The client was a beauty brand focused on the natural hair niche.
They had developed a set of products targeting natural hair enthusiasts and had already received a lot of user-generated content on Instagram, Facebook and YouTube. However, the majority of their revenue came from small brick & mortar retail stores and hair salons via distributors.
They wanted to leverage their organic traffic & user-generated content to build a direct-to-consumer eCommerce business and diversify their sales channels.
In approximately four months, we managed to take them to $1.7 million in revenue. $1.39 million directly attributed to paid traffic, at a total ad spend of $270,164.98 across Google and Facebook.
I don’t know about you, but that’s a pretty good ROI, especially given that their products are replenishable. That means these customers are likely to repurchase hundreds of times during their lifetime.
I’ll show you how we approached the project, how we structured the campaigns, and what had the most significant impact on the success of the campaign.
Our first step was to make sure we were getting clean data so that we could see clearly where the traffic was coming from and why. Using that data, we could then quickly identify opportunities and build strategies to maximize our efforts.
Looking at their Google Analytics setup, we noticed that they had simply placed the Analytics tag on the Shopify store and their website, and nothing else. Unfortunately, this type of installation often generates confusing data because as a customer moves from through a funnel that spans two or more domains, they can create multiple cookies.
Duplicate sessions and referral traffic makes it difficult to see which source or action is responsible for the conversions, and without clear data, it’s difficult to make accurate decisions.
For example, Shopify merchants sometimes see sales coming from checkout.shopify.com or PayPal.com after a purchase, but these tools didn’t generate the transaction, they just completed it.
We begin by setting up referral exclusions, sub-domain tracking and cross-domain tracking so we could correctly attribute the source of any sales. We also activated enhanced eCommerce tracking, advertising reporting and remarketing.
Next, we made sure that the Google Search Console was linked to the Analytics account so that we could see which search queries our customers were using.
We also linked the Adwords account to Analytics so we could build all our remarketing audiences inside Analytics and then pull that data into Google Adwords.
Finally, we set up conversion funnels so we could quickly identify bottlenecks in the checkout flow. Using Google Tag Manager we also set up custom events to track:
1. Time spent on specific blog posts
2. Scroll depth on the most popular blog posts
3. Video view lengths on the most popular user-generated review videos.
The goal was to use these custom events to build more focused retargeting audiences for use in our marketing efforts.
After the account prep, we waited a few weeks so that we could accumulate enough data to use for the next steps.
Looking at their top conversion paths in Google Analytics, we noticed that each customer purchase involved multiple touchpoints.
We also looked at the top search terms from the Google Search Console to determine what the prospective customers were searching for and use that data to find clues that could be used to position the brand properly.
One thing that stood out was that the top searches were mostly around the client’s brand names or variations of their product names, so we decided to start with remarketing campaigns first, to capitalize on that organic traffic.
Another top path was from social media; this made sense because the client had an extensive network of micro-influencers who reviewed their products, recorded tutorials and made recommendations. Some of these influencers were paid, the majority were just enthusiasts.
First, we built out remarketing lists inside Google Analytics staggered around store & website activity and custom events as follows:
Then we set up a product feed to be used for Google Shopping and Facebook dynamic product ads.
Facebook Dynamic Product Ads (DPAs)
All our bottom of funnel traffic on Facebook was retargeting using Facebook DPAs. These campaigns were split based on 7-day, 14-day and 30-day cart visits. We used bundles and percentage-off incentives at 14-days and 30-days to drive conversions.
Facebook Video View Campaigns
The client had been very active on social media before working with us. They had a lot of videos on both Facebook and Instagram with significant view counts that they hadn’t monetized.
We build video view remarketing campaigns sending those prospects to store category pages and bundle offer pages.
One of the underlying pain points we identified from social media and search term reports was the issue of product reliability.
Most of the competing products didn’t seem to deliver on their promises and our prospective customers were wary of trying yet another “new product.”
