With the huge breadth of machine learning and AI technology available, brands risk appearing creepy if they go too far with the details they use to create client experiences. This is the line brands should not cross.

Businesses want Machine Learning to be more human, but then ultimately, people get freaked out when it is.

To avoid frightening clients out by crossing unnecessary boundaries with their data, brands need to simply ask for a few things at the start of their relationship with the business. It’s best, to begin with, a light touch and fill in the details as the relationship progresses.

Below are the few dominant criteria that are needed to create digital experiences that are based on machine learning and human empathy.

1. Determine the long-term worth

The goal of machine learning-enabled technology should be to improve the human experience, not the other way around. Something that’s code smart doesn’t imply it’s people smart. Great AI and machine learning tackle consumer problems before they escalate into huge business problems that can’t be tackled.

The business challenges will likely evaporate once a company can solve their customers’ problems – and offer ongoing value. 

2. Maintain a high level of stickiness in order to foster loyalty.

Facilitating meaningful customer interaction is the best approach to creating memorable experiences that encourage repeat visits. If a company requests client data, there should be an equal exchange — or an offer — to the customer. Continuously seeking reviews on past purchases can be one great step to this initiative.

3. Include measurements for behavior and emotion in your data sets.

Machine learning takes time, especially for businesses that depend primarily on first-party data culled from user interactions. Scroll depth, heat mapping, click mapping, content viewed, time on page, and landing exit page is examples of behavior tracking metrics that might provide useful information. Emotion tracking is also advantageous, with techniques such as sentiment analysis, face coding, voice analytics, gesture tracking, and more being available.

There are certainly privacy problems and creepy elements here, but businesses should smartly tackle them.

4. Develop a relationship with your customer while remaining cautious.

When it comes to using machine learning and AI in your marketing efforts, technology can sometimes reveal more about a person than their friends or relatives.

When leveraging advanced technology to create digital experiences, the consideration of openness should be taken into account. Transparency and open communication about how consumer data is utilized foster trust with customers will lead to a long-term partnership. When customers see how we use their data, it encourages them to give us more.

Another strategy that can be used is spontaneity, which involves proposing things outside of the algorithm in order to surprise and excite clients while learning more about them. This strategy always does wonders!

Honestly, not all businesses have the means or time to follow all these guidelines, but it’s always best to try. It is important to ensure that the machine learning technologies are integrated into the user design processes to determine the ongoing value one is providing.

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