Personalization, speed, and responsiveness are the pillars of not only customer experience (CX) but customer delight.
Specifically, in the last five years, artificial intelligence (AI) has been a key enabler for SAP users, transforming the mode of customer interactions and experiences. As large and small businesses continue to recognize the value of better customer experience as a differentiator, AI has become an important component of users’ CX strategy.
Smarter Customer Relationship Management
We are quickly seeing the SAP customer base’s customer experience strategy as explicitly driven by emerging technologies; both those developing customer relationship management (CRM) and using CRM systems are equally dependent on technology. The process of interactions between businesses and customers has fundamentally changed, and customers can now obtain real-time insights into customers’ behavior, preferences, and needs by analyzing massive volumes of data, even before engaging them.
SAP users are easily able to automate their routine tasks and streamline communication with customers. All this has become possible because of AI, which helps various SAP users to know their customer comprehensively, using customers’ purchase and interaction histories, their time spent on various products, and their social media presence while accessing the similarities between customers and other buyers. Many SAP users effectively use such contextualized data for recommending new products, enabling better services, and building smarter relationships with their customers that differentiate them from competitors.
Role of Intelligence in improving Customer Experience (CX)
Intelligent sales and services offerings, including within SAP Sales Cloud and SAP Service Cloud V2, are already helping SAP users in the following areas to improve their customer experience:
- Improving forecast accuracy, identifying at-risk opportunities, and increasing win rates with embedded generative-AI and machine-learning intelligence.
- Automating the translation of incoming emails from source language to log-on language, enabling recipients to comprehend and engage with content in their natural language
- Natural language processing (NLP) classification scenarios include a “sentiment” output field that determines if the vocabulary used in a survey is positive or negative, as well as the degree of positivity or negativity.
- Conducting thorough analysis for the presence of profane words, promptly issuing warnings in cases where such language is detected to maintain a professional, respectful communication environment.
- Using Email Draft Recommender, executives can draft the perfect sales pitch email, describing the product or providing a service update about reported cases, improving efficiency, and enhancing the quality and personalization of communication.
- With the Case Interaction Summary and Solutions Recommendations feature, service executives can save time reviewing email interactions between customers and service agents, summarizing the entire conversation history in a paragraph and suggesting solutions that have resolved similar reported cases.
- With Lead Booster, a game-changing feature, sales representatives can target the right deals by understanding customers’ needs and preferences, existing products, and what solutions they may need. Lead Booster creates an Intelligence summary of an account, describing challenges and possible alignment with other accounts.
- Using the Account Synopsis feature, sales and service teams can gain a holistic view of the sales account in different dimensions, such as business, culture, competitive landscape, etc., resulting in a complete picture of an account.
Some standout AI use cases are:
- Starbucks’ Predictive Analytics: A tool with machine learning and predictive analytics, Deep Brew suggests menu items based on a customer’s past orders, location, weather, and time of day, among other factors.
- Sephora’s Virtual Artist App: This app uses Augmented Reality (AR) to allow customers to virtually “try on” different makeup products. It scans the customer’s face and lets them see how different products look on their skin before actually purchasing them.
The Future of Artificial Intelligence in Customer Experience
Artificial intelligence is set to play an even larger role in CX as we head into the future.
Here are some trending AI features and tools for better customer experience in the coming future:
At Wipro, which provides its customers with preconfigured templates for SAP Sales and Services Cloud Version 2, in addition to AI-based CX solutions developed on SAP Business Technology Platform and integrated with V2, we believe in delivering the best customer experience through products and solutions. To remain aligned with current business needs around AI, Wipro consistently updates and produces solutions with embedded intelligence.
One of our Cognitive Customer Service (CCS) Applications, using intelligence at its peak, reads past interaction history and contextual data to predict the reasons for interactions using ML in real time. It also has Next Best Action Determination and Process Automation capabilities. Wipro is focused on generative AI-enabled solutions, such as conversational assistants and sales & marketing assistants for different industries like healthcare, Insurance, gaming, and marketing. Wipro is also ahead in developing AI-enabled solutions for procurement.
How AI Helps Businesses
When a sales executive steps out to sell any product, his most difficult task is which audience to target, considering who has more propensity to buy. Most of the time, as consumers, we just ignore the promotional calls or the executive trying to pitch us somewhere in public.
Using AI, sales executives can reach audiences that have shown interest in any specific product source. While selling, sales executives can also leverage AI to build accurate sales databases, with correct and verified addresses, phone numbers, and percentage of successful sales. With this, sales executives can reach maximum sales targets. AI’s predictive forecasting, customer segmentation, and churn reduction methods assist with all the above areas.
And for sales executives weary of following up with customers they’ve met but haven’t converted into deals, AI’s Deal Intelligence and Predictive Scoring capabilities can help, providing executives with insights and a percentage score of prospects moving toward closing deals.
Similarly, a service executive struggles to collect all the information for a service ticket or case they’re working on, between the team and customer care; they must repeatedly ask customers to identify problems and search for different solutions, which reduces their productivity and diminishes customer trust. Using AI’s interaction summary and solutions recommendations, these executives can quickly obtain summaries of entire cases in paragraph form, and recommended solutions from similar resolved in the past.
Artificial intelligence is no longer a technology of the future – it's today’s technology, shaping our tomorrow. By adopting AI at scale and implementing AI into specific business use cases, SAP users can drive their organizations forward and optimize the customer experience. To learn more about how to get started, contact Wipro today.