Top 5 Quick to implement yet cost-effective retail analytics solutions for accelerated sales!

The landscape of the retail industry is constantly changing. The rising competition and thin margins are imposing several challenges on the retail industry. It is no longer as simple as the Supply Vs Demand theory. Channels are proliferating and consumers expect more from their retailers. In addition to that, there is so much competition and direct-to-consumer & online pure-play companies are quickly grabbing market share. With tight competition, fluctuating markets and ever-changing consumer demands, retailers are struggling to keep up. Relying on intuition is no longer enough for success in the retail industry.

In this highly volatile environment, data has become one of the core competitive advantages. And those who best harness data to make core business decisions will be the real winners. And retail analytics plays a crucial role to make that happen. By analyzing large-scale data, retail analytics solutions can provide valuable insights that improve business models and respond to the demands of the industry to ensure stable profits. Retail analytics solutions is a deep discipline, covering many different departments and areas of the business.

Here’s 5 cost-effective yet easy to deploy Retail Analytics Solutions for accelerated sales.

1. Customer Behaviour Analytics

Customer behavior analytics is crucial to address challenges like improving customer conversion rates, predicting and avoiding customer churn and lowering customer acquisition costs. Consumers interact with retail through multiple channels such as mobile apps, social media, physical stores, e-commerce sites and more. When all of this data is aggregated and analyzed together, it can provide valuable insights about consumer behavior. These detailed insights increase the probability of customer acquisition and increase customer retention rate and brand loyalty. It can also answer some of the important questions such as which campaign combinations accelerate more sales or how to acquire more customers at less cost? Etc.

For example, a real-time video analytics system such as Emotyx can track customers and understand their needs. Emotyx’s emotion analytics can analyze customers’ emotions, their satisfaction level based on their on-premise activities. The intelligent insights generated from emotion analytics can be used to push personalized combo offers, product discounts, product recommendations, etc. It can also track customer’s affinity towards various products and their most desired product categories. Emotyx can be plugged into an existing CCTV infrastructure for on-premise real-time video analysis. It’s easy to deploy and one can view results from day one.

2. Big Data Analytics to personalize In-Store experience

In the past, merchandising was mostly speculation and there was no credible way to measure the specific impact of merchandising decisions. Thanks to retail analytics solutions, it’s possible to analyze store behavior of the customer and measure the impact of merchandising efforts. The data can be obtained through various channels such as Websites, Point-of-sale systems, Loyalty Card data, Mobile apps, Supply chain systems, and even In-store CCTV Cameras. The data-driven insights acquired from these channels will help retailers to optimize in-store experiences that provide unique value and pleasure for consumers. It leads to an increase in customer loyalty, cross-selling and promotion effectiveness.

For example, Retails can personalize