AI’s golden rule: Good data inputs = better AI outputs

As consumer behavior continues to evolve under the constant influence of some of the biggest, most customer-centric brands on the planet, companies must stay agile, adaptable, and in lockstep with their customers’ ever-changing needs and expectations. Customers want what they want, when they want it. This is where real-time data becomes indispensable.

For your business to remain competitive, data is your strongest asset. The quality and availability of data enables how quickly you can respond to customers and adapt to market challenges.

Think about how we interact with and serve our customers as an equation: Real-time data is the input, and the ability to respond to a customer’s needs in real time is the output. At its core, real-time data captures and acts upon information as it happens, like in a physical conversation, without the delays and latencies that have traditionally plagued data processing pipelines. In the context of customer experience (CX), real-time data empowers businesses to understand and respond to consumer behavior in the moment, enabling a level of personalization and relevance that dazzles.

The AI golden rule

Consumers have a lot of choices—where they eat, where they stay during travel, how they get there—and many more. Consumers will continue to either choose the only option offered or the best option for when multiple are available. Data is how companies get an edge by understanding their customers’ desires and giving them better experiences. And as we already know, the fastest one wins.

As we embark on this new frontier of data-powered business, there’s a lot of noise around just throwing AI at the problem. It’s imperative to understand that AI is only as good as the data you feed it. This is what many experts call the AI golden rule.

AI models, especially those based on machine learning and deep learning techniques, thrive on vast quantities of diverse and up-to-date data. Consented and enriched real-time data provides a continuous flow of the right information, allowing these models to continuously learn, adapt, and refine their predictions and recommendations as consumer behavior shifts.

Many forward-thinking companies are focusing on widening the bottom of the funnel. While some businesses concentrate on pushing more into the top of the funnel, others believe in building a more efficient engine. By leveraging real-time data and AI, they aim to increase conversion rates significantly, making the entire process more effective.

For example, consider the success of e-commerce giants. They rarely lose customers, except in cases of impatience. This anecdote speaks volumes about the need for real-time data and AI-driven experiences. When customers want something, they expect it immediately. The companies that can deliver the best experiences to their customers, powered by real-time data and AI, are the ones that win.

Build a strong foundation

Despite the recent hype around AI, it’s crucial to remember that there’s no easy “AI button.” The path to successful AI implementation requires a strong data foundation. Many companies make the mistake of hiring numerous data scientists and giving them a massive haystack of data to sift through. This approach is not only expensive but often ineffective. Instead, we need to be purpose-driven in how we approach data.

This is where the concept of “moments that matter” comes into play. In today’s world of shortened attention spans and abundant choices, customers will quickly move on if they’re not getting the experience they want. Real-time data, when properly harnessed by AI, allows companies to identify and capitalize on these crucial moments, delivering personalized and relevant experiences that keep customers engaged.

Moreover, real-time data plays a vital role in various AI applications beyond customer-facing interactions. It fuels predictive analytics, enables more accurate forecasting, powers virtual assistants and chatbots, and drives real-time decision-making processes like dynamic pricing and supply chain optimization.

However, it’s important to strike a balance. While real-time data is powerful, it’s not a cure-all. Organizations must consider the cost implications of duplicating data across multiple systems and develop a well-architected data strategy that incorporates both real-time and batch processing capabilities.

As we look to the future, the next best experience driven by AI is the holy grail. But to achieve this, companies must focus on the quality of their data foundation. The fact that few are succeeding in this area speaks volumes about the challenges involved and the out-of-the-box thinking required.

In the age of AI and rapidly evolving consumer behavior, real-time data has become the beating heart that powers personalized, adaptive, and responsive customer experiences. By embracing real-time data as a strategic asset and integrating it into their AI initiatives, businesses can stay ahead of the curve, continuously meet and exceed customer expectations, and thrive in this new era of AI-driven experiences.

Mike Anderson is founder and CTO of Tealium.

https://www.fastcompany.com/91180070/ais-golden-rule-good-data-inputs-better-ai-outputs?partner=rss&utm_source=rss&utm_medium=feed&utm_campaign=rss+fastcompany&utm_content=rss