Tech

Leverage the Potential of Retail Merchandising Analytics for Higher Sales

Over the last decade, we have witnessed the tremendous influence of big data and analytics in the retail sector. Even before the advent of data science, the top retail companies kept track of key performance indicators. Be it the average billing amount, sales volume, or the return/exchange frequency, each metric yields important insights. In the current scenario, merchandising analytics are particularly instrumental in bridging the gap between customer requirements and in-store offerings. Therefore, the most successful retailers today are the ones who strategically convert analytics to action.

Advantages of Harnessing Retail Analytics

For some retail entrepreneurs, investing in big data might appear like an added or unnecessary cost. But examining the benefits of harnessing retail analytics to optimize in-store performance, the ROI makes it truly worth it:-

  • Streamlines a precision-based approach towards the key performance metrics that directly affect store performance and revenue
  • Merchandising Analytics provide valuable insights on the latest customer psyche- preferences, shopping patterns, trends, and so on
  • Channelizes your retail marketing investments in the right direction
  • Provides valuable insights to tailor products as per your key market segments
  • Aids in the creation of robust loyalty programs for customer retention
  • Helps with efficient in-store marketing activities for maximum conversions

Insightful Ways to Use Merchandising Analytics to Your Advantage

Work on the Key Growth Drivers

It is very likely for any retailer today to get entangled in the maze of metrics. But to use retail analytics to your advantage, it is necessary to wade through the clutter. Focussing on the right metrics will help you synergize various retail functions under a single umbrella. It will also help you weed out the loopholes and duplicities at the store-level SOPs that are hampering productivity.

Integrate a Uniform, Data-Driven Approach

The most successful retail start-ups today are the ones that have integrated data analytics across all functions and departments. As a retail entrepreneur, relying on data only for forecasting sales, footfall, and demand patterns is a half-hearted effort. While these aspects are pivotal, a holistic and data-driven organizational approach is required to outperform your competitors today.

Rely on Comparative Analytics

When it comes to comparing footfall trends, purchase behavior, and customer shopping patterns, comparing merchandising analytics is highly recommended. Consider a scenario wherein you are witnessing a sudden footfall decline post the festive season. Compare your footfall and conversion figures on the same dates for the previous year and the year before that. If you are witnessing de-growth, examine the average customer transactions and the best-selling products for that year. Based on these comparative insights, you can strategize your merchandising plan for the current year to maximize your sales potential.

Opt for Cutting-Edge Data Assessment and Visualization

Using an integrated EPOS system and inventory-management software inside a retail outlet is pretty much basic now. This conventional technology can no longer give you the much-required extra edge. The need of the hour is to step beyond regular tech and embrace cutting-edge data-led technologies. Some of the best examples include:-

  • AI tools for simulation-based data analysis
  • Dashboards to display growth driver metrics in real-time
  • Use of Infographics and Interactive Videos for Team Briefings
  • Well-updated, uniform, and error-free marketing database
  • Data visualization software to foresee trends and monetize them within the short opportunity window

In-Store Technology for Retail Compliance

No matter how many plans and campaigns you launch at your retail headquarters, in-store implementation is extremely crucial. Your marketing investments can be worthwhile only if there is proper merchandising compliance on the shop floor level. Monitoring the activities of multiple stores from a single point can be incredibly challenging. Using the relevant retail compliance software for daily reports, geo-fencing of stores, and monitoring employee activities is thus highly recommended.

Conclusion

Given the highly customer-oriented operations and logistical challenges in retail, the role of data analytics is crucial for retail compliance. It provides clarity of vision and aids in strategic decision-making to enhance both the customer experience and ROI. With the kind of vast, unorganized databases available with retail companies today, the focus should be on intelligent data assessment. Leveraging in-store analytics to enhance merchandising, productivity, and sales should be the ultimate aim for retailers in the post-Covid-19 world.

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