This is the second article of a series of blog posts where we review the full landscape of the opportunities for incorporating AI in your performance marketing strategy.
Hard truth: If you’re using AI bidding systems like Google Performance Max out-of-the-box, you are likely overspending on acquiring existing, low-value customers.
Advanced bidding systems do a great job of hitting revenue based KPIs. But–as covered this first article– to find more profitable customers, marketing leaders must adapt these systems to focus on a better alternative: customer lifetime value.
Why? When preconfigured to a diet of revenue figures, AI advertising platforms will do a great job hunting down the cheapest available revenue sources. But, feeding these systems with “junk food” source data like past revenue data tends to clash with long-term profitability goals.
In other words, if you aren’t feeding your system with the right data, you may not be reaching the right customers.
Here’s an example.
Imagine you are an office supply vendor. You sell various products, and your platform currently optimizes toward past revenue data.
Now, consider:
- Higher margins. The reality is that some products– like printers–have higher margins than others–like headsets.
- Low return rates. Printers also have a lower return rate, perhaps because customers tend to do a lot of research beforehand, while headsets are returned more frequently because they don’t fit.
- Customer lifetime value. There is a huge difference in the value of a new customer who buys a printer vs. a headset. Why? After purchasing a printer, this customer may be more likely to come back and buy ink cartridges and paper throughout the year.
As this example illustrates, you need to optimize your machine learning tool with the correct values in order to maximize profitability.
What Data Sources Should We Leverage to Maximize Profitability?
Integrating first-party data, like margins, return rates, and customer lifetime value is the secret to measuring true profitability and informing bidding AIs to optimize toward it.
This is how you incentivize your bidding system to bid higher for valuable customers – even if their first transaction falls below your average ROI target.
Remember: Purely revenue-based optimization will not give you an edge in a competitive environment. Acquiring new, loyal, and profitable customers is critical to your EBITDA growth.
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