How Chatbots & Intelligent BPO Are Enhancing Customer Experience In Retail Industry

The rise of intelligent BPOs is helping retailers tackle newer challenges of rising transaction volume, business complexity, and the need for personalized instant services.
How Chatbots & Intelligent BPO Are Enhancing Customer Experience In Retail Industry

The post-pandemic era of isolation has shifted most in-person interactions to digital channels. We find most people reliant on either their phones or computer screens, exploring new products or interactions. There has been a huge shift in customer purchase behavior, and now, almost the entire purchase lifecycle happens online.

The retail business has been becoming more complex over the last several years, as consumers are increasingly shopping across multiple channels. The rapid shift of multiple product categories and customer segments to digital channels has made the retail business more challenging. According to a survey by eMarketer, customers’ topmost preferences remain instant gratification, faultless service, and trendy products. The rise of intelligent BPOs is helping retailers tackle these and newer challenges of rising transaction volume, business complexity, and the need for personalized instant services.

Intelligent BPO is a relatively new term that is used to describe a service model that entails extensive use of digital technology. While AI attempts to solve cognitive problems associated with human intelligence, bots help to optimize speed and quality of interactions as well as back-office operations. In other words, intelligent BPOs are those that are capable of:

- Implementing AI-driven virtual assistants and intelligent chatbots that can handle simple to moderate customer conversations over chat

- Optimizing complex workflows through robotic process automation (RPA) and self-learning algorithms

- Effectively using data analytics and business intelligence tools for customer insights

- Transforming business processes to enable effective digitization and automation

- Employing solutions like natural language processing (NLP), semantic analysis, and intent analysis to understand a customer’s unstated needs and disposition.

Let’s understand the impact of these technologies on customer purchase and support experience and how they create value for the retailer.

How is AI Improving Customer Purchase Experience?

Companies that can create personalized experiences for their customers by leveraging intelligent digital technologies are winning in the competitive space by reducing friction in the buying process. There are many ways in which AI and intelligent chatbots are improving the experience and therefore the rate of acquisition.

- Personalization and customer insights: Intelligent chatbots help in understanding customer attitudes, unstated needs, and customer disposition. AI-powered chatbots also help offer personalized recommendations. An interesting example is Mira, an AI-based chatbot from Flipkart that led to a 12% increase in online orders.

- Handling complex queries: AI technology utilizes natural language processing to help customers navigate through the enormous product listings and finding the product of their choice in the quickest possible time. A premier omnichannel fashion retailer in the USA needed to manage a high volume of interactions and used an optimized chatbot to find the product of choice.

- Visual curation: Algorithmic engines are helping translate customer’s browsing behaviours into digital retail opportunities through image and video-based search and analysis, and curating recommendations based on customer insights.eBay launched an image search on its portal in 2017, which allowed customers to use pictures instead of keywords to search for products.

- Workflow optimization: Intelligent automation is helping retailers streamline their inventory, staffing, distribution, and delivery workflows in real-time, helping them meet customers’ expectations for immediate access and support.

- Demand forecasting: Accurate demand forecasting helps in improving customer experience by improving order fulfillment accuracy. Data analytics can help mine through heaps of customer purchase and social behavior data to forecast customer demand for a festive season.

How is AI improving customer service and agent productivity?

The quality of customer service strongly influences customer loyalty and future purchase patterns. Some advantages of deploying AI and intelligent bots for customer service in the retail industry are:

- Transitioning basic customer service to self-help: Research indicates that chat/self-help is the most preferred customer service channel. This has the potential to reduce customer service costs by up to 40% for retailers.

- Faster response times: According to one estimate, almost 25-30% of the time of an agent is spent searching for relevant information to complete a task. According to a Juniper Research study, a chatbot can potentially reduce average handling time by 4 minutes per query, compared to traditional call centres. Virtual agents can further speed up response times by nearly 100%.

- Comprehensive understanding of Net Promoter Score (NPS): AI text analytics when deployed on customer feedback from all channels, helps understand the correlation between feedback and NPS scores and further helps them to deflect fluctuations within NPS.

Deriving Business Value:

AI, NLP, RPA, and chatbots are some of the most sought-after solutions by the retail industry today. Research by Gartner predicts that close to 66% of all Customer Experience (CX) projects are expected to rely on IT solutions by 2022, and over 40% of all data analytics projects will be driven by the need to understand customer behavior and attitude. Another Microsoft research quotes that by 2025, as many as 95% of all customer interactions will be through channels supported by AI technology.

Technology investments need to deliver predictable value for the business. According to a Boston Consulting Group study, retailers that adopt AI-based technologies have witnessed their revenue increase by 6% to 10%, two to three times faster than those who do not. Each retailer needs to develop its own roadmap to ensure they derive value from investments as their customer base, and value proposition is unique to them. They should prioritize high-value opportunities that can create immediate impact to build momentum for enterprise implementation.

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