In 2019, retailers in the United States announced over 9,000 store closings. In 2020, the onset of COVID-19 has only exacerbated the problem. So far, over 27 retailers across North America have filed for bankruptcy, including legacy giants such as J.C. Penney, J. Crew, and Forever 21. As corporate restructuring ensues, players need to dive deep to address the underlying causes of the crisis in retail.
With the integration of e-commerce and omni-channel marketing, retail 3.0 possesses immense potential for expansion. Currently, retailers must confront the following questions in an ever-changing landscape:
The answers to these kinds of questions are crucial for a retailer’s success. A wrong guess has huge costs, both in time and in capital, and can lead to mistakes that have a sunk-costs which take much longer to recover from. For instance, each location has a cost that is directly proportional to the terms and duration of the real-estate lease.
Moreover, different customers engage and interact with products differently in their purchase journey. Younger demographics are more likely to access e-commerce end-points, while an older demographic could potentially prefer an in-person shopping experience. Participation by different demographics also affects how consumers think and feel about a firm’s brand, which is affected by a host of factors such as community involvement, discounted pricing, ESG initiatives etc.
With the availability of new social media platforms, customers are engaging with brands and organizations across multiple channels. More often than not, this interaction is taking place simultaneously rather than sequentially, often making it harder for retailers to identify what’s working and what’s not.
Each purchase from a customer affects the network of a retailer in a unique way. It’s imperative for retailers to identify these relationships to enhance the customer experience. Fortunately, DeepSpatial AI takes the guesswork out of optimization.
By utilizing robust datasets, our solutions not only assist firms in avoiding these mistakes but ensure that they leverage the full capabilities of what our solutions have to offer. With advanced analytics and machine learning, we analyze the business and the existing network as a complex system rather than an isolated sales end-point. The result - a more comprehensive understanding of operations, and a more effective growth strategy that can lead to double-digit revenue growth.