Focused and targeted marketing aren’t new trends. Marketers have always measured what appeals to specific demographics and analyzed consumer behavior to create more effective campaigns. Technology has enhanced how quickly and accurately marketers can find and appeal to their audiences.
Whether it’s through social media, surveys, or email/newsletter campaigns, the information age has afforded marketers and salespeople several tools to boost conversion rates. While some marketers are still worried about the impact AI will have on their job prospects, forward-thinking ones have seemingly embraced it.
They see it as a tool that they can use or work alongside. A prospect that many of these innovators have begun to consider is the role facial recognition software has in the future of marketing – specifically targeted marketing. The idea may inspire some incredulity or unease in some readers. Is there an ethical way to use facial recognition for targeted marketing, and how? The following guide will answer these questions and explore four reasons facial recognition may be the future of targeted marketing.
What is Facial Recognition Software
Facial recognition refers to the process of identifying a person by the face or facial features. Most sources believe that facial recognition systems and software have their roots in the 1960s. However, the origins are a bit murkier and more complicated than that. What you can be sure of is that facial recognition, at least as a concept, was prominent in forensic science. Particularly in the practice of facial reconstruction.
Albeit, it isn’t a new idea or discovery. In the last two decades, it’s been used by social media to recognize and tag people in pictures, smartphone cameras and lock screens, automatic ticket gates, etc. However, recent advancements in artificial intelligence and machine learning have been a boon for automated facial recognition.
Computer Vision (CV) is the AI/ML field most concerned with facial recognition. The ultimate goal of a CV is to train computer systems to extract meaningful information from digital images. These images can be captured or streamed in real-time.
With companies now increasing their ML budgets by as much as 75%, these technologies can only be expected to grow even more. Unfortunately, there are still many misconceptions related to facial recognition and how it works. These may interfere with your targeted marketing and ad campaign goals.
Understanding the Challenges of Facial Recognition
It’s important to note that many facial recognition systems do not capture and save images of subjects’ faces for later identification. The application may just temporarily capture an image to quickly discern human faces from noisy backgrounds/foregrounds.
Yet, many companies and individuals may still be reluctant to adopt such technologies. Mainly because it may breach regulations, laws, and rules related to personal data and privacy.
There’s also a question of ethics and company image. Many people believe that the adoption of facial recognition systems may eventually create a slippery slope that leads to mass surveillance. China is often used as an example.
It has been speculated that they don’t just use facial recognition to monitor their citizens and prevent crime, they use it to control the behavior of their people. Chinese companies are the biggest exporters of facial recognition technology.
Consent is another issue. Many people aren’t informed or even asked for permission before facial recognition software is used on them. Albeit, there are ethical and lawful ways to use this technology. You need to understand them before you consider how facial recognition can be employed to improve your targeted marketing.
Ethical Use of Facial Recognition Software
One of the biggest challenges of AI paired with facial recognition (or any other human recognition) software is bias. We’ve seen it exemplified in how companies train autonomous vehicles.
Albeit, making preliminary judgments to identify who your audience is can be considered a part of marketing. However, it often results in advertising bias. You must address this first before you consider employing modern facial recognition systems. The goal is to instill a sense of nuance and understanding in your ad campaigns, even with AI at the helm.
The ACLU proposed an ethical framework for using facial recognition in 2014. A summary of its key principles is as follows:
- Consent: Companies must obtain written and informed consent before collecting biometric or facial recognition data and storing it. Furthermore, this data should not be shared or traded without the knowledge or consent of its subject. Organizations must be transparent by defining policies and standards for the ethical and lawful use of biometric or face scan data. They must also codify what measures must be taken when a breach or leak occurs. These measures must also establish accountability in the event of a mishap.
- Access: Citizens must have the right to view, change, or even delete their facial recognition and biometric data.
- Security: Companies, especially those that host records that are available to the public, should ensure that they have the right security measures in place. Again, biometric and saved facial recognition data can be considered personally identifiable information (PII). As such, any breaches or loss of data could leave you liable to fines as specified by regulations such as the GDPR and CCPA. The CCPA imposes penalties of up to $2,500 for unintentional violations alone, while the GDPR is much more severe with its penalties. Furthermore, partners and employees must also exercise ethical use of data. This often means developing a data security-conscious culture in the workplace.
- Government Access: Organizations may allow the government to have access to confidential information, including PII, upon receipt of a probable cause warrant or under conditions stated in the Data Protection Act of 1974.
- Recording Metadata: Organizations must keep records that include information about when the data/images for facial recognition were captured, stored, used, and dispensed with. This should include dates and time stamps as well as details of what the PII was used for.
- Usage: Organizations and individuals must refrain from using facial recognition software to identify a person’s race, age, religion, ethnicity, nationality, or disability.
Now that you understand what considerations and precautions to take when using facial recognition for targeted marketing, you can explore how you can use it in the present and future.
How Facial Recognition Can Be Used to Innovate Targeted Marketing
As the introduction discussed, companies such as Google and Facebook have been monitoring user behavior for years. However, it’s easy to understand how meaningful data for targeted marketing can be extracted from behavior. Doing so with faces is a bit trickier. But it can be done in the following ways:
Identifying Moods and Mind States
The shopping habits of those with depression differ from those without. Facial Emotion Recognition (FER) software can be used to determine the emotional state or mood of subjects by performing a detailed analysis of their facial expressions. This includes microexpressions.
You can use this technology in a brick-and-mortar setting to determine how customers feel upon entering a shop or viewing certain products. This allows you to extract useful CRM analytics in real-time.
FER can also be used in research surveys (after consent is provided) to gauge the emotional reactions participants display when shown certain images or products.
Facial expression recognition software can go as far as identifying mental illness in subjects. However, while useful, the ethics of doing so may be questionable.
Identifying Loyal Customers
Brick-and-mortar shops can use facial recognition software to identify frequent or loyal customers. This information can then be used to market loyalty programs to them. Facial recognition can also be used to determine the demographics of their average customers. This can then be used to inform your marketing strategies. Whether you’re trying to attract more of that demographic or customers from other demographics, facial recognition can tell you a lot about which groups frequent which stores.
Connects The Real World to The Digital
This ties the last two points together. Technologies such as the Internet of Things (IoT) and the Metaverse have already begun to diminish the line between the digital world and the real world. Metaverse development companies are at the forefront of creating immersive digital spaces that could revolutionize the future of targeted marketing. Facial recognition software can recognize faces and then tie them to the publicly available information. For instance, this can be your email address or social media accounts such as Instagram, Facebook, Twitter, LinkedIn, etc.
Shops, gyms, and nightclubs can use this capability to automatically tag your Instagram account when one of their in-house photographers or camera captures your picture and uploads it.
Advertising screens equipped with facial recognition software can be used to apply targeted ads based on the age or facial expressions of the faces they see. If an ad screen contains a story or video, it can include an interface that can be navigated through using a subject’s eyes or facial expressions.
Facial recognition software can be used to detect early signs of a stroke or even market the closest mental health facilities for people suffering from depression. However, it can also be used to discriminate and stalk people. It has the potential to truly innovate how marketing research is acquired as well as improve targeted advertising. But it’s important to stay conscious of the ethics of how you use these tools. If you want to see facial recognition software in action, start a free 7-day trial with pics.io.