The Cross-Channel Advertising Strategy That Generated $241,305 in 28 Days
“We’ve never broken $200,000 in sales outside of peak holiday season. Do you think you can beat that?”
Those words still echo in the back of my mind.
You see, we just completed an audit of soon to be client’s account and had a pocket full of suggestions, and we were confident this was doable.
But… there was a catch (there always is). They wanted to do it next month.
That meant no long testing period, no opportunity to gradually scale… if we took this on it was go time.
With some deep breaths and an internal pep-talk, we said, “It’s going to be tough, but yes we can do that.”
Table of Contents
Before we jump into the nitty-gritty, let me set the scene.
This e-commerce store had done fairly well in 2017, but it was done entirely on the back of Facebook ads. Don’t get me wrong, Facebook ads are awesome and we have some badass strategies to scale them quickly. However, one channel was not gonna cut it in order to meet our goal.
So what did our options look like?
Well, they had a stale AdWords account setup, but nobody had been paying attention to it. And, a sizable email list they’d been running heavy promotions to for the last year.
So at our immediate disposal, we had:
- Facebook ads
- Google AdWords
- Large email list
With our channels set, we marched forward and put together a kick-ass game plan.
The Crucial First Step
Sure we had a tight timeline, but you know what honest Abe said…
“Give me six hours to chop down a tree and I will spend the first four sharpening the axe.”
Over a weekend sprint, we built a diabolical war chest of intel that laid out:
Competitive market map
Leveraging some of the best competitive research services available online; We quickly broke out their top competitors and came back with their monthly ad spend and placements. It is important to understand who the players are and to know where they stand. Knowing all the cards on the table helped us greatly in crafting our strategy.
We also learned what keywords and landing pages were being used, and how they were performing. This took out any guesswork on our behalf. Finally, we even pulled all of the best performing text and display ads. By doing so, we quickly gained a better grasp on the key messaging that was out there already. This helped us essential cut the corners we needed to.
By doing so, at worse, we can be right where our best competitor is overnight.
Perhaps one of the most important parts of research that sadly is rushed or worse, skipped. It is imperative you know WHO your customer is. If you don’t know who you are targeting, then you will never know what their interests are. If you don’t know what their interests are, you will surely never find them in an audience on Facebook or Google.
We identified four key personas and blew out demographics and psychographics for each. Here are the questions we asked and answered for each. What brands does this person buy most? What was the most recent purchase they made? What are their favorite stores to visit? What do they aspire to be in life? What are their hobbies? What types of ideals do they stand for? What kind of personal goals are they trying to achieve?
Once you know who it is you are trying to talk to, it gets a helluva lot easier to pick the words you use to speak to them in your ad copy.
We like to focus on a particular part of the story or give an overview of the entire experience. Then, we can identify key interactions that the prospect might have with us. You have to take into consideration the user’s feelings, motivations, and questions. This will allow you to align your messaging across each channel and where that consumer is at, it in their current state of intent.
With this in hand, we developed what we call the “Omnichannel ecosystem.”
This lays out channels, ads, and messaging at every stage of the customer journey, to nurture prospects across their path to purchase.
Now we were ready to chop dahn’ that damn tree.
The first swing of the ax was to set up a game-changing retargeting strategy across Facebook and Google AdWords to capture and nurture all of the traffic we’re about to throw at the site.
The second herculean swing was to develop our audiences and creatives in Facebook. With our personas and historical data, this was quick. We developed over 100 audiences (lookalike and interest-based) and begin testing.
Third, we built detailed search, shopping campaign and display campaigns in AdWords to round out our paid strategy. We used brand keywords, product specific search terms, and custom-intent audiences for hyper-targeted traffic.
Then we refined the abandoned cart email sequence and planned out the promotion campaigns we’d need at the end of the month.
Last, but not least we broke out the budget into three phases:
And with these five swings…
… well, I don’t want to spoil the end.
We want to give you the nerdy details others leave out.
There are Levels To This…
To begin, we break our campaigns out by traffic temperature on each platform. We don’t have time to go into the details of how to do this today, but they break down into:
- Cold: Never been to the website or interacted with the brand
- Warm: Have been to the website or interacted with the brand
- Hot: Purchased a product before ← often overlooked
How you construct these will depend on the platform, but when segmenting warm and hot audiences we recommend that you always break them down by time and stage of the funnel.
For example, our retargeting audiences for e-commerce stores breakdown into 50+ segments.
This allows us to have specific messaging for each segment AND most importantly, determine which ones have the best ROAS.
Testing 1, 2…
Like a bat outta hell, we moved into testing.
Since time was not on our side, the testing phase had to be quick, efficient, and get us enough insights to move into optimizing and scaling.
Before jumping into a ton of cold audience testing, we set up (in silly detail) our warm and hot campaigns across each.
This breaks out into three campaigns and we started with the following setup:
- Warm campaign 1
- Facebook Page visits
- Facebook Post/ad engagement
- Video views
- Instagram Profile visits
- Instagram Post/ad engagement
- YouTube video views
- Warm campaign 2
- Facebook & AdWords
- Initiate checkout
- Add to cart
- Viewed product(s)
- All website visitors
- Facebook & AdWords
- Hot campaign
- Facebook & Adwords
- People who purchased a product in the last 90 days
- Facebook & Adwords
By having this foundation in place, we make the most of our cold traffic and limit risk on our testing budget.
