In September 2020, a new client came to us looking to grow their small book printing business for self-published authors.
They had just recently taken the business over from the previous owner, and were ready to take their marketing to the next level beyond the personal (but manual) efforts they’d taken up to that point.
Our first ad campaigns launched in October of 2020. From the start, we saw elevated numbers in leads even with a modest initial advertising budget. At the end of that first month, the site had seen 3.6x as many leads as the month prior.
That high volume of leads continued through the end of the year, but it wasn't until January 2021 — after 4 months of ads — that we began to see monetary return as the quotes began to turn into purchases.
By the middle of January — with 3+ months of ad spend and limited revenue data for a handful of the leads that had closed so far — our campaigns had already brought in 2.3x as much in profit (accounting for all overhead) as they'd spent in budget.
Even as the amount spent in ad spend continued to increase each month, the rate of return grew as more leads were closed and more revenue data was finalized. After 8 months, the campaigns had brought in over 4.5x in profit as they'd spent in budget.
In those first 3+ months before quotes began closing, it would have been easy to say "something isn't working," and try to rework our campaigns to drive immediate sales and returns.
But the client understood from the start that it typically took at least 3 months before most leads (even the warm ones) were truly ready to print their books and thus convert into customers. That understanding was essential to the success of our digital marketing campaigns.
Had we altered our campaigns in an attempt to drive leads that closed immediately, it's very likely that the business would have suffered in the long term.
Chasing after immediate returns when a product or service requires a longer sales cycle and multiple touchpoints can often result in worse metrics over time, especially given how the major ad platforms optimize behind the scenes.
Both Facebook and Google — the biggest players in the digital advertising space — have platforms that help to optimize your campaigns based on performance. Facebook's conversion objectives and Google Ads' automated bidding strategies all aim to drive more of your target conversion, and they do so with machine learning.
The more of the target conversion that the platforms drive, the more they learn, and the better they get at driving more conversions.
But if you're focusing on the wrong conversion — like trying to drive immediate sales of a product that often requires multiple touchpoints — the ad platforms will struggle to get any results at all.
With little or no results, the ad platforms can't get enough data to optimize for those conversions, and the campaigns will limp along unsuccessfully.
Had the client not had such a clear understanding of their sales cycle, it's unlikely that our campaigns would have been able to continue as they did for 3+ months.
Sure, the lead volume was high, but the return was nearly non-existent. It took 3.5 months to reach profitability, but both BK and the client knew that going in — and our strategy accounted for it.
While great ads and proficiency in the ad platforms can make a big difference, the best marketing is built on a solid understanding of a business and its customers.