Given all of the hype around artificial intelligence (AI) and its effectiveness, it’s time to migrate from Cost Per Mille (CPM) campaigns to Cost Per Sale.
Though Cost Per Acquisition (CPA) campaigns have been used for years, they were usually targeted campaigns. With the advancements in AI technology, it’s time to expand the use of Cost Per Sale as a user acquisition tactic.
Over the last few years, we’ve seen an increase in the use of AI technologies to optimize marketing performance, which has generated better results. Specifically, marketers have focused on AI Conversion Rate Optimization (CRO), the use of machine learning and advanced algorithms analyzing vast amounts of user, campaign, and on-site/in-app engagement, and conversion data to predict which future users will convert.
How We Got Here
One technology-driven tactic that marketers have successfully used to improve conversion rates is personalization. By relying on engagement and conversion data, marketers are using personalization technologies to more effectively engage with customers, resulting in improved conversion rates.
Personalization isn’t just putting someone’s first name on an email salutation, but personalizing the sales journey based on that user’s and similar users’ experiences. According to data from consulting firm McKinsey, marketers can increase revenue by 5-15% based on the effective use of personalization.
Effective Campaign Performance
A/B testing, a long-standing digital marketing tactic, is also benefiting from advances in AI technologies. Now, instead of running a test comparing two versions of a landing page, AI technology can optimize performance in real-time as prospects are shown different variations of images, headlines, texts, calls-to-action, and even button colors, to offer the best converting options.
A third AI-driven technology that marketers are relying on to improve conversion rates is predictive analytics. By analyzing historical user, campaign, and conversion data, predictive analytics technologies can uncover data signals that enable predicting the users that are most likely to convert. Specifically, predictive analytics technology can predict which customers are likely to make a purchase or leave your service, rank sales leads according to their likelihood of conversion, or group customers into cohorts or segments based on their predicted behavior to convert.
When marketers utilize personalization, A/B testing, and predictive analytics technologies, they’re able to more effectively estimate campaign performance.
If marketers can comfortably and effectively predict campaign performance, why not offer campaigns on a Cost Per Sale basis? And by running Cost Per Sale campaigns on a revenue share basis, the entire campaign process is more transparent and also more equitable for all, and in many cases, more profitable.
Put Your Money Where Your Mouth Is
Now that marketers have run successful campaigns utilizing AI technologies, they have a better understanding of what works (and what doesn’t). Based on technology and the performance it has enabled, marketers should begin the migration to Cost Per Sale.
The reality is that many marketing campaigns will still focus on branding. The ability to effectively predict and convert visitors into customers is driven by successful branding, which moves prospects down the funnel to the point where a Cost Per Sale campaign is able to convert.
Though it’s AI technology that has gotten us to the point where we can run successful, profitable campaigns on a Cost Per Sale basis, like with most tasks related to AI, it’s the technology that enables the account team to become more successful. And it requires an account team that understands how to work with AI technologies, how to run the most effective campaigns, and read the signals to ensure results are profitable for all. Whether it’s running queries on ChatGPT and Claude to improve campaign segmentation or knowing how to read the signals and optimize via AI marketing technologies, success comes from a team that understands how to work with AI.
New Business Model
Given all of the hype around AI, it’s time for technology-driven marketers to offer Cost Per Sale as a business model. Instead of promising improved Return on Ad Spend (ROAS), or other marketing-based outcomes, they should make a commitment that the CEO and CFO will understand on a Cost Per Sale basis.
This doesn’t mean that every sales proposal and RFP has to be tied to a specific Cost Per Sale KPI. There are product and service categories with uncertainty that might not warrant Cost Per Sale pricing. But it’s important that sales decision makers make a shift and begin thinking on a Cost Per Sale basis.
As marketers, it’s time we embrace the power and efficiency of AI technologies and begin to offer clients the opportunity to work on conversion-based models. By offering Cost Per Sale campaigns on a revenue share basis, these campaigns can be equally profitable for both parties. Furthermore, they increase trust in marketing solutions as clients see a willingness to be open and transparent.
Omri Argaman is the Co-founder, Chief Marketing Officer and Chief Growth Officer at Zoomd, a mobile acquisition platform. He has been in digital marketing for 20 years. Before Zoomd, Argaman was a Co-founder and VP of Business Development at mobile marketing provider Moblin, which merged with Zoomd in 2017. Argaman began his career in sales and marketing at Microsoft.
