John Lott, partner at Spearmint Love, an online store selling baby clothes, had a problem.
He had just left his job at an equity firm to work full-time on his wife’s ecommerce business.
He was tasked with increasing ROI from advertising channels.
Facebook was an easy target. The company already had tens of thousands of fans there, and the community was highly engaged.
But a couple months into a well-performing ad, ROI would suddenly drop.
John couldn’t figure it out. He thought the ad copy must have gone stale. Perhaps customers had seen it too many times.
He wrote new ads. He changed the images.
The drop-off stayed steady.
Six months later, on a jog, he realized immediately what the problem was.
New moms, their target market, had moved on. Not from the ad, but in their buying behavior. He needed advertising cohorts that matched his consumer’s quickly changing life.
He set in place a plan that today has the company’s cost per acquisition (CPA) on Facebook down to $5.
What Spearmint Love Did
When John sorted out that the parents who were just announcing their pregnancy didn’t have the same needs and pain points as the parents who were preparing to welcome their baby home, he decided to create a strategy that would help serve up more relevant ads to parents at different stages of the parenting lifecycle.
And after testing audience changes over the course of a year, Spearmint Love has learned how to adjust the custom audiences for their Facebook ads so that they better evolve with the changing needs of a young family.
In doing so, they can provide highly relevant product solutions to customers. This strategy has driven more than 15,000 conversions and hundreds of orders from Facebook.
Here’s how they did it.
Studying cost per customer acquisition
To generate the highest possible ROI for the ads they were creating, Spearmint Love closely studied the conversion rate of each and every ad they launched using Facebook insights.
They dove deep into their ecommerce metrics that accounted for both organic and direct traffic coming from these ads.
These metrics included:
- Net new customers acquired through aggregate ad spend
- Total net new customers
By dropping these into a custom table in Excel, the numbers helped them get a more holistic view of what was working across the platform and empowered them to calculate a highly accurate cost per customer acquisition (CPA).
But the data analysis didn’t stop here.
Within the same spreadsheet, they also began to track every customer using their order ID from BigCommerce and the month of their first purchase, and then grouped these customers into different ‘cohorts’ based on time of purchase activity.
This enabled them to complete a cohort analysis, which is a process whereby the data from a given set is broken down into related groups of users (rather than looking at all users as one unit.)
For example: A customer acquired in February of 2016 would always be associated with this particular cohort throughout its lifespan.
They also created a proprietary cohort called a ‘custom window,’ which aligns customer groups with specific changes in behavior and mindset.
For example: One custom window might be the window of time from six months before the baby is born to six months after the baby is born. After this window, the parents and baby have a different set of needs — so they move into the next custom window.
By siloing customers into different cohorts, Spearmint Love could better look for common behaviors and patterns that emerged over time related to acquisition time frame and purchase habits. With this data, they were better able to launch marketing campaigns to their audiences at exactly the right time (which, in turn, drove down CPA.)
How Your Brand Can Do This
So how can you use this information to improve your PPC efforts, too? Take a page from Spearmint Love’s playbook by following these four steps.
1. Start by creating cohorts for your custom audiences.
Rather than looking at your customers as a whole, break them down into smaller groups based on purchase dates, purchase type, and buying habits.
You can use your ecommerce platform’s analytics to help you do this. Go to your customer report and download a CSV file. Pay particular attention to returning customers, the channel they first purchased through (to help define cohort), average order value across purchases and purchase time periods. From here, you can configure the first purchase cohort AOV and time to average second purchase.
2. Study the patterns.
Look at customer activity over an extended period of time to see if there are commonalities in timing, purchase type, or progressional changes amongst your niche buyers. Conduct a cohort analysis on this data to find and leverage the trends you spot there.
3. Create a Facebook advertising plan that addresses evolving needs.
If your research indicates that your customers are following common customer journeys, adjust your ad strategy so that it is always presenting the most relevant information (like product recommendations) based on the custom audience’s current needs and pains. Make sure your ads are evolving with your buyers.
4. Study key metrics on a regular basis.
Keep a close eye on CTR, CPC, and CPA to see which types of Facebook ads produce the highest conversion rate for your audience, and note the specific tactics (copy, images, ad type) that work best, too. You should be studying these numbers on a daily (or at least weekly) basis and optimizing for lowest possible cost.
5. Remember: No ad does well without the proper photo.
John may be the Facebook advertising analytics expert, but his wife, Shari, is the creative brain behind the business. Customers often come to the site to buy *exactly* all the products featured in an ad. It’s the way Shari combines products, merchandises them within advertising images and then connects with the community that makes the ads successful to begin with.
Wrap Up
Using this approach, you can craft highly effective Facebook ads with an impressive ROI.
Just remember: Your customers aren’t one massive group. Study them as individual groups with unique buyer personas.
About The Author:
Kaleigh Moore is a writer at BigCommerce a platform to build your online store with bigcommerce and founder of Lumen Ventures, which helps to educate online sellers on how to grow their businesses across the web. She’s a longtime entrepreneur, who’s run profitable businesses with zero paid advertising. Kaleigh’s been featured in Entrepreneur, Inc. Magazine, Kissmetrics, and SumoMe.
