From big boxes to web giants, the retail sector of the economy is embracing content intelligence as a key part of their marketing operations. Retail operators, facing stiff competition and ever-changing consumer tastes, are embracing big data, machine learning, and artificial intelligence as tools that can give them the competitive edge they need to thrive in a rapidly evolving world.
Today’s consumers have access to more information and expect a more personalized experience than ever before. Rapidly changing tastes require more accurate forecasting of business trends. Younger generations often build brand loyalty through a company’s narrative and values. The collection of technologies that make up the field of content intelligence make it possible to efficiently reach the needs of a wide variety of consumers, allowing both online and brick-and-mortar retailers to capitalize on their strengths and shore up their weaknesses.
Online retailers rely on AI-driven systems to fulfil the same role that a sales associate might fill in a store at the mall. Predictive analytics learn customer tastes and get more accurate with every purchase as data accumulates. These systems will display related products to each customer and can even account for factors that a human sales assistant might ignore, such as product availability or profitability of the item. A well-tuned system can increase profits per item or help reduce excess inventory by recommending overstocked items to consumers looking for equivalent products.
In a notable example of the above, The North Face, a popular outdoor clothing retailer, currently offers an app that uses a virtual assistant with natural language capabilities to guide the customer through the shopping experience. The system asks questions and interprets the answers to offer the customer relevant products. This type of technology can lead the customer to discover new products they might not have otherwise considered.
Another technology that is bringing businesses more power to drive sales are Content Strategy Platforms like CONCURED. When a business can provide the information that a customer wants and needs, trust in that business is automatically generated. That leads to more sales. Artificial intelligence can predict which topics a customer or an audience wants to read about next, or show where their competitors are addressing information needs that they are not.
The availability of massive quantities of customer data, captured at every touchpoint in the buyer’s journey, can be leveraged to build sophisticated models of the consumer’s needs and preferences, allowing the retailer to add value at each step and demonstrate to each consumer how they can meet their exact needs. This data can be used in many ways, from in-store recommendations to online retargeting of consumers to recommending specific pieces of content that will lead them down the funnel based on which pieces they’ve read before.
Many retailers are also benefiting from machine learning and artificial intelligence to manage inventory, especially in sectors where tastes change rapidly, or perishable items create wastage. For example, clothing retailers have in the past relied on experience and intuition to determine sales orders. The availability of highly accurate data and advanced predictive modeling has helped clothing retailers with problems from sending correct sizes to online retailers to finding clothes in stock based on a snapshot. The same technologies are helping grocers optimize fresh food inventory and fine-tune their product mix for different markets, as seen in the below image:
On the bleeding edge of technology, modern systems can use video cameras, image recognition software, and artificial intelligence to observe customer behavior in stores and build accurate models of customer flow and behavior. Data-driven insights replace more fallible reporting from salespeople in optimizing product layouts and locations, both improving the customer experience and increasing sales.
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