Customer Data & Analytics Blog

IoT data and machine learning: A powerful combination for marketing

Janet Wagner | 3 minute read

Zylotech_IoT Data and Machine Learning A Powerful Combination for Marketing_041819_headerOn our blog, we highlight the many ways machine learning allows marketers to gain valuable insights from data- insights such as products customers are most interested in, when customers are most likely to buy, and the propensity for customers to churn. Today, we thought we would highlight how machine learning and data from connected devices are a powerful combination for marketing. When we talk about connected devices we are talking about the Internet of Things (IoT), a worldwide network of devices all connected to the internet. IoT data is generated from every connected device that consumers use- smartphones, smartwatches, activity trackers, home appliances, to name a few.  

IoT data and machine learning are a powerful combination for marketing as they enable marketers to reach customers in innovative and timely ways.


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Map of Paris, restaurants near the Eiffel Tower - Image Credit: TripAdvisor via OpenStreetMap

Contextual marketing

Thanks to connected devices, marketers can gain access to a wealth of customer information including likes, dislikes, location, behavior, and activities. When customers opt in, much of this information is made available to marketers in real time. When machine learning is applied to IoT data, marketers can create highly contextualized marketing campaigns that reach consumers on the right device at precisely the right time.

For example, activity trackers and smartwatches collect detailed data about the health habits and activities of wearers. Consumers who wear activity trackers tend to be health-conscious. A well-timed ad on an activity tracker app could persuade a health-conscious consumer to purchase health drinks from a nearby health foods shop or buy a membership to a nearby gym.

Location analytics

Most connected devices include GPS, which when enabled, allows a device to broadcast its location in real time. Location data can also be found on social media posts, and millions of social media posts are published every second. Social media content often includes a geotag containing information such as city name, latitude and longitude. Marketers could leverage geotagged social media posts along with IoT data to analyze behavior as it relates to location. Armed with machine learning and location data, marketers could engage with and influence customers wherever they go in real time.Zylotech_IoT Data and Machine Learning A Powerful Combination for Marketing_041819_sub

For example, photos of the Eiffel Tower posted on Instagram are likely to be taken from a smartphone and include a geotag. Well-timed ads in the Instagram app could influence tourists to visit popular restaurants near the Eiffel Tower. Taxi companies and ridesharing companies in Paris could leverage real-time IoT data to create marketing campaigns that target tourists visiting various regions of France. Tourists using a ridesharing app could see offers for rides going to famous tourist destinations like the Louvre museum or Avenue des Champs-Élysées. A hotel chain could use location analytics to build a contextualized marketing campaign that targets affluent tourists visiting regions near Paris. The goal of the campaign would be to persuade these tourists to book rooms at posh hotels in Paris or the surrounding areas.

Real-time push notifications

Most connected devices allow users to receive push notifications, automated messages that pop up on the device. Push notifications are independent of the user visiting a website or a mobile app so alerts can reach customers at any time. Brick and mortar stores could use machine learning, IoT data, and push notifications to reach customers when they are near store locations.

For example, a high-end clothing retailer could provide customers a smartphone app where users opt-in to receive alerts about in-store sales and coupons. The app would leverage GPS so that push notifications are sent automatically to customers when they are near a store location. When a customer enters the store, an alert could be sent to their phone that includes a link to a map of the store with markers that show exactly where each sale item is located. The clothing retailer could also use GPS, indoor beacons, and machine learning to analyze the in-store shopping habits of customers- heatmaps would be generated that show foot traffic patterns in real time. And the smartphone app could be programmed to send push notifications containing relevant messages to customers based on the areas of the store with the heaviest foot traffic.

Marketers should leverage IoT data

With machine learning and a wealth of available IoT data, marketing campaigns are only as limited as the imaginations of marketers- which means the possibilities are endless.

Janet Wagner is a Zylotech contributing writer.

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