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retail data analytics
   

Insights to Impact: Boosting Sales with Retail Data Analytics

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Once slow-influencing and driven by intuition, data and analytics has now become a game-changer in the retail industry. As we move towards increasingly data-powered environments, assuming that just dipping toes in the data & analytics pool will address all your business challenges is not a wise proposition. To make effective use of data, you need to have a powerful data engine that quantifies the actions and differentiates growth champions from the rest.

With this in mind, let’s first understand retail analytics and how it helps businesses. Let’s take a look at retail data and how retail data analytics help companies identify the most promising prospects and compete better in the market.

Jumpstarting Business Value Creation with Retail Data Analytics

To define in a simple language, retail data is a collection of information that quantifies business actions. The diversified range of retail data includes operational data, sales data, consumer data, inventory data, etc. As with any other information, data needs to be collected, processed, and evaluated to take necessary action - and this is when retail analytics comes to light.

Retail analytics leverages retail data and unlocks its true power. By providing insights into hidden patterns, it delivers significant improvements across different verticals like operations, inventory management, sales, supply chain management, and customer experience.

Empowering the Seller: Employing Data Analytics in Retail Industry

While the retail industry has made significant strides in the past few years, it has required some amount of data analytics to efficiently manage the business. To date, however, these analytics have been highly siloed within different business areas - such as planning and marketing - with little coordination or information sharing across business areas. With data analytics influencing so many business areas, it can be challenging for retail companies to thoughtfully invest in building their capabilities.

To effectively enhance data analytics capabilities, retail players primarily need to decide where analytics will achieve the business impact. They should develop a cross-functional roadmap and examine every aspect of their operations to spot challenges, unlock growth opportunities, and fully optimize data analytics investments. In the dawn of the big data-analytics era, let’s discuss the advantages offered by retail analytics and how growth leaders drive sustained growth by amplifying people's power with technology and retail analytics.

Interested in Retail Analytics? Get Actionable Insights at your fingertips

Advantages of Retail Analytics

Understanding Customer Behavior: In the opaque of changing customer behavior, retail analytics acts as a window to your customer preferences, journey, and behavior. Predictive analytics provides a 360-degree view of customers’ tastes and preferences. This way, retailers can estimate sales potential and rank SKUs per department. Additionally, you can personalize your service offerings and orchestrate the most fulfilling customer journey.

Effective Inventory Management: Effective inventory management can be notoriously tricky at times in the retail sector. While some retailers have struggled at maintaining inventory, others have leveraged predictive analytics to deconstruct obstacles and ensure the factory-to-shelf journey is effective and insightful. Data & analytics enable retailers to stay ahead of the supply-demand curve by aligning channels to opportunities based on various factors and generating remarkable results.

Cost Optimization: Data and analytics allow retail companies to maximize ROI at the customer level across different touchpoints on the buying journey. With efficient inventory management, enriched customer experience, and capitalization on timely opportunities, retail analytics help businesses optimize costs in many ways. From launching a marketing or sales strategy, streamlining operational tasks, or managing stock at warehouses - retail leaders will find themselves steering their sales force in a way that will positively impact the bottom line.

Analyze Trends and Spot Anomalies: As businesses move toward a data-driven approach, historical data holds as much significance as current data. A comparative analysis can be carried out with predictive analytics to identify trends that will be beneficial for the organization. Simultaneously, artificial intelligence in BI can also spot anomalies at the initial stage.

retail analytics

Decision-making: Winning in the Retail Industry

For cross-cutting decisions, the winning organizations lay emphasis on operational processes and ways to run decision meetings in an effective manner. Since cross-cutting decisions most often culminate from smaller decisions made over time, involving people from almost every department of an organization and deciding which KPIs matter the most for their retail business. Companies that excel at solving the paradox of growth and profitability by focusing on relevant KPIs and making effective coordination among different decision-makers and stakeholders.

Focus on KPIs: Make the Most Out of Retail Data Analytics

Leaving such essential KPIs untapped leave value on the table. Make sure you don’t miss out on them to extract the most out of retail analytics:

Sales per square foot: With foot traffic analytics, you can enhance store layouts to boost sales and space efficiency.

Gross Margin Return on Investment (GMROI): Quantifies profit gained on the amount that you invest in your inventory.

Year-over-Year Growth: It is one of the most common retail data KPIs that records a business’ performance against its last year’s performance.

Average transaction value: You can get an idea of how much your customers are spending by accessing retail sales data.

Inventory turnover: It measures the frequency with which your business offerings sell through.

Customer retention rate: Measures business growth based on its ability to convert one-time shoppers into long-term, revenue-generating customers.

Shrinkage: This KPI calculates the loss of inventory/stock that does not correspond to business sales.

Conversion rate: This KPI is an important component of retail sales analysis that measures the rate of converting viewers to shoppers.

KPIs provide you with a detailed picture of how your retail business performing. Now that you know the types of KPIs for your retail business, you can keep track of growth. And now that you can measure business performance with metrics, you can improve it. Are you ready to kick-start analyzing your data and setting the right business goals?

Polestar Solutions: Enabling Smart Business Decisions

No matter which metric you use, retail data is only useful when used effectively. Data is a critical business asset and Polestar Solutions helps you capture the full value of your data by implementing broad-based analytics, novel technologies, and industry best practices.

Polestar Solutions helps you become a future-forward retailer by doing a quick data analysis that will often surface the best suitable options to begin with, though additional work may be required to assess tricker security issues. So, what are you waiting for?

You are ready to become a DATA-DRIVEN + INSIGHT DRIVEN organization. Book a session with us today!

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