Retail Analytics: How to Empower Brand Managers to Better Understand Customer Behavior

by Dhiren Patel, Chief Product Officer & Head of Customer Excellence

Retail Analytics: How to Empower Brand Managers to Better Understand Customer Behavior

by Dhiren Patel, Chief Product Officer & Head of Customer Excellence

Over the last two decades, the retail industry has expanded beyond brick and mortar to establish a strong e-commerce presence. From giants like Amazon to niche players like Etsy, several e-commerce platforms have consistently gained market share. This has challenged retail businesses to reinvent their business models and constantly monitor market trends.

Challenges faced by Retail Companies

Need for a Tailored E-commerce Strategy

The “one size fits all” approach does not work while defining strategies across categories. Different categories have different end customer demands. A category like consumer electronics has to compete on price and customer support, while a category like home improvement has to compete on SKU selection and technical support. They require tailored e-commerce strategies. Niche players like Etsy and Wayfair are successful with a highly focused approach to their categories. However, as the number of categories increases, it becomes extremely difficult to compete with behemoths like Amazon.


A far cry from its humble beginnings as an online bookstore, Amazon now holds a dominant position in every retail market. Any retailer trying to sell anything to customers must pause and think about competing with Amazon either now, or at some point in the future. However, companies like Shopify enable small players to compete effectively by offering “e-commerce in a box.” This has helped tens of thousands of small business owners worldwide become sophisticated e-commerce players, causing fragmentation of the retail market.

Maintaining Customer Retention

With diverse categories and fragmented markets, retail businesses also face the additional challenge of retaining customers. Today, customers are just a click away from a competitor with a better inventory, price, customer service, or return policy. Knowing what customers want and catering to them effectively in real time is more critical than ever before. Inventory, supply chain, pricing, profitability, and customer service discussions are essential in influencing every single customer’s purchase decisions.

Finding Actionable Insights in Customer Data

Capturing and leveraging customer data in real time is essential for understanding and choreographing exact customer intent and actions. This data comes from different sources. It is diverse and granular, and needs to be distilled into actionable information to make an impact on the top and bottom lines.

How does MachEye help retail businesses analyze their data effectively?

Get quick answers effortlessly

Quick answers help make prompt decisions. With MachEye, searching data for answers is as simple as asking a question in a natural language. Any business user can ask “Top 5 categories by revenue in December 2020” or “product with the highest customer rating” or “Segment with most returns monthly for Huggies Little Movers Diapers 124ct” and take actions quickly. MachEye’s search based analytics encourages easy conversations with data that help retailers measure category performance, track effectiveness of promotions, and improve customer service.

Understand the “why” behind insights

MachEye goes beyond obvious insights to deploy relevant AI models that uncover anomalies, segments, or drivers based on customer behavior and granular data from e-commerce platforms. Then, MachEye helps you understand the reason why you see certain observations in your data. Why is a certain SKU selling more this quarter? Why is a certain geographic area showing weak sales for this SKU? Understanding the underlying causes of insights helps leaders plan strategies and tactics.

Achieve scalability in analytics

Diversity and granularity of data is critical in the retail space. For certain segment-level analytics, data volume and velocity are limited. However, for individual customer-level analytics, data volume and velocity can be a big challenge, requiring sophisticated data infrastructure and technology. MachEye helps scale analysis to large online datasets and handles addition of new data sets with ease, without any performance constraints.

Analyze real-time data without delays or duplication

Data may be siloed in different data stores for each business operation such as sales, marketing, customer relations, or supply chain. MachEye connects directly to data sources to provide insights from the latest data, thus preventing unnecessary time delays, data duplication, and quality issues due to different data silos and islands.

Encourage insight-driven decision making

Simple interactions with data help build confidence and encourage users across organization to adopt data analytics in their everyday activities. MachEye offers a simple search interface, interactive audio-visual insights, and access to insights anywhere and anytime - thereby promoting a culture of insight-driven decision making, not just simply data-driven.

Improve ROI with TCO reduction

Through rich user experiences, quick implementation, and no additional infrastructure requirements, MachEye ensures quick onboarding and greater adoption of analytics. This helps retail businesses maintain a low TCO, given the enormous top line and bottom line challenges faced by the industry.

MachEye can help retail businesses achieve agility and intelligence in their strategies and operations to help them keep pace with not only competitors but also the changing demands of customers.