By using a lot of user-generated content on Facebook and Google for retargeting, we were able to speak to those fears and show third-party endorsement, which gave prospects the confidence to at least try the products for themselves.
Google Shopping Campaigns
The first Google shopping campaign was a “low bid” campaign. Here we didn’t layer the campaign with audience targeting; we just set a very low bid. What that does is limit our campaign to only show up for brand search queries and long-tail search queries. We were able to pick up a lot of cheap conversions this way.
The second Shopping campaign was an RLSA (remarketing lists for search ads) campaign, this was broken down by product SKU and had high bids but only targeting shoppers on our remarketing lists. We had different bid adjustments for cart visitors, purchasers, etc.
Google Search Campaigns
We built branded search campaigns around the client brand names, product names, misspellings and variation. The objective was to blanket the top half of the search results with our brand. People searching on Google (and other search engines) rarely go past the first page, a lot of them don’t even scroll down, they simply click on the first listing that makes sense.
We created three types of RLSA (remarketing lists for search ads) search campaigns. The first targeted only our product’s names and brand names with positive bid adjustments for all our cart visitors (7-day, 14-day, etc.)
The second campaign targeted competitor brands and product names. The objective was to show up in the search term when anyone who had been on our store or site searched for competing products.
We also ran RLSA search campaigns using our custom event audiences. These were people who landed on the main website and blog but didn’t go to the store.
We felt that if someone had watched 75% of a 15-minute tutorial video or scrolled 75% into a tutorial blog post and was now searching for similar products or competitor brands, they were an excellent prospect for us to target.
YouTube Remarketing Campaigns
On YouTube, we used Trueview for shopping campaigns and only focused on cart visitors and key product page visitors.
We asked the brand’s founders to create short personal videos to engage with their customers personally. We also created video mash-ups from influencer generated content, talking up the benefits and applications of the products.
These videos we also repurposed on Facebook and Instagram on our video views audiences to push those prospects to the store, where the DPAs would pick-up from there.
Because of the nature of user behaviour on YouTube, some conversions attributed to YouTube ads show up as direct or organic traffic along with view-throughs on the Google dashboard.
Google Display Campaigns
With Google Display, we only ran two campaigns, cart viewers 14-days and cart viewers 30-days. The first was just a cart reminder, and the second was a bundle offer with a discount.
For cold acquisition, we tested mainly Facebook ads and Google Shopping ads. The targeting was based on lookalike audiences on Facebook and similar & in-market audiences on Google.
Unfortunately, the cost to acquire a new customer on Facebook was almost double that of Google Shopping.
The Facebook campaign was still profitable but it was cheaper to acquire customers on Google Shopping so we moved the majority of the budget there.
By default most eCommerce brands use Facebook ads for customer acquisition and rarely test other traffic sources, this has created a lot of competition on Facebook and higher bid prices are the result.
Also, Google Shopping traffic likely converted better because it has higher intent because those prospects are actively searching for the product.
A portion of the search volume was likely a result of our competitors’ advertising on social media causing some prospects to search on Google, where our ads appeared on top with search and shopping campaigns.
In the first 4 months of running the remarketing campaigns, we were able to generate over $1.7 million dollars in revenue, with $1.39 million directly attributed to Google Adwords & Facebook ads at a ROAS of 516.6%.
$1.136 million came from Google Adwords with $716,879.70 (63%) coming from Google Shopping. $259, 650.60 came from Facebook & Instagram ads.
We spent a total of $270,164.98 across Google & Facebook during the 4 month period.
There was also an increase in organic search traffic and direct traffic as a result of all the paid ads we were running. The direct and organic search traffic brought an additional $337,959.97 in revenue, some of this lift is a result of YouTube ads.
The biggest takeaway from this project was the client’s willingness to test customer acquisition outside of Facebook ads.
A vast majority of eCommerce brands ONLY use Facebook and Instagram as their primary customer acquisition channels. This has resulted in a lot of competition for ad space and higher CPMs.
Testing other channels may open up additional revenue growth at lower acquisition costs.