The most important thing from the beginning was to set realistic expectations.

We always give a realistic timeline and communicate that we’ll need to cooperate closely in the first two to three months to optimize and grow the account.

We started from scratch, and we didn’t have any previous data. 

Once we added the pixel, it needed time to collect the data since the account was new.

We didn’t have any previous performance information, so we needed to collect data for the first few months and understand what was working.

Campaigns needed time to go through learning phases, get stable, and find people most likely to convert with our budget. 

The client needed specific zip codes and areas to be targeted with ads. This type of targeting meant we needed to focus on smaller audiences, and the setup was trickier but not impossible.

The primary approach was to have separate acquisition and remarketing campaigns for Maryland, Atlanta, and DC. Separate campaigns brought more control and better potential for optimization. We also had better control over creatives and could adapt messaging and banners to the states.

We chose to start by promoting two of their services: Long Distance Moving and Local Distance Moving, which were their focus at the time.

The budget was $1000 per state. In the first month of running the campaigns, we spend $3000. We had 27 leads, and the CPA was $111.11.

The client was happy with the first month’s results, as they understood that we were going in the right direction.

However, we knew the audiences were too small, and the budget wasn’t so flexible. We needed to reorganize the structure to have more leads and decrease CPA. Desired CPA, in this case, Cost per Lead, was around $80-90. 

In December 2021. we had 23 leads for $4000; the Cost per Lead was $174. December is also when people don’t move much, and it’s essential when the season is for this type of business. 

The results were not ideal. The client was very understanding and knew we were still in the optimization phase. However, they were clear that if the results don’t start to improve in the next month, they’ll have to shut down Facebook. They didn’t want to invest if the source was not profitable for business, simple as that.

We had been testing different audiences and ad variations for three months. It was time for a more extensive optimization. 

So what we did was:

1. Merge audiences from Ad Sets which worked best and kept them in one Ad Set per campaign due to the budget and size of audiences.
2. Include Lookalike audiences from the customer list of all booked people and converters from our Facebook Ad Account.
3. Since the client started working more intensively on social media, we created remarketing for people who engaged with the Facebook page. 

In January 2022, we had 51 leads for $3.975, and CPL was $78. The lift was evident and confirmed what we initially thought. The lookalike audiences brought in more leads, contributing to a CPL drop. Merging audiences also contributed because it allowed us to focus the budget better.

And by the time we made all of these changes, Facebook was actively learning who the right audience was. After three to four months, we helped the algorithm recognize and target better leads through the Conversion campaign objective.

We kept this structure and have it still today. 

We wanted to test Lead Generation campaigns since they are a common choice for this type of business.

Lead Generation, in our case, was doing good but couldn’t match Conversion campaign performance. We tried everything and worked on the form questions, but nothing could change performance. 

The conclusion was that the Lead Generation campaigns weren’t bringing in qualified leads like conversion campaigns were. They brought in poor lead quality with higher CPL, and the conversion rate from Lead to booked Lead was lower.

Lead Generation forms may seem more accessible for users and more straightforward to fill. But in the end, bringing users to the website has proven to bring better results and high-quality leads.

Quality is always more important than quantity.

As time passed, we kept optimizing and tracking the campaigns’ performance weekly with ad creatives testing. 

Facebook works best with a few banner variations to rotate and compare. We knew the key was to test as much as possible and always have different creatives. 

We tested graphic pictures for a few months – illustrations vs. photographs of employees working, usually packing furniture and bringing boxes to the trucks.  

Click-Through Rate was good on both of them but always a bit better on banners with real people. This result was generally expected based on competitor ads and the branch. However, we wanted to work based on our data and performance and gain all insights through testing.

So, how did these banners perform?

The average CTR for the illustrated banners was 0.20% – 0.30%. It was lower than the photo banners, with a CTR of 0.40% – 0.50%.

The account kept growing as we increased the number of leads out of season. We continued to optimize and test as we did in the previous months; the algorithm was learning, and the account started performing great.

Then in May, when we started approaching the season, we had up to 150 leads for $4000. CPL for this month is $30. The main focus was to keep the results and work additionally on the quality of the leads. 

Quality always mattered the most to us regardless of the number of leads. We kept the whole funnel in mind, and the final step, booking customers, was the ultimate goal.

In June 2022. we had 106 leads for $3.713. The cost per Lead was $35, and we also had many weeks where CPL was around $20. 

Compared to June, CPL increased by $5, but the number of booked leads also increased, which in the long run is a better thing for us. 

Do you remember the CPL for the first month?

Well, with all of the changes we went through and the budget, which is pretty much the same, we can say that account is growing and going in the right direction.

The CPL dropped significantly and was much lower than the desired CPL, which made our client very happy and their business profitable. 

We focused on bringing in the correct type of leads, merging audiences, and adding lookalikes to find the right pool of interested potential leads. 

The conversion rate grew steadily from month to month. The initial Conv. rate was XZ, and we increased it by XY at the end, and it’s still growing.