Does artificial intelligence (AI) listen to our conversations?
The answer is yes. AI is recording and logging conversations, but not for sinister purposes. Applications that use AI are always looking for ways to meet the needs of users–even when users don’t verbally state them. Large datasets of conversational data provide AI models with a rich source of information to learn user behavior and predict patterns and trends.
There are millions of people who use digital assistants in their homes and they’re equipped with AI that is lightly listening in the background, usually for its name or a trigger word that prompts it to respond. Occasionally, AI will record small bits of conversation, even if the device hasn’t been addressed.
These bits of conversation are scrubbed of any personal identifiable data that could link a conversation back to the person originally recorded. The information is only used to help train the digital assistants to provide better, more accurate answers.
With all the questions currently circulating around AI, Paige Lord, AI ethicist, shares some compelling insights into what is really happening behind the scenes, and the role AI will play in our future. Understanding how AI systems work and their full potential is critical to executing a well thought out customer experience strategy.
How advertisers really target consumers.
At times, AI is listening but it’s not doing so to share information with advertisers. That would be prohibitively expensive and time-consuming, not to mention a violation of privacy rights. It would also be much less accurate.
Advertisers already have all of the information they need to target consumers with ads for products and services they’re most likely to buy. Most people give away information that makes it easy for companies to target advertisements with precision. The truth is, the metadata provided through phones and applications is the most powerful tool advertisers have.
To illustrate this point, Paige shared an anecdote about how she began to receive a ton of ads for dog food, pet tech brands, and even doggie bandanas. The only problem is that she doesn’t have a dog. It turns out that she was targeted with dog-themed ads after hanging out with dog-owner friends who frequently talk about their dogs.
AI wasn’t listening to her conversations to make assumptions about whether or not she was going to get a dog, it was leveraging data points at its disposal to make an educated guess about what types of ads might be compelling.
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Importance of AI in gathering data.
Free products like social media, search engines, and other applications aren’t exactly free. Users share information about themselves in exchange for the ability to use these services. Some of the data is exchanged consciously, like a user’s name, email, or social media handle.
For example, when using a car parking application, users will share information like their license plate numbers and the make and model of their car. To receive government services, people will routinely share their social security number, faceprint, voiceprint, or fingerprint.
Other data is shared unconsciously, like GPS information. Applications can access a user’s GPS coordinates to gain information about where users are going, where they’re shopping, and the people they’re coming into contact with. In addition, each phone has a unique identification number and companies can make note of unique phone IDs coming into contact with each other.
It’s safe to make the assumption that Paige’s friends were likely searching for dog specific products on their phones, taking their phones to places where dogs would be like dog parks or doggy daycares, and using store memberships to purchase dog items.
Since Paige’s phone was in the vicinity of her friend’s phones, companies could make an assumption that she would be a good target for ads about dog products and services. In the end, Paige doesn’t have a dog, but the company used the data they had available to make an educated guess.
AI parses through data points and makes correlations. In this case, it didn’t hit the target, but the data typically leads to successful, highly tailored ads that address consumers’ wants and needs without any direct verbal communication.
What does this mean for the future of retail and digital marketing?
The future of digital marketing is bright. With the amount of information available to marketers and the capabilities of AI, companies can clearly identify who is most likely to purchase their products, when, and where.
Companies that are using digital marketing have access to a wide range of data, from very high-level information to specific knowledge. For example, a company can make an educated guess that Paige is most likely to make quick purchases between 5:00 a.m and 7:00 p.m on Mondays and Thursdays, based on her data.
Going forward, digital marketing strategies may flex as additional regulations for the use of AI to collect data are proposed and implemented around the world, but marketers will still have access to more than enough information to successfully target ads to consumers.
The future of retail is also bright. While some consumers may not want highly targeted advertising, the alternatives are arguably worse. On one hand, the option would be no advertising at all, which is unrealistic. On the other hand, the option would be advertising without precision.
If users want social media services to remain free, they will need to comply with advertisements.
A lack of precision in advertising would most likely result in more frustration for people. It’s fair to say that most people would not want to receive advertisements for products and services they’re absolutely not interested in.
It’s much more likely that people will enjoy advertisements on social media platforms that feel like personal shopping experiences rather than viewing ads for products and services that are useful or relevant. In this way, AI makes it possible for data provided through applications and phones to be put to good use.
The future of AI and customer service.
One of the most fascinating examples of the importance of AI in meeting the needs of customers without any verbal cues is within customer service and contact centers. This is because applications and websites can gather a great deal of information about customers to help businesses tailor their customer service information.
For example, if a customer goes onto a website and quickly leaves, that information reveals something useful to the company. It could mean the customer found the information they needed right away or it could mean that the customer left because the website was too difficult to navigate.
It’s true that websites are made to provide customers with critical information about a company’s products and services, but when companies understand how and why consumers engage with a website, they’re in a much better position to tailor their customer experience.
Data is incredibly helpful for contact center operations. If a customer calls for assistance with an account or a charge, non-verbal data can reveal a lot of information quickly. Information like whether the customer used the numbers or voice to select options gives companies insight into whether their customers are comfortable with newer forms of technology.
Other details such as how long a customer listens to the menu options, how many times they listen, and whether they’re hesitant to select an option can provide insight into how accurate the menu is and how well it serves the needs of the customer. Even knowing how quickly a customer clicks out of a chatbot window gives a company awareness about how willing their customers are to engage with chatbots.
Companies can use this type of data to help customers meet specific needs or specific concerns about products. When a customer calls from a phone number they used to make a purchase, the company can automatically find the customer’s purchase history and pull it up for the representative, eliminating the need to place the customer on hold.
All of these capabilities demonstrate the importance of AI and how it can help generate faster resolutions for customers and increase their trust in a company. On top of this, these solutions also reduce the burden on contact center agents, reducing costs for the organization.
The power of AI, customer experience, and data.
It’s important that consumers are aware of the data they’re giving away and to provide them with the opportunity to opt out of certain services. Yet, a lot of customer data is benign and the vast majority of companies are using this data only to provide more tailored and more precise experiences for their customers.
While it’s true that AI isn’t listening to everyone in the traditional sense, it is being used in the background to parse through high volumes of data to create better, more personalized customer experiences for countless brands around the world.