What’s tomorrow’s secret to better personalization? To more human content and more authentic brand-consumer relationships?
AI is making the customer experience more personalized than what most marketers would have ever thought to be possible. Companies are already using artificial intelligence to make their websites, emails, social media posts, video and other content better tailored to what customers want right now. This is going to re-energize the push towards higher customer expectations even more, leading to not just steps forward in the way brands interact with their customers, but leaps ahead.
How can you keep pace with this exponential change? Start adopting the AI methods that are relevant to your industry, and to your business, today.
To give you an idea of what’s on the table right now, here’s a look at the different ways artificial intelligence is set to ramp up personalization in 2018.
Push Notifications with Personality
Push notifications are becoming an increasingly popular way to communicate with customers. They are delivered via mobile devices, which means users are more likely to pay attention. When done well, they create the feel of receiving a personalized text.
The more personalized, the more likely consumers will take notice. This is a powerful tool in an era when even engaged consumers are directing most of their marketing emails to their Gmail account’s promotions inbox or email junk folder.
Here’s an example from Trip Advisor. The company’s app’s algorithm uses data from a user’s previous actions in order to send a custom-tailored message. Far from appearing salesy or pushy, this technique comes off as helpful.
Already plenty of websites are using basic machine learning to customize the content a visitor sees when they land on a website. Basic algorithms include tailoring content based on universal data sets like trending topics and recently published articles. These types of fundamental-level functions ensure a webpage won’t remain the same so visitors always have a fresh experience.
In 2018, the move will be towards creating more sophisticated experiences with the help of AI. The artificial intelligence learns more about visitors based on how they engage with a site and what actions they take. One technique brands like Netflix and Etsy have excelled with is collaborative filtering. In this case, the ‘machine intelligence’ will gather information about visitors and then group multiple site visitors together based on their preferences. Then, these ‘groups’ will get similar experiences when they visit the site. These experiences won’t remain static either, but will evolve over time as the data inputs influence the group filters.
AI-Based Image Recognition Software
Images are powerful engagement tools. But with artificial intelligence, they can also be repurposed into a revolutionary source of information marketers can use to make smarter decisions, and to help develop more spot-on buyer personas by identifying consumer behavior and trends. With AI-based image recognition software, it’s possible to sift through hundreds of thousands of images posted on social media to then identify trends. Imagine the depth insights when you know xx% of your engaged customers use your product at night, at the gym, eating ice cream, or with their cat.
At the end of 2016, Facebook opened their image recognition software to everyone, going the open source route with the intent of advancing the technology. They have hopes to use image recognition to improve their content for the hearing impaired and to start developing ways to use AI-image recognition in videos. In 2017, the interest in image recognition has been picking up tremendously, with industry leaders like Salesforce getting involved. Rob Begg, VP of marketing for social and advertising products at the software company, believes it can do more than offer consumer insights, but also help brands see where influencers may be using their product or service online. This can then be used to inform influencer strategies. It can also be used to learn more about who is being exposed to a product or service, based on the influencer’s audience.
Machine learning is also being used to help brands deliver a more personalized experience on a wide scale with chatboxes and voice interaction, which have finally made conversational user-interfaces the appealing, seamless experiences that UI innovators have been trying to create for years. In 2018, things are set to get even more exciting. Microsoft, for example, is experimenting with ways to go beyond voice, using sight, sound, touch, and a consumer’s gaze and hand gestures to learn more about their needs and expectations. Then the AI ‘learns’ this sensory information and can deliver a better experience – answering the right questions, anticipating needs, and connecting users with the knowledge, product, or service that they want.
Increasingly Segmented Email Messaging
Email is one area where AI has been playing a major role for years. With predictive analytics, marketers are able to easily segment their emails, making sure customers get the information that is most relevant to them. Expect AI for email marketing to continue getting more sophisticated, making it the norm for marketers to deliver hyper-personalized content, at the right time of day, with the right tone of voice, the right offers, and the personal touches that will encourage long-term relationships.
With customers expecting a tailored experience for them, brands can come up with creative ways to gather more information about their subscriber lists, to go even deeper into segmentation and seemingly effortless personalization.
Why All Marketers Should Be Moving Towards More AI
Considering the fact that more than half of marketers feel that the industry isn’t getting personalization right, the insight, automation, and data-based guidance of AI is a welcome relief.
Personalization is an evolving area. Despite the benefits of AI and machine learning, there is still a lot of trial and error to go. But, there’s good reason to stick with it, doing our best to implement the technology that works and to apply it to our own marketing models. It’s not just that innovative teams will start figuring out more effective methods. The machines are going to start revealing even more of what we can do as they get smarter. You’re better off with a marketing team that is already familiar with AI basics when the business and consumer world dives even deeper into an AI-driven existence.
Marketers, on their own, may take some time to significantly improve their personalization efforts. But, we have machine learning on our side, an intelligence that is always getting smarter, a lot faster than us humans will ever figure it all out.