Artificial intelligence (AI) is already playing a vital role in the way that businesses interact with their customers. According to research from SemRush, over 80% of marketers already use AI (chatbots) as part of their customer experience strategy. A further 40% of businesses say that customer experience is their top motivator for using AI.

AI is being used for a myriad of customer-focused tasks, including offering personalised product recommendations, and predicting how customers will behave. If you’re keen to unlock the full potential of AI but are struggling with the application, we’ve covered five of the most impactful ways AI could help customers interact with your brand.

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Personalisation

AI enables companies to collect and analyse vast amounts of anonymous data about customers. This allows them to personalise interactions and advertising. By guiding visitors through increasingly individual journeys, businesses can both achieve their KPIs and ensure a satisfying customer experience.

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Rollouts

The number of successful product launches fuelled by innovative ideas speaks volumes about the strength of an organisation’s innovation process. Tesla and their ground-breaking vehicles that have shaken up the automotive industry. They exemplify the power of transforming innovative ideas into game-changing industry disruptors. It’s a testament to the importance of nurturing a culture of innovation and creating a framework that allows groundbreaking ideas to thrive.

R.O.I in innovation encapsulates the financial gains, and positive outcomes from innovative initiatives. By evaluating R.O.I, companies can gauge the worth of their investments and their rippling effects. Innovation’s R.O.I is the key that unlocks:

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Predictive Analytics

Last year, VentureBeat reported that 95% of companies now integrate AI-powered predictive analytics into their strategy. Predictive analytics generally fall into three categories:  

• Decision trees, which place data into different sections based on certain variables. This is the simplest model and is easy to understand and dissect.  
• Neural networks, which deal with complex data relationships using AI and pattern recognition. This can work best when you have excessive data and no set formula to sort it.  
• Regression, which is used most in statistical analysis. It is best used when there’s a linear relationship between your inputs and can help to determine a formula.

Image Recognition

While facial recognition has been the source of some controversy, particularly in early iterations, AI models have achieved a 95% accuracy, backed by manual confirmation for identified exceptions. In addition to facial identification, AI-powered image recognition can also be used to identify products and make recommendations, such as a customer’s clothing or interior style.

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Fraud Detection

In previous blogs, we’ve discussed the benefits of AI in fraud detection. The sheer amount of data that can be crunched by an AI system can help to identify patterns – detecting fraud quicker and more accurately than the human eye. This can help companies to prevent fraud, keeping customer data and transactions secure.

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Sentiment Analysis

Also known as option mining or emotion AI, algorithms use text analysis and processing to shift data into positive, neutral and negative sentiment. It can be used to help inform customer opinion, and even uncover fake reviews, with increasing accuracy.  

While there are a number of ways AI can be used, they still rely on verification; ensuring that AI systems are performing as expected and that the results they produce are accurate and reliable.

This is particularly important in the context of consumer spending, where inaccurate recommendations or predictions could lead to wasted money and lost opportunities.

The impact of AI verification on consumer spend can be significant. For example, consider a case where a customer is recommended a product, based on an AI system that has not been properly verified. If the recommendation is inaccurate, the purchase may not meet the customer’s expectations. This can lead to frustration and dissatisfaction with the product, the entire shopping experience, and the brand overall.

Properly verified AI systems help businesses to better understand customer behaviour and make targeting more accurate. This in turn can lead to better product design and marketing strategies, increasing sales and customer loyalty, as well as reducing marketing and advertising costs.

Businesses with any significant customer service offering should be embracing AI systems to ensure that they are operating at their full potential and providing the greatest benefit to their customers.

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