How we scaled ad spend in the first month of working together by 944%
All while improving ROAS and achieving 982% revenue growth in our first 2 months working together on growth.
Where We Came In
We'd been working with Follow Your Legend for over 2 years on Email/SMS before Kevin (Founder and CEO) approached us about the prospect of running his paid acquisition in Q4 of 2022.
We set out initially to try and accomplish 2 main things: return his new customer ROAS metrics to be profitable on acquisition while also maximizing ad spend in order to yield the greatest profit return possible during the holiday season.
- Increased ad spend by 944% month over month
- Improving new customer ROAS by over 30%
- Improved profitability of the business overall
- Overall new subscribers increased by 635.5%
- Overall Email revenue increased by 1025.71%
- Overall SMS revenue increased by 594.9%
Email & SMS
Going into Q4, Follow Your Legend was experiencing a dip in overall email campaign performance. Even though new products were being released and cross-sell opportunities should have been high to entice repeat purchases, we still needed to catch up to the anticipated metrics we wanted to see generated from these campaigns.
We identified the core cause as lower-than-preferred opened and clicked rates, which indicated we needed to improve our inbox placement and segmentation strategy if we wished to see better results moving forward. To combat this, we began implementing higher engaged segmentation methods and exclusion strategies to slowly help rebuild healthier engagement ahead of 2022's BFCM sale season. The process ensures that our emails sent during this busy time of year have a better chance of competing for exposure against other brands.
This new strategy changed who Follow Your Legend's most highly engaged segments comprised when a surge of new high-intent customer subscriptions via the ads channels accompanied it. By targeting these new subscribers frequently, we saw successful results in further increasing engagement and revenue performance from our upcoming campaigns.
We soon saw a trend that this daily volume of new customers would continue during the sales period. By understanding this, we implemented a very densely packed email campaign schedule. Emails went out on high-purchase opportunity dates every day, if not twice a day. This method was a very successful strategy when we sustained a consistent and healthy open/click rate across all campaigns during this time. SMS campaign volume also increased to match the momentum of new customers.
By the end, we achieved and maintained a record-breaking volume of revenue generated per campaign on both email and SMS platforms. We also naturally produced the highest orders placed via our email and SMS flows as a by-product of the increased customer traffic/interest on the website and through our campaigns.
The 3 core focus ad channels for Follow Your Legend were Meta, Google, and TikTok. Meta and TikTok receiving the majority of the ad spend whereas Google was bidding on more bottom-of-the-funnel audiences.
How we improved efficiency:
One of the biggest mistakes we see advertisers make is overspending on remarketing and retention. This is not to diminish the value that campaigns provide however you have to be careful because in platform attribution especially for paid social sees remarketing and retention pick up a substantial amount of view through attribution that is not necessarily directly correlated with a sale or is finite which yields to increase regression in results as scale transpires.
So, how did we fix it?
We moved towards third-party and UTM-based attribution to dictate ad spend especially on these campaign types to ensure that when comparing only on click attribution which is more directly correlated with real revenue than view to ensure that we were basing our spend decisions off of this attribution type to increase efficiency.
This change in attribution lead to remarketing becoming less than 10% of the account budget, but it also lead to increases in ROAS for both remarketing as a whole and new customer ROAS across the whole acquisition funnel
We also looked to consolidate spend into fewer campaigns and ad sets to improve account optimization and allow for more consistency as we scaled. This improved performance as the account had an unnecessary amount of diversification between campaigns. We separated the account by SKU to ensure we were optimizing on SKU specific efficiency targets and also separated US and Worldwide targeting.
The real question is: how did we scale spend so fast in such a short amount of time?
- New customer ROAS being above our full-funnel ROAS target
- First-click to-conversion cohort analysis meant limited revenue lag until a purchase
Simply put, we had enough inventory to sustain this newfound scale. This is one of most important parts in executing scale, financing inventory. Luckily, Follow Your Legend was well positioned here.
More importantly, however, two key performance indicators allowed us to scale so fast.
New customer ROAS.
One of the biggest mistakes we see time and time again is that brand owners do not have distinct rules around new customer ROAS and the relationship it has with full-funnel ROAS. What do we mean by this? The most profitable sales are return customer sales. Generally these occur organically or by low cost sales channels like email, SMS, push notifications, etc. This profit is somewhat fixed. But when store owners set KPIs they often look at paid acquisition first. Maybe a store owner is happy with a 1.5 new customer ROAS but needs a 2.5 full funnel ROAS to maintain margin targets to continue investing into scale (inventory, logistics, org growth, etc).
The best situation possible is when your new customer ROAS exceeds this minimum since you are not capped by return customer profits. This was the case for Follow Your Legend, since we were able to improve efficiency by 40% this allowed for this scale.
Lastly, and perhaps one of the most overlooked metrics when scaling a paid acquisition campaign is the distribution of revenue after first click. One of the biggest fallacies in online advertising is that more spend will always yield lesser advertising performance. This is true to some degree, but most people overestimate the extent of this by not taking into account certain data points OR by interpreting data wrong completely.
What does it mean to look at the relationship between first click and conversion? It means after someone clicks your ad for the first time how long does it take for people to buy. If there is a meaningful % of customers who buy days 2-15 after clicking as an example. Naturally, once you raise spend it may take that many days before results normalize from a reporting standpoint at the new spend levels. This also leads to a false positive feedback loop where for stores where this is apparent, when they drop ad spend they also see ROAS temporarily engulf because they are experiencing the wave of demand that occurred while previously being at higher spend.
Luckily, for Follow Your Legend we were able to recognize that the vast majority of conversions happened within the first 24h of first click so this allowed for little to no delay in waiting for conversions to occur and therefore we could scale spend not only daily but also sometimes multiple times per day based on results. We actually did the bulk of the scaling in only 2 weeks for this account. In the end the only thing that stopped us was inventory as although we were well positioned Follow Your Legend did eventually reach an output cap that we look forward to further pushing in the future!