“You have to maximize your ROI” “You need to aim for a higher ROAS.”

Does that sound familiar? What if I told you that mindset and those requests coming from your marketing directors should be put to rest?

While those goals certainly seem logical, the ever-evolving digital advertising landscape calls for ever-evolving strategies to maximize profitability.

  • Adapting to the future of machine-learning
  • Maximizing your profitability through data and KPIs

Let’s dive in, shall we?

Adapting to the future of machine-learning

In a recent chat between performance marketing agency, WPromote, and Google’s Chief Evangelist, Nicolas Darveau-Garneau, he makes the bold statement that 100% of advertising will be online (or in some digital format) and automated within five years.

This seems like less of a stretch when you know that about 55% of U.S. advertising was already online as of 2019.

One other key prediction from Darveau-Garneau, involves the predominance of machine-learning algorithms and automation.

“Machine learning algorithms are going to automate most advertising in the next five years.”
The Financial Brand


Make your life easier through automation


The goal of every marketer is to get the most bang for their buck, improve upon their desired goals (be it reach, engagement, or conversions), and to make the process as easy as possible.

Machine-learning is the answer to… well…. all three of these.

Marketer’s lives are made much easier when they aren’t spending time manually optimizing campaigns to reach desired CPMs, CPCs, and CPAs. (You know, the fundamentals of campaign management?) Imagine the resources needed to do this on a large scale.

If you’ve ever ran a campaign, you know the time required for optimization is a huge portion of your workload. Selecting keywords, segmenting audiences, adjusting CPMs/CPCs, A/B testing creative, fine-tuning landing pages…the list goes on.

All of these are important, yet time-consuming pieces of the marketing puzzle. And they can all be performed by machine — allowing you to concentrate on high value strategy.

Make better decisions using data


Machine-learning initially takes some time to learn new things (and yes, for optimal impact, you’ll want to have some initial data for the algorithms to work with); however, once the “machine” has ingested this information, the capabilities exceed far beyond what humans can achieve.

Many machine-learning tools are already much quicker, more precise, and far more efficient than humans. Tools you’re familiar with such as Smart Bidding and Dynamic Search Campaigns are generally outperforming manual optimizations especially when it comes to Target CPA and Target ROAS.

There are two key ingredients that make these machine-learning algorithms effective: the right KPIs and the right data.

Maximizing your profitability

One of the cornerstone mistakes is focusing your strategy on maximizing your short-term ROI rather than profitability and maximum cash flow.

Unless you’re working for mega-corporations, you’re likely working within constrained budgets and doing everything you can to hit your targets and get the best return on your investment.


However, if you can unleash your budget and increase your cash flow, this unlocks the ability to scale your highest performing channels — ultimately resulting in more profitability for your business.

Your strategy should focus on what makes you as much money as possible. Profitability is the KPI you should be focusing on.

While that may seem obvious, so many marketers are still focused on trying to achieve the highest possible ROAS to effectively grow their ROI (spoiler: the highest ROAS doesn’t always mean the most profitability)

Improve your algorithm to focus on value

One of the best ways to improve the effectiveness is to improve the data you feed the algorithm. To do so, you need to understand your performance as fully as possible.

Marketers will typically start out with simple conversion data, and then evolve to revenue-based conversions. From there, you want to take it to the next level by sharing your margin-per-conversion data (even if that means indexing the data).

By sharing this data the algorithm begins to  account for your bottom line — it begins to focus its efforts on high value conversions, not solely based on revenue generated.

For example: if one of your $60 transactions made you $40, and another made you $20, you’d probably want to focus your efforts on the first transaction. If the machine learning algorithm knew that, it would behave quite differently and make you a lot more money.

We’ll say it again, the best way to improve your algorithms to focus on value is to understand your performance, and share this relevant data with the agencies you work with.

Find the right ROAS for your business


Your main focus should be on growth. It’s easy as a marketer to get bogged down over a low CPA or obsessing to achieve a high ROAS.

Selecting the right KPI is important when thinking about profitability. While there are many different possibilities, you might be starting out with what you can do with a fixed budget, then moving forward to measure on a target CPA target. Or you may focus on a sales ROAS and eventually graduate to the previously mentioned profit-margin ROAS.


When looking at your ROAS, we have one request.

Don’t fall in love with your ROAS. Having the highest ROAS, does not necessarily mean having the greatest profitability.

There is no magic ROAS ratio that will define profitability for your business. Test various numbers — up and down — and see which makes you the most money. Make sure you can lock in your ROAS for testing purposes and experiment!

Once you have found the right ROAS for your business (the one that makes you the most money), you can then begin to increase your budget to cover the full demand.

Now that your algorithm is fully supplied with relevant data and your optimal ROAS is chosen, it’s time to add in the final key piece: cash flow based on lifetime value.

Hone in on your customer lifetime value

If you haven’t started thinking about customer lifetime value (CLV) and segmenting your ads based on the highest value customers, you have to begin now. This doesn’t have to be perfect to start — even narrowing it down to quintiles or deciles will set you up for success. You can always improve upon this as time goes by.

You’ve probably heard of the 80-20 rule: 80 percent of your outcomes come from 20 percent of your inputs (inputs in this case being your high value customers). Focus your efforts on the top 20% of existing customers and try to find more customers that have similar qualities.

With those CLV forecasts, you can optimize for profitability for the long-term rather than the immediate impact.

Forecast the cash flow of your new customers even three years into the future could allow you to use that information to help train your algorithms. If you can set your customer acquisition as a percentage of the lifetime profitability, you can bid higher to acquire more of the coveted top 20% of high-value customers.

Where would you rather focus your ad spend: $100 to acquire one customer worth $1,000 or $300 for one customer with a lifetime value of $3,000? While the ROAS ratio is the same, the profitability of the second scenario far outweighs that of the first.

Machine-learning bidding improves as it has a more robust understanding of the value and life cycle of your conversions.

In summary…

If there’s anything you take away from this, it’s that we urge you to do three things.

  1. Refocus your strategies to focus on long-term profitability rather than striving to achieve a maximum ROI. — Test and find the ROAS that makes your company the most money (think profit margins)
  2. Utilize machine-learning to help automate and optimize your campaigns. — Feed the algorithms high quality data around profit margins and high value customers.
  3. Focus on the top 20% of customers with the strongest CLV. — Optimize your campaigns to aggressively advertise to those who bring you the most value.

The advertising landscape is changing rapidly, and the pandemic has only accelerated these changes. Will you be prepared?








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