How to deliver the best customer experience possible with predictive AI

Customer experience is THE differentiator for a modern, successful business. Being able to provide a compelling, valuable CX can lead to a variety of benefits, including improved customer satisfaction, better retention, and improved business performance.

Today's businesses are well aware of the critical nature of the customer experience in their future. 80% of companies that focus on CX report seeing an increase in revenue, while brands that are more customer-centric and focused on the customer experience report 60% higher profits. Companies that update their CX to be more data-driven find that by improving the customer experience they can reduce customer support costs by up to 33%. And companies are putting their money where it counts when it comes to the customer experience. Global CX spending is expected to reach $641 billion in 2024.

It's not just businesses that want a quality, value-driven CX. Consumers are willing to pay good money when interacting with a high-level customer experience, so long as they get something in return for it. For instance, consumers are willing to pay a 16% price premium in return for a superior customer experience. Data shows that customer spending increases by up to 140% following a positive customer experience.

And don't kid yourselves, today's consumers are more empowered than ever before and will bolt for another brand if they don't have a good customer experience. 49% of customers who left a brand that they are loyal to say it's due to poor CX.

But for brands to be successful in executing a superior CX, they must come to terms with the fact that the foundation of a value-driven customer experience is quality, accurate customer data. The reality is a data-driven customer experience is a better CX.

And while up to now the CX was predominantly fed with more traditional "observable" data, including first-party data like pages visited, clicks, adds to cart, and time on site, for the customer experience to proactively understand customer behaviors it must deploy predictive AI algorithms to deliver to consumers what they desire before they have had a chance to act on it.

What is predictive AI and generative AI?

The two primary AI models being deployed today in the enterprise business world are predictive AI and generative AI.

Predictive AI uses historical data to find patterns and anticipate future potential outcomes, while generative AI is more focused on the creation of new content assets, like images, text, and video from that data.

With predictive AI, businesses can better understand what their customers need, and what they care about. In this, businesses can finally move beyond making best guesses when detecting churn, scoring leads, recommending next best actions, forecasting spend, and making smarter decisions based on solid predictive data.

These two approaches to AI can be complementary if their algorithms are combined with the right software infrastructure that addresses data-oriented challenges like data quality, unified data integration, data integrity, identity resolution, and global data privacy compliance.

To be proactive, not reactive

Making decisions from aging data is always going to put a business on the back foot. They will be forever reacting to something that happened in the past. But if an organization can predict future outcomes, it can be prepared ahead of time for the actions of customers, market fluctuations, and even challenging economic headwinds. Predictive AI delivers the knowledge of the possibilities of what might occur and allows a brand to prepare a response before it happens.

To do this companies must invest in the right AI technology infrastructure that will give them robust, dynamic predictive data to feed their CX systems. 19 out of every 20 CX leaders have invested in or plan to invest in data integration, data integrity, or data enrichment technologies.

Faraday provides the data and the predictive AI modeling infrastructure (IaaS) that enables organizations to iterate on their business challenges, instead of their technology infrastructure. With our platform, brands, and the software companies who support them, can now develop end-to-end customer experiences, at scale, driven by predictive insights.

In the end, a data-driven CX is a better CX. Faraday is the only predictive AI platform, both for software teams and brands, dedicated to predicting customer behavior. Everything you need to make customer experiences predictive is built into our software.

Conclusion

How important is the customer experience to the modern business? According to Gartner, 80% of organizations expect to compete mainly based on CX. 90% of businesses, regardless of their vertical market, have said they have made CX their primary focus.

For companies to realize this potential, they must have quality, accurate data to feed the CX system. By only using observed data companies remain inherently reactive, not proactive. To be proactive in serving their customer's needs, brands must deploy predictive AI software technology to deliver the dynamic, enhanced data needed to power the CX.

Through predictive analytics, brands can deliver a superior omnichannel customer experience, anticipate future trends, identify customers' behaviors and future needs, and proactively prevent customer churn.