As technology advances, one of the biggest trends gaining momentum in the marketing world is real-time personalisation.
This is a way for organisations to present customers with what they want, at the right time, with content that hits the mark. This strategy dramatically affects revenue because it makes it easier to engage customers, lowers the cost of getting and keeping customers, and makes customers more loyal.
Real-time personalisation has been shown to increase revenue significantly.
This is because customers are more likely to purchase products or services that are tailored to their specific needs and interests. With real-time personalisation, organisations can present customers with personalised recommendations, discounts, and content based on their past behaviours and preferences. This helps to build trust and rapport with the customer and encourages them to make repeat purchases.
Another benefit of real-time personalisation is reducing customer acquisition and retention costs.
Organisations can improve customer engagement and loyalty by presenting customers with personalised content. This can lead to a decrease in the price of acquiring new customers and a reduction in the cost of retaining existing ones.
However, there are some key challenges to implementing real-time personalisation.
These include data management, scalability, privacy concerns, and the ability to deliver personalised content in real-time. To overcome these challenges, organisations need to have a solid framework in place, along with best practices for managing data, deploying AI models, and delivering personalised content.
Artificial intelligence (AI) is core to personalisation at scale.
Data science is the differentiator in this field, and the ability of organisations to build AI models quickly and deploy them effectively is key to success. To do this, you need to know a lot about the data and have experience with machine learning and other AI technologies.
Building a personalisation engine requires a well-defined framework and best practices for managing data, deploying AI models, and delivering personalised content. This means getting to know the customer really well, using data science and machine learning to build predictive models, and putting in place scalable systems for real-time content delivery.
Looking to the future, real-time personalisation is set to become an even more important trend in the world of marketing.
As technology continues to evolve, organisations will need to be able to adapt quickly to changes in customer behaviour and preferences. The ability to deliver personalised content in real time will be a key factor in the success of any marketing campaign.
In conclusion, the future of marketing is all about real-time personalisation. By presenting customers with personalised content that is tailored to their specific needs and interests, organisations can increase revenue, reduce acquisition and retention costs, and improve customer loyalty.
However, in order to be successful, organisations need to have a solid framework in place, along with best practices for managing data, deploying AI models, and delivering personalised content.
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