Case Study for Subscribed Lawn care
We created Facebook Ad campaigns get some useful information about what the company’s next goals.
ABOUT THE CASE STUDY
This is an advertising experiment we ran for a company called Subscribed Lawn Care.
The owners had just purchased the company 3 months before. So, the new owners were still figuring out a lot of things.
For example, whether there was a high demand for lawn cutting. Or if all the hiring happens at the start of the season.
The company had 325 active customers when they bought it. Midway through the first cutting season, the owners discovered a problem.
Problem to be Solved
The company wasn’t as profitable as they had been led to believe. In fact, it wasn’t generating any profits.
So, it was critical that they make some decisions before the next cutting season.
For one, they knew they would have to bump their prices higher for next season. That was a certainty.
A second decision was whether they should expand or not. A couple clients had mentioned how hard it was to find someone to cut their grass. Because all the other grass cutting companies were operating at capacity.
So, the owners thought that if unfulfilled demand existed, it might be worth expanding for next season. The company already had 9 staff and 4 vehicles. Growth would mean 6 more employees and 3 more vehicles.
Since this would almost double the company size, it would require a lot of capital.
The question was:
“Would they be able to find enough clients?”
In the spring, they planned to run Facebook ads to bring in clients. But, by that time, they would have already had to buy more vehicles and hire more staff. So, the level of risk would be high.
To mitigate the risk, they approached Experimarketing. We suggested that they do some Facebook testing now. That would give them some data to help make their decision.
They could run their “spring ads” now to see if there was enough demand for lawn care. If they got customers at a reasonable price, they could make the investments. If not, then they will have saved themselves from a huge loss in the spring.
In the client’s words:
“I was trying to figure out what demand actually is in the marketplace. It is a tricky thing to put your finger on because it is very seasonal.
And it is hard to tell because everyone wants their grass cut at once. So, we don’t know if there is a huge demand or if the demand gets filled at a certain point or how that works.“
The only issue was I was trying to decide if we should expand the business next year or solidify it.”
EXPERIMENTS AND ADS CREATED
BUDGET & CAMPAIGN
To make a simple test, they decided on an advertising budget of $500.
We wanted to find whether there was demand, so we planned a simple strategy.
First, we didn’t want the Facebook campaign type to be a failure point in the system. To prevent this, we would test two different campaign types.
That way if one of them didn’t work, the other still had a chance to work. It would give us a higher percentage chance of finding whether there was demand.
So, the two campaign types were:
Lead campaign and Messenger campaign.
A Lead campaign has a form on Facebook which clients fill out. A Messenger campaign starts a conversation with the client on messenger.
The second part of the strategy was the way we approach the ad copy. We would try two different approaches with our ad copy, for the same reason. It spreads out our risk, and makes it more likely we will find whether there is demand.
For the ad copy, we decided to test out a direct ad and an appeal-based ad.
The direct ad would use copy taken from the client’s website. The appeal-based ad would focus on the benefits of having your lawn done for you.
On the technical end, we would also be setting up targeting criteria and applying some AI tests. The AI tests mimic eye tracking technology. This will tell us what elements are most likely to receive the most attention and how clear the presentation is.
Geographical targeting was set up, as the client prefers clustered clients. This reduces travel time and increases profitability.
In the images, you can see the ad images with the AI overlays. The areas with the deeper red are attracting the most attention. You can see the path the eye is most likely to take when looking at an image.
The software also considers how clear the information is presented and how difficult it is to understand at a glance.
The final direct ads chosen were these two versions.
After the client saw this version (Direct Ad 1.0), they wanted to remove the middle two paragraphs.
So, the final direct ads chosen were these two versions.
And for the appeal-based ads, we ran these two versions. The copy is the same for the text part, but the image text and image are different.
This ad copy was done more in a copywritten style. While the direct ad was mostly taken from the copy on their website, this copy was more creative.
The client’s comments about the appeal-based ads we created:
“I like that these ads focus on value. It is explaining the value to the customer. Not just focused on us. A lot of ads are targeted toward explaining the company. Where good marketing is explaining how a customer is going to be able to sit back and have a beer. That is what you are buying – that freedom. And those are the customers we want too. Not the person who is in love with their lawn and cares about every blade of grass. Not the perfection-focused person. We want the average client who wants their lawn cut well.”
After seeing the appeal-based ads, the client felt like the direct approach probably wasn’t as strong. But we wanted to test it to find out.
For our campaign structure, we set up two different campaigns. One for the lead ads and one for the messaging ads. Each campaign had a $35 daily budget.
Inside each campaign, we set up two different ad sets. One for the “direct ads” and the other for the “appeal ads”. And so, each ad set had a $17.50 daily spend.
Here is the targeting that was used for all the ad sets. You can see the geographic regions targeted, the age range, and the placements. Because this ad was run outside of the USA, we could not target home owners directly.