Our IT Executive Roundtables are invite-only events hosted by peers for peers that bring together a select group of senior IT leaders from across industries for topic-driven, intimate dialog on current trends and topics. The group met remotely to discuss growing your brand through customer experience led by the CEO and Founder of an emerging retail technology company. This Session was sponsored by Linc.
Data analysis and personalization are vital in growing a brand through better customer experience and optimized operations. Businesses can gauge customer sentiments, identify improvement avenues, and strategize better by analyzing data. So, what types of data can you capture for a better customer experience? And how can data help a business meet the ever-rising expectations of the modern customer?
From a business perspective, data can be divided into two categories: data about the customer and data for the customer. Both data types can be leveraged to solve business problems and enhance customer experience. Data about the customer is used for marketing purposes. It enables a business to personalize customer interactions, offer product recommendations, and build customer-centric products. Data for the customer allows a company to share time-sensitive updates with its customer, like real-time tracking of orders, shipping, and returns. This data can also be aggregated and analyzed to solve operational issues, like supply chain and logistical bottlenecks.
A participant said that the expectations of the digital consumer are higher than ever before. They expect brands to offer seamless omnichannel experiences. They expect to be able to access information about their orders and back orders with full transparency. They also expect a hassle-free return policy. It can sometimes be challenging for businesses to balance meeting customer expectations and being cost-effective. For example, you want a lenient returns policy with free shipping but don’t want to accept damaged goods. However, by leveraging customer and operational data, it’s possible to develop customer-centric strategies that are also feasible for the business. E.g., you can analyze a customer’s purchase history, feedback, and comments from the logistics team to determine whether someone qualifies for a return.
An attendee said that large volumes of data are only useful if you use it to generate actionable insights. Data-driven insights should enable businesses to make tangible improvements in different areas, including customer experience, supply chain, and marketing. For example, if you start analyzing data generated by your self-service system, you can identify trends like “How many customers are interested in product X?” “How many customers had a hard time using feature ABC?” “How many of the queries are made post-purchase?” and “How many customers are anxious about late deliveries?” These insights can enhance product design, optimize the buying process, improve customer satisfaction, and much more.
An executive told the audience that their holiday preparation usually starts in July and August. As part of the preparation, they ensure that their systems are scalable enough to meet the high demands of the holiday season. However, since they have moved to the cloud, they are exploring ways to build an adaptive infrastructure that can scale automatically, powered by headless and server-less platforms. Using advancements in the self-service and communication spaces, they are exploring ways to offer uninterrupted, 24/7 customer service during the holidays.
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