It may seem like the latest AI solutions are already being applied everywhere, but this is not yet the case. Despite discussions in the media and industry in 2023 about the potential applications of AI and advances in analytics technology, we are still on the cusp of large-scale adoption in business. For example, at the end of 2023, a survey showed that more than 80% of companies agree that the ability to remain competitive will depend on using AI for customer analytics to improve customer experience (CX), but less than a quarter did. Our experience with consumer packaged goods (CPG) manufacturers has shown us that there is wide variability in the maturity of customer analytics between and within industries.
A few organizations are already creating advanced insights with the latest AI solutions, leveraging natural language processing for predictive analytics, generative AI or recommendation engines. However, many don’t do this because they struggle with other fundamental elements of a successful customer analytics program. For example, they may lack a well-defined data strategy, have siled data that prevents a customer-centric view, or need skilled talent to use digital analytics tools. If organizations can close these fundamental gaps, this could be the year that AI solutions gain enough momentum to transform the way businesses conduct customer analytics.
Deliver a better customer experience
Clearer insights allow businesses to deliver better experiences at many points in the customer journey. Effectively leveraging customer analytics can enhance customers’ feelings of recognition and ensure that offers and communications are more targeted and timely. By analyzing customer responses to AI-generated enhanced product recommendations, businesses can more accurately forecast demand, reduce the risk of out-of-stocks, and gain valuable insights into services and product experiences. Using this data for continuous improvement allows companies to refine their offers and improve customer satisfaction.
Some CPG brands are already using analytics and AI for better customer experiences. A global FMCG company collects and analyzes customer data to understand their needs and how customers think their products compare to competitors’ offerings, sentiments around specific ingredients, how customers talk about the company’s products online and which influencers the company should work with.
Make better decisions faster
Real-time customer analytics gives businesses immediate insights they can use to improve their customer interactions or share to help their customers improve their own customer experiences.
Some B2C companies are already using AI technology in their customer support channels to analyze contacts based on customer stress levels and the quality of support provided. For example, AI-powered chatbots can generate contextually relevant and human-like texts to respond to consumers in real time, thereby expanding and improving customer service and advice. Later, insights from these interactions can help adjust the support experience to reduce stress and minimize customers’ need to seek help.
Improve sustainability
Better customer analytics capabilities can also help businesses address increasingly pressing sustainability priorities. According to recent data, 61% of organizations are seeing a lack of sustainable practices as “an existential threat,” and nearly half believe climate change will be the biggest disruptor to business over the next 10 years. As a result, 52% of business leaders are investing more in sustainability initiatives this year.
Analyzing customer feedback and preferences can provide valuable insight into the product’s desired features, functionality, and sustainability attributes. Companies can use this information to design and develop products that meet customer needs while minimizing environmental impacts throughout the product life cycle, from material sourcing to end-of-life disposal. . For example, a global luxury brand uses predictive analytics to forecast demand to avoid overproduction that would create waste and additional expenses related to disposing of unsold products.
Customer analytics can also help businesses track key sustainability metrics and KPIs such as carbon footprint, energy consumption, waste generation and recycling rates. By monitoring performance over time and comparing it to industry standards, companies can identify areas for improvement and implement strategies to improve sustainability across their operations.
More than AI tools: succeed with customer analytics
AI is the engine that powers these customer analytics use cases, but other elements provide the fuel. Without these essential components of a strong customer analytics program, AI investments in this area cannot maximize ROI.
Client orientation : The organization needs a truly customer-centric mindset and culture that prioritizes thinking about customer data in a way that enables innovation.
Structure: Organizations that still have siled data need to finally break it down and democratize it so that teams can derive insights across the entire customer value chain. This type of restructuring reflects and reinforces both the customer-centric strategy and culture.
Talents and expertise: Your analytics teams need strong data skills and a customer-centric mindset. Whether internal specialists working in a center of excellence or external support from an experienced partner, the combination of analytical acuity and customer focus is essential.
Data collection and analysis solutions: Collecting, integrating and analyzing data from existing and emerging touchpoints is one of the biggest challenges for many organizations.
Technology: The right AI tools can help organizations achieve many of the outcomes discussed above. However, the ROI of analytics solutions will largely depend on the quality of other elements of the analytics program.
The examples we shared above, of companies using customer data and AI for CX improvements and innovations, are possible because these companies also have customer analytics program elements in place. As more companies adopt AI and related technologies this year, the fundamentals above will be the keys to getting the most out of these next-generation investments. Having the right foundation will help businesses do more, faster, with their new technology investments for customer experience and business decision-making.
