Three vital considerations for strategic AI implementation

Artificial intelligence has started playing an important role in customer experience and marketing.

It is generating predictions about what customers are likely to want, when potential demand will arise or propensity to switch will occur, and which channels they are most likely to engage on. As a result, AI is critical for brands wanting to improve their capabilities to offer personalised experiences.

What’s more, there is a strong business case for investing in AI to deliver high-quality personalisation at scale. Personalisation is key to customer loyalty and experience – Google found that only 43% of UK customers felt that retailer websites got to know their preferences or personalised content for them. Enhancing the ability to engage with customers on an individual basis is critical for brand success. 

But investment alone is not enough. For AI to provide effective personalisation, it must be leveraged appropriately by a gradual rollout of progressively sophisticated use cases while respecting consumer privacy. 

For successful personalisation, business leaders must develop a clear strategy for implementation, look beyond initial hurdles, as well as establish governance to ensure utilisation and value realisation.  

It’s essential to understand that merely having AI and machine learning capabilities does not guarantee that a brand can offer a higher quality of customer experience. To see significant improvements, organisations must decide what customer experience problem they are aiming to solve, which data sets they need, and how they are going to use them to remove the particular pain-points that customers face. 

Whether a brand wants to convert more website views to purchases, increase the number of customers returning to the site, offer a smoother transition across different touchpoints or improve online self-service, these priorities must be decided from the outset. Then, the right data can be collected and harnessed to address it. With an overwhelming amount of data being generated and compiled by companies, this is an effective way to streamline efforts and ensure the most critical issues are dealt with first.