Hawthorne Advertising CEO Identifies Key Mistakes In AI-Powered Marketing
AI-powered performance marketing can be misleading if not used correctly, according to MarTech. Marketers must avoid common mistakes to achieve business growth.
Original reporting · martech.org
Original: “6 mistakes to avoid with AI-powered performance marketing”
Read “6 mistakes to avoid with AI-powered performance marketing” at MarTech →
How this was written. Gosling Marketing Studio wrote this article with a language model from MarTech’s reporting (model: @cf/meta/llama-3.3-70b-instruct-fp8-fast); it describes that reporting rather than adding to it. The original, linked above, is the full story.
Key points from MarTech’s report
- Marketers must define the business outcome before using AI to optimize campaigns.
- AI cannot replace human judgment in decision-making, but rather augment it.
- Marketers should look beyond individual platform metrics and consider the overall impact on the business.
- Over-optimizing every variable can create unnecessary complexity and distract from the overall business goal.
- Incrementality is crucial when measuring results to understand the actual impact of advertising.
Marketers are increasingly relying on AI to optimize their campaigns, but this can be problematic if the technology is not used effectively. The risk is that AI systems may become very good at achieving the wrong goals, leading to inefficient use of resources.
AI can perform various tasks such as identifying audiences, adjusting bids, and allocating budgets, which can improve campaign operations. However, it is up to marketers to define what the business should ultimately value, as AI cannot make this decision on its own.
As performance marketing becomes more automated, it is easy to lose sight of the larger business objective. Marketers must be careful not to rely too heavily on platform metrics and overlook the importance of human judgment in decision-making.
One common mistake is letting the algorithm choose the objective, rather than defining the business outcome first. This can lead to campaigns that appear successful on the surface but do not actually drive meaningful growth.
Another mistake is confusing platform performance with business performance. Marketers must look beyond individual platform metrics and consider the overall impact on the business, taking into account factors such as incrementality and customer journey.
Over-optimizing every variable can also be a problem, as it can create unnecessary complexity and distract from the overall business goal. Marketers should focus on determining which variables are most important and prioritize those.
Additionally, marketers must not overlook the importance of incrementality when measuring results. This involves understanding whether the advertising actually caused the desired outcome, rather than just attributing it to the campaign. This article is based on reporting by MarTech.
Questions and answers
What is the main risk of using AI in performance marketing?
The main risk is that AI systems may become very good at achieving the wrong goals, leading to inefficient use of resources.
Why is human judgment important in AI-powered marketing?
Human judgment is necessary to define the business outcome and determine which variables are most important, as AI cannot make these decisions on its own.
What is incrementality and why is it important?
Incrementality refers to understanding whether the advertising actually caused the desired outcome, rather than just attributing it to the campaign, and it is crucial for measuring the actual impact of advertising.
