Integrating artificial intelligence into Internet of Things (IoT) devices isn’t a new concept, but it is still in the development and early adoption stages. In other words, no standard approach exists yet. How can you use AI and IoT data to personalize the customer experience?
How Do IoT Devices and AI Work Together?
IoT technology is constantly connected to the internet, continuously exchanging data with a remote server and other local nodes in real time. These devices are often called “smart” because you can connect to them from an app or a dashboard, regardless of location.
Several types of IoT devices exist, each with its own benefits and use cases. For instance, internet-connected sensors can collect data on everything from vibrations to temperature, so placing them in-store is strategic. Wearables are better for tracking or monitoring because they follow customers around.
“AI can scale with your business needs, handling as many customers at once as you need it to.”
When deployed at the network’s edge — meaning near the data source — IoT technology struggles. The infrastructure simply doesn’t have enough computing resources or processing power to analyze the information it collects efficiently. This is where AI comes in.
Since AI rapidly processes massive datasets in real time, integrating it into IoT devices — especially those at the edge — significantly lowers latency and improves processing speeds. Whether you select a machine learning, natural language processing or large language model affects the specifics.
Having said that, every model can handle a high volume of interactions, meaning it can hold multiple conversations or process numerous data sources simultaneously. It can scale with your business needs, handling as many customers at once as you need it to.
Why Is a Personalized Customer Experience Important?
About 55% of business owners who have deployed AI say they use it for personalization, which shows how important they consider it. With digitalization on the rise, more organizations are considering it a priority. All indicators suggest a one-size-fits-all solution is quickly becoming a thing of the past.
Customer demand has shifted and the path forward is clear — people expect a personalized experience relevant to their wants and needs. Regardless of your industry, you should prioritize segmenting them into groups and tailoring your services to meet their needs better.
People know they leave digital footprints behind whenever they interact with phones, smart devices, computers or point-of-sale machines. The unspoken agreement is you get to leverage all this personal data for free in exchange for improving the customer experience.
Generally, consumers think highly of brands that meet their expectations, resulting in increased satisfaction, loyalty and sales. According to one survey, 63% of marketing professionals agree an increased conversion rate is the main benefit of personalization. You could grow your revenue and gain a competitive edge this way.
“You can use this technology’s data-driven insights to customize customers’ in-store experience.”
How to Use the IoT and AI for Personalization
No matter what your goals are, data collection should be your first step. Using sensors, you can gather information on lighting, touch, proximity and motion, enabling you to monitor foot traffic or your occupancy rate. Wearables can reveal specific details about customers’ locations, visit frequency and loyalty.
At first, the information you collect will be unstructured and challenging to manage. Fortunately, AI can automatically clean, transform and analyze it. You can use its data-driven insights to customize customers’ in-store experience by dynamically adjusting the lighting, music or layout.
Feeding the sensor and wearable datasets into your machine-learning model can help you personalize omnichannel experiences. For example, knowing someone’s typical hours and visit frequency lets you determine the best time to send promotions. These insights can help you digitally communicate, recommend products or advertise.
Imagine you use some combination of IoT wearables, sensors and devices to figure out that one person only ever shops on Wednesday and typically goes straight to the sales rack. Using a decision tree — or another relevant data science technique — you can make an informed guess about their workweek and habits.
Once you narrow down the specifics of their buying behaviors, schedule and unmet needs, you can act accordingly. In this case, offering an in-app sale on Wednesday just for them could encourage them to make more purchases, increasing your revenue.
“Overpersonalization can make people feel like your data collection practices are too intrusive.”
Considerations for Personalizing Customer Experiences
You should consider privacy and data security to ensure personalizing customer experiences grows revenue, improves brand loyalty and increases conversions. While today’s consumers expect you to tailor your offerings, services and advertisements for them, they don’t want you to know them too well.
Overpersonalization can make people feel like your data collection practices are too intrusive or invasive, alienating them. Remember — you need the big picture, not specific details. Knowing their names, birthdays, product preferences, dislikes and demographics should be enough.
Besides privacy, security is one of the most significant considerations. Securing your information storage systems is essential when collecting so many identifiable data points. This way, you can defend against cyberattacks and hackers, preventing sensitive datasets from being exfiltrated or compromised.
Improving Business With an IoT and AI Integration
Integrating AI into IoT technology can improve business outcomes, helping you stabilize revenue in competitive markets and uncertain times. As long as you consider privacy and data security considerations, your strategy should be successful.
