to dropshipping. It's easily said, yet much harder to execute. Getting these 3 things aligned is the key to scaling a campaign to the crazy numbers you may see around on the internet."

The formula is:

Right Product + Right Audience + Right Offer x The Right Scale = BANK

Now that we have seen Lokesh's formula, we are going to analyze how he used it to generate sales for his new Shopify store.

The Right Product
The product Lokesh chose wasn't very popular on Aliexpress, he discovered it while scrolling through the Facebook feed. He then researched further about the product and he found out that it was going viral on Tiktok. This gave him a green light to test the product.

The Right Audience
When it comes to choosing the audience, Lokesh doesn’t make presumptions in terms of demographics. He prefers going with numbers and data.

Lokesh always starts with an audience that is as broad as possible. The only key fact he considers is that it must be related to the niche of the product. The initial audience sizes usually turn up in between 2 000 000 to 3 000 000 users. Starting with a broad audience is very important for him because it allows him to scale fast to $10 000/ day and above.

He also prefers to stick to 1 interest/ ad set if possible. However, if the audience is small, he stacks them together.

The Right Offer
Lokesh considers the offer as a key part as it separates winning campaigns from the losers.

He says, "You could have 2 campaigns convert differently even though they have the same product and targeting. The difference in conversion is brought by the offers. Most people assume that free shipping is always best to let me tell you it's not."

According to Lokesh, the first thing people see is the price. The lower the price, the more people are likely to reach the Add to the cart stage. Once they notice that they can buy at a lower price, they won’t mind checking out even though you add a shipping fee. This situation converts better than when there’s a higher price and free shipping. If they abandon the cart at the point of checking out, the retargeting sequence can always catch them.

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Examples of Offers:

  • $19.99 + FREE Shipping
  • $16.99 + $2.99 shipping
  • $15.99 + $4.99 Shipping

He initially set a very low price for this product. He got many conversions which helped to build his Facebook pixel quickly. It found more targeted buyers very fast because of the amount of data being received.

Initially, it was a free shipping offer, but Lokesh tested adding a shipping cost and it didn't hurt the conversions at all.

This new pricing strategy was able to stay stable for a long time without slowing down the engagement or purchases. At this point, Lokesh tried to increase the base product price, and the results remained as strong as before.

The Right Scale
To understand his scaling strategy, we need to go through how he set up everything initially. For this project, Lokesh started by targeting a very broad audience. He used the Website Conversion campaign type with the Purchase objective and video ads. This was because he wanted Facebook to send him real buyers.

Lokesh also separated the USA from World Wide GEOs by creating different ad sets. This is because the CPM in the USA is always high. He also excluded countries that provide bad traffic like India, Pakistan, Peru, Indonesia, etc.

His testing ad sets looked like this:

  • 25-65 — (Interest 1) — USA
  • 25-65 — (Interest 1) — World Wide
  • 25-65 — (Interest 2) — USA
  • 25-65 — (Interest 2) — World Wide
  • 25-65 — (Interest 3) — USA
  • 25-65 — (Interest 3) — World Wide
  • 25-65 — (Interest 4) — USA
  • 25-65 — (Interest 4) — World Wide

He tested 2 creatives per ad set. After 48 hours, he saw the best performing ad set and creative. So, he stopped the bad one and kept the winner going across all ad sets.

After 2-3 days CPC was at $5 and ROAS 3-5 across most ad sets. This was a clear indicator that this campaign was a winner and it was time to push it further and see how it would respond. Lokesh then increased the budgets by doubling them to see how it responded.

After 2-3 days ROAS and purchases remained great, he knew that was a golden winner. His plan was to scale it as fast as possible before other people copy and steal the campaign.

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He duplicated the winning ad sets to max-bid ad sets, each with a budget of $1 000. He set the max-bid at 3x the amount of his auto-bid ad sets CPC. The CPCs on the auto-bids were at $5, so on his max-bid ad set, it was $15. He kept the auto-bid ad sets running too.

The next step was to add more interests to test and scale with lookalike audiences.

When scaling with lookalike audiences, Lokesh took the following steps:

  • He tested the USA and EEA first.
  • He chose everyone who viewed 95% of the video ad and Viewed Content.
  • He split up the percentages from 1,1-2, 2-3, right up to 10%.
  • He tested all of these on auto-bid to see how they perform and took the winners to the max-bid ad set with a $1 000 budget for each ad set.

It was then a case of simply rinsing and repeating this process with Add to Cart, Initiate Checkout, and Purchases lookalike audiences. He shut off the losers and kept the winners.

To scale further he broke down the best-performing countries, ages, genders, and placements. He also made a general targeting ad set that targeted the whole world on FB, which let the pixel pick out buyers on its own. This should be tested after spending $5 000. That’s when it will work well. If it doesn’t, then try it after spending $10 000 or $15 000.

The longer the campaign went on, the lower the ROAS went. The most important thing to him was to scale fast and get the profit while the margins are high.

Retargeting campaigns were the campaigns that got him the highest ROAS. Here are the campaigns that Lokesh set up:

  • Everyone who viewed content but did not add it to the cart;
  • Everyone who added to the cart but did not purchase;
  • Everyone who initiated checkout but did not purchase;
  • Everyone who purchased;
  • Everyone who viewed 95% of the video ad.

He targeted these audiences with crazy offers to attract buyers. His favorite offers were:

  • Stock is running low;
  • 5% off discount;
  • 10% discount;
  • Free shipping.

We believe that this case study has provided a clear pathway for anyone who would like to start testing Facebook ads for a new store or eCommerce brand. The biggest problem faced by the strategy is the decline of ROAS and increase of CPA, which is a common issue whenever marketers try to scale fast with Facebook Ads.

We have an article showing how to control your CPA while scaling to have a steady ROAS for a long time. Be sure to read it.

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#facebook ads #scaling