Retail in Real Time

Retail is constantly changing and so is the way consumers shop. The growing demand for a market of one experience is driving retailers to adopt data strategies that are designed to help them understand their customers. Having insightful information on customers, their behaviors, likes and dislikes, and even their families and friends tendencies are extremely impactful when it comes to pairing customers with products.

We as consumers are no stranger to this in the world of e-commerce. Online shopping does a phenomenal job at putting what we like right in front of us, at the right time, to drastically influence our buying decisions. What about brick and mortar? How can I get that same high touch experience in store?

Sure, some of the largest retailers who’ve spent the last 15 years focused on consolidating their systems by hiring 20,000 employees can achieve this. What about the rest? The need to understand, interpret, and act on retail data, all in real-time is the new standard. Retail data analytics, when done right, is capable of delivering unparalleled results when it comes to driving sales, increased revenue, and decreased expenses. So what are some ways that unlocking all your stores data can benefit the retail organization?

Really know your customers

Big data from places like point-of-sale, customer loyalty, social media, and even location based services can help stores truly understand their customers. Artificial intelligence modeling derived from large data sets allow retailers to accurately predict future tendencies based on buying habits, monitored behaviors and social media sentiment. Customer location data analysis helps retailers evolve as their customers do. For example, knowing that a large population of people visit a single store from 30 miles away may facilitate the decision making process for future store placements.

Marketing teams are always looking for ways to attract customers to their brand. Integrating big data and AI simplifies the marketing strategies through predictive analytics, targeting subsets of customers and potential customers with customized ads – targeting location, proximity, and buying preferences. Retailers that can personalize to this level of precision are optimizing their marketing budgets by removing the “trust your gut” approach, trading it in for clarity that they are reaching the right consumers with the right message.