A recent article in Harvard Business Review on retailers failing to adopt Advanced Data Analytics got my attention. Despite its potential, only a few prominent players in the retail industry have fully embraced this technology. In contrast, others continue to rely on traditional tools that cannot accurately forecast market conditions and demands. Roadblocks to adoption may include organizational culture, lack of skill sets, legacy systems, and siloed data.

According to Gartner, Advanced Analytics is the autonomous or semi-autonomous examination of data or content using sophisticated techniques and tools beyond traditional BI. It can uncover deeper insights, make predictions, or generate recommendations by using techniques like data/text mining, machine learning, pattern matching, forecasting, visualization, semantic analysis, sentiment analysis, network and cluster analysis, multivariate statistics, graph analysis simulation, complex event processing, and neural networks. By applying these techniques, businesses can identify trends and patterns, address issues, make improvements, and make well-informed, profitable decisions while accurately predicting future outcomes.

Advanced Analytics impact on Retail

The retail industry is a vast sector that will continue to grow exponentially with the increase in the size of the middle class and its buying power. Advancements in smartphone technology, high-speed internet connections, better product lines, delivery, and payment options are driving the industry’s growth by generating valuable data. In addition, Advanced Analytics is a game-changer for retailers as it generates insights into customer behavior, financial performance evaluation, supply chain needs, and requirements for business operations.

Establish Optimal Assortment

Retailers can use Advanced Analytics to maintain optimal store assortment, leading to higher sales, better margins, and happy customers. The solution can identify products that are in demand and those that can be easily substituted, which is crucial in this new era of rapidly evolving customer preferences. Non-technical employees can also leverage the solution to make informed decisions and deliver high value. Granular-level data can equip businesses to micro-target their audience and personalize their products and services accordingly.

Enhanced Customer Engagement

Retailers face the challenge of establishing better customer engagement, especially with rapidly changing customer tastes, economic uncertainty, and other factors.  Advanced Analytics provides the appropriate solution to address this issue.  It helps retailers identify customers likely to spend more on specific product categories or predict customer churn, enabling retailers to develop a more effective customer engagement strategy and create an ongoing positive experience leading to customer loyalty.

Maximizing Retail Profits

An Advanced Analytics solution opens several opportunities for retailers to maximize profits by offering the right price for the right product at the right time. Retailers can integrate the proper pricing into their day-to-day operations and cater to customers’ unmet demands.

Supply Chain Optimization

Advanced Analytics makes it possible to optimize the supply chain and monitor its performance, enhancing the operational efficiency of the supply chain. Forecasting and efficiency are improved, and retailers can respond better to customer needs.

Retail organizations should undoubtedly invest in Advanced Analytics to enable strategic business decision-making, improve business performance, and stay ahead of the curve in today’s highly competitive market. However, data quality and accuracy are crucial for generating valuable insights, and retailers should invest in data quality management tools and processes. Retailers must also prioritize training their employees on how to use Advanced Analytics and incorporate data-driven decision-making into their operations to realize the full potential of the technology.