Artificial Intelligence will make personalization too good to opt-out

Experience is personal , so I believe to change lives and foster the type of creativity, openness to diversity, and self-exploration that enriches personal and professional outcomes. What kinds of products and networks can make this more accessible and affordable to all? Whatever products and employers lean in this direction will prosper. Ultimately, we all either follow the trail of great talent or fall behind.

My growing contrarian view about the trend of privacy and opting out of ads is that artificial intelligence will make personalization so damn incredible that opting out will be the equivalent of using an old flip phone or going to a restaurant and getting served a random dish. This is especially true for the next generation that prefers transparency over privacy. , “Ads” conjures up the era of annoying banner ads and pop-ups. But “personalized experiences” are the new advertising, and most of us would prefer it whether we admit it or not.

We already want personalized experiences: We want local restaurants to know our names and preferences. We want shoe stores to remember our size. We want online food markets to hide the food we’re allergic to.

If you subscribe to my view that technology, it takes us back to the way things once were — but with less friction and at a far greater scale. We’ll want AI-driven immersive experiences to know us well, but not at the expense of our security and comfort.

The Hyper-Personalization Framework For Driving Customer Engagement

The decision to shifting to a hyper-personalized approach may be easy but the implementation can seem complicated. In fact, as of 2022, only 10% organizations have achieved complete implementation till date. For most companies, technical hurdles seemed to be the greatest challenge in the implementation process.

In order to build an effective hyper-personalization framework, it’s important to overcome the conventional approach of basing strategy on just data and adopting an analytics-driven approach for measurement of the data.

In the hyper-personalization landscape, brands need to modify their marketing tactics to meet the customer’s needs. To collect, measure, analyze, and eventually action the data, you’d inevitably need a customer engagement platform. This can always be Engagement Optimization Features to meet all your engagement and incentivization requirements. The best part is that the vast array of services it offers will help you hyper-personalize your marketing efforts, without writing a single piece of code! With a simple SDK/API integration, you can create, control, modify and monitor engagement journeys without having to develop them from the scratch.

Some of the features can be :

• SmartSegmentation — To create preferred audience buckets based on demographic and behavioral data.
• SmartNotifications — To send the right message through the right channel.
• SmartSurvey — To get customer feedback about your product or service.
• SmartGeofencing — To connect with an audience right where they are.
• SmartEngagementScore — To understand how engaging your app is.
• SmartReferral — To help grow your app via word-of-mouth marketing.

As always (at least in my mind), design is the solution. UX design, AI policies, and practices will be at the forefront of building customer relationships that let us hyper-personalize future experiences at scale without compromising trust.