Cold as Ice
This is where things really started to get fun (and interesting).
Since we’re rapidly testing new products and audiences, we use a strict set of rules to govern this process. This removes the emotion of wanting to hold onto an ad set/ad group because you have confidence in it or keep an ad live because you spent a ton of time on the creative.
The rules vary per platform, but generally, we let ad sets run up to 3 days before making a final call and use rules to chop early losers.
For example, if an ad set spend reaches 2x (sometimes 3x) our ideal CPA and revenue is < $1 = pause the ad set.
We started with 10 interests closely related to the products or company. Then we created lookalike audiences from previous purchasers of our top products.
After looking at the conversion rate in analytics, we could see vastly different conversion rates by desktop and mobile, so we broke all ad sets by desktop and mobile. This gave us 40 ad sets to start and looked something like this:
- Ad set 1: Related interest 1 – desktop
- Ad set 2: Related interest 1 – mobile
- Ad set 1: Related interest 2 – desktop
- Ad set 2: Related interest 2 – mobile
- Ad set 1: Lookalike 1% – desktop
- Ad set 2: Lookalike 1% – mobile
… and so on.
This setup worked amazingly to give us the data we needed to quickly identify what audiences and devices we could double down on and find similar audiences for the next two phases.
Since Facebook allows us to target people based on interests, demographics, and behavior, we used AdWords to find people searching for the exact products in the store.
We built single keyword ad groups (SKAGs) around high-intent keywords and competitor keywords.
We need to toot our horn here a lil’. Shopping is where we shine and this isn’t the time or place to show you how we set these campaigns up, but we’ll give you a taste.
We set up a tiered campaign structure that allows us to do keyword targeting for our top products. During the testing phase, we’re gathering data on keywords and products that convert, so that we can quickly scale in the next phases.
Target cold audiences in display is an art and a science. The scale is massive, but it can take some time to figure out what works.
Since we didn’t have a ton of time, we used custom-intent audiences layered with specific placements we know convert well. This gives us very targeted traffic of people who are interested in similar products and on specific sites.
In a nutshell, that’s was our testing strategy for the first week. This was extremely detailed because we need to gather data quickly to inform the rest of the month.
For example, here’s how our CPA trend on Facebook during week 1. While we were figuring out what worked, the average CPA was almost $50 (unsustainable).
As you’ll see in the following sections, it was an ongoing fight, but we managed to significantly decrease the CPA in the following weeks.
Trimming the Fat
After letting the test fly, we let them run for a few days before making any real conclusions. While the test was in flight we had rules shutting off ad sets that weren’t converted at all on Facebook and adding negative keywords in AdWords to sculpt what we’re showing up for.
Heading into week 2, we felt pretty good. We have a lot of audiences to work with on Facebook, and our ROAS on AdWords was strong at 2x.
For the remainder of the optimization period, we did two very important things:
- Built similar audiences to our winners
- Began incrementally bumping our budgets
On Facebook, this was as simple as using audiences insights to expand the interests we were already targeting.
One way to do this is by sorting page likes by affinity and selecting pages that you’re not already targeting. This gave us another batch of audiences to test and expand upon our current winners.
For AdWords, the process is much different. On a daily basis, we combed through keywords to exclude negatives we didn’t want to rank for. In addition, we took the best converting keywords and looked for places we could expand.
We began incrementally increasing budgets on our top performing Facebook ad sets and AdWords campaigns. This is a crucial step to see how they perform at higher budgets and shapes our approach as we scale.
Luckily, most of the ad sets and campaigns held their CPA during these bumps. This gave us the green light to start scaling in week 3 (a lil’ ahead of schedule).
Mo’ is Better
Time to scale this & break records.
We had two weeks to scale this campaign, so we scaled it horizontally. We did this building out additional campaigns and ad sets similar to the ones that were performing well during our testing period. Then, we launched them but all with much higher budgets.
This allowed us to double our ad spend, and keep our CPA low. Which, you can see we were able to the get the CPA down to as low as $22 and keep it there.
Now the even bigger story… We were also able to scale AdWord. So much so we were seeing a return on ad spend north of 4X. Meaning, for every single dollar we put into this machine, the machine would give us four dollars back.
We pulled this off by leverage our shopping campaigns for high intent searches. Once we identified the keywords that were performing the best we increased all our bids. We also had an aggressive display remarketing strategy as well as a search strategy to capture high intent. This allowed us to net everyone who was in the funnel and helped to get them over the finish line to convert.
The Results After 28 Days
The hard work we did upfront was 100% worth it as it gave us a serious competitive advantage. We had a legitimate plan and understood the market and the customer journey. We were able to hit the ground running with a strategy we were comfortable with. This allowed us to test quickly and scale quickly. So much so we generated $241,305 in sales in 28 days.
$241,305 in 28 days 😎
How’d we feel about our work?