AI and Customer Insights: The Future of Online Advertising
Or How to Build Customer Trust and Loyalty Through AI Analysis of Online Ads
As a product manager, you know how important it is to understand your customers. You need to know what problems they face, what they want, and what motivates them to use your product. One way to learn more about your customers is to analyze their online behavior, including their interactions with online ads.
Learning With Online Ads
Let's say you run a small business selling eco-friendly cleaning products. By analyzing customer behavior from online ads, you can gain valuable insights into their pain points and motivations. For example, you may notice that customers are searching for "non-toxic cleaning products" or "sustainable cleaning solutions," indicating that they are concerned about the environment and their health. This information can help you tailor your products and marketing messages to better meet their needs.
To collect this data, you can use tools like Google Ads, Facebook Ads, and Amazon Advertising to track customer interactions with your ads. The cost and setup time for this analysis are relatively low, making it accessible to companies of all sizes. For example, setting up a Google Ads account can be done in a matter of minutes, and the cost of running ads can be as low as a few dollars per day.
However, the run time for this analysis is medium, as it involves analyzing large amounts of data from multiple sources. You'll need to regularly monitor and analyze the data to identify trends and patterns that can inform your product and marketing decisions.
The scalability of this analysis is high, as more data can be added as the company grows. For example, as your business expands into new markets or introduces new products, you can track customer behavior from online ads to gain insights into how they are responding.
It's important to note that the evidence strength of this analysis is medium, as the data may not be representative of the entire customer base. For example, customers who do not use search engines or social media may not be included in the data set. To mitigate this, it's important to use multiple sources of data and to regularly validate your findings with other methods, such as customer surveys or focus groups.
AI-Powered Ads
Using AI to generate optimized ads is an exciting opportunity for companies to improve their online presence and attract more customers. With AI, companies can analyze customer behavior from online ads and generate insights into what makes their target audience click. AI algorithms can analyze data faster and more accurately than humans, making it possible to identify patterns and insights that would be missed otherwise.
For example, a company selling running shoes can use AI to analyze customer behavior from online ads and generate insights into what motivates their customers to buy. The AI algorithms can identify patterns in customer behavior and create ads that resonate with their target audience. By using AI, the company can reduce the cost and setup time of the analysis, while increasing the impact of their ads.
The cost and setup time of using AI to generate optimized ads is relatively low, making it accessible to companies of all sizes. The run time is slightly lower, as AI algorithms can analyze large amounts of data in a short amount of time but still depends on traffic. The scalability is also very high, as the AI algorithms can handle large amounts of data and requires less human intervention to generate the ads. The evidence strength is high, as the AI algorithms can identify patterns and insights that are difficult for humans to detect.
Unintended Consequences of AI
One ethical challenge that can arise from using AI to analyze customer data from online ads is the risk of invading customer privacy. Customers may not expect their online behavior to be analyzed by companies, and there is a risk of companies using this data for their own benefit without the customer's knowledge or consent.
An example of the privacy concern is when a customer searches for a particular product online, and suddenly sees ads for that product on every website they visit. This can feel like an invasion of privacy, as the customer did not expect their search behavior to be tracked and used for advertising purposes. In some cases, companies may use this data to create targeted ads that exploit the customer's vulnerabilities or personal information, such as their health status or financial situation.
Another ethical challenge is the potential for AI to reinforce existing biases. If the AI algorithms are not designed properly, they may reflect the biases and assumptions of their creators. This can lead to inaccurate insights and reinforce existing biases.
An example is when an AI algorithm is used to analyze customer data and the data reflects the biases of its creators. For instance, if the creators of the algorithm are predominantly male, it may be biased towards male preferences and miss out on the needs and wants of female customers. This can lead to inaccurate insights and recommendations, as well as perpetuate existing biases in the company's products and services.
Transparency, Honesty and Respect
To ensure that ethical concerns are addressed, companies must take practical steps to ensure that AI is used in a responsible and ethical manner. One of the most effective ways to do this is through transparency. By being upfront and honest about their use of AI, companies can build trust with their customers and alleviate any concerns they may have about their privacy.
Another important consideration is the use of unbiased AI algorithms. Companies can work to reduce bias and reflect the diversity of customer opinions by involving a wide range of stakeholders in the development process. Regular auditing of the algorithms can also help to ensure fairness and accuracy.
Finally, the insights gained from AI analysis should be used to benefit customers, not just the company's bottom line. This means using the data to improve products and services, address customer pain points, and better understand their needs. By doing so, companies can foster long-term loyalty and build positive relationships with their customers.
Learning about customer pains, gains, and jobs-to-be-done from online ads is an important part of continuous discovery and lean experimentation. The use of AI in this process can greatly improve its effectiveness and efficiency. However, it is important to consider the ethical challenges of using AI and take steps to mitigate them. By working together as a community, we can ensure that AI is used ethically and to the benefit of all stakeholders.
Next week, we will dive deeper into how AI can help us learn faster and better with Paper Prototype!