Hyper-personalization in customer service
Posted: Tue Jan 21, 2025 5:05 am
Treating customers individually is what makes hyper-personalization a trend that is here to stay, and that will gain prominence over the years.
A survey conducted by McKinsey stated that companies that know their audience and invest in hyper-personalization generate 40% more revenue compared to those that do not.
Another piece of data also released by McKinsey is even more interesting and mexico phone number library advantageous for companies, because 78% of users said they would buy again from places that produce hyper-personalized content.
And our goal is to show you how to offer quality service through hyper-personalization, and everything you need to know about this subject.
In today's world, it is not enough to have a great product and an excellent price, you need to put yourself in the consumers' shoes and see that each person has their own desires and individualities.
What does this term mean?
The idea is to provide highly personalized experiences, including: recommendations of solutions based on purchase history, the ads viewed, using artificial intelligence and machine learning to create situations focused on each person.
A survey conducted by McKinsey stated that companies that know their audience and invest in hyper-personalization generate 40% more revenue compared to those that do not.
Another piece of data also released by McKinsey is even more interesting and mexico phone number library advantageous for companies, because 78% of users said they would buy again from places that produce hyper-personalized content.
And our goal is to show you how to offer quality service through hyper-personalization, and everything you need to know about this subject.
In today's world, it is not enough to have a great product and an excellent price, you need to put yourself in the consumers' shoes and see that each person has their own desires and individualities.
What does this term mean?
The idea is to provide highly personalized experiences, including: recommendations of solutions based on purchase history, the ads viewed, using artificial intelligence and machine learning to create situations focused on each person.