Most discussions around AI, Big Data, and IoT revolve around the benefits they can offer to businesses. Running a more data-driven company is certainly a noble goal, and it is one of the smartest ways for businesses to stay competitive in today’s business world.
We know that using this technology can provide business leaders with the exact data they need for smarter and more effective strategies, especially for planning, predicting trends, and audience targeting.
But one conversation we often fail to have is how AI can help the most important person in the business: the customer.
Having a customer-focused approach to business is essential to long-term growth and success, as well as improving the overall experience. So where do AI and Big Data technology fit into the Customer Experience (CX)?
Let’s talk about it.
Resolve Problems Faster with Feedback Data
One of the best ways for a business to improve is by paying attention to customer reviews. Often times, these ratings are full of insight directly from customers about what they enjoy and dislike about a company. However, looking through these reviews and gleaning important information or identifying recurring pain points can be quite time-consuming – and almost impossible for larger organizations.
Machine learning technology can be applied to customer feedback to sort through reviews and identify patterns in both complaints and compliments. Let’s use the company Trustpilot as an example here. They have collected hundreds of customer reviews from various sources online, which would make it quite difficult for manual examination. By using machine learning to analyze review text, each review is processed and can then be organized by using tags based on keyword mentions, such as returns or service.
This tagging system is excellent for segmentation and a narrower approach to problem resolution. By using natural language processing (NLP), machine learning systems are able to determine the overall sentiment and provide the necessary information regarding areas where changes need to be made that will improve the customer experience.
For example, one customer mentioned that they had an issue with the survey template and wished that Trustpilot was able to integrate with other programs for a centralized dashboard. This review could be categorized under dashboard , analytics , or survey templates. If any of these tags started to receive a large number of negative reviews, Trustpilot’s team would be notified for further investigation.
Once these patterns have been identified, active changes can then be made to improve the experience for future customers. In Trustpilot’s case, they took Aziz’s review to heart and even posted a response regarding his recommendation. By using this approach, Trustpilot was able to identify a common issue and actively make changes for better customer experience in the future.
Use Data Sets for Predictive Problem Resolution
Reaching out to customers at the perfect time is a key aspect in providing a better CX. AI and predictive technology can be used by the customer service department to warn of potential issues and step in with assistance before a customer even reaches out.
This approach combines past behavioral data with real-time analytics to predict what a customer’s next move may be and what problems could possibly arise. The Royal Bank of Scotland currently uses this approach to track complaints and predict questions or issues that customers may have in the future. They use AI to link complaint data to customer interactions so that proper information is issued out to the specific user. For instance, if a customer is having trouble getting their debit card to work, the bank could immediately email information to the customer about what the issue could be or even automatically order a new card – all before that person reaches out to a customer service representative.
Offer Truly Influential Personalization
Personalization is super influential on today’s consumers, and many either request or expect customized offers, discounts, and experiences from online retailers. Not only does personalization make a customer feel special, it greatly improves the CX and increases the likelihood of conversions. If a customer is only shown the products that are relevant to their needs and preferences, the chances they will add those items to their cart are higher than if they had to search for the products themselves.
The only way to truly offer personalized experiences is through loads of quality consumer data. Online retailer Stonewall Kitchen uses AI to create one on one personalization with each customer, which directly leads to a better experience and higher conversion rates. Their platform tracks consumer browsing patterns and uses this data for customized product recommendations via an AI sales assistant. As a result, their recommended products are added to a cart about 40% of the time.
Allow Customer Independence
Having customers reach out to your sales team or customer service through the phone or an email should be a last resort for an online business. Offering more self-help services which allow customers to find information or resolve a problem on their own can be quite helpful and support a better CX.
Of course, AI chatbots are quite useful in this regard, if they are created correctly. Obviously, the key here is to use chatbots wisely and ensure that the NLP programming is sophisticated enough to provide beneficial assistance. Using a conversational AI program is key for a smooth, pleasant experience that doesn’t make the customer feel like they’re talking to a computer program. Be sure to integrate aspects of your brand’s personality into the chatbot, like this engaging one from Charlie Finance.
Conclusion
AI plays a pivotal role in the success of modern businesses today, and it can either make or break the CX. By using the data and capabilities of this technology in areas where it will have the most impact in customer satisfaction, businesses can offer the exact information and experiences people are looking for, possibly even before the customer realizes this themselves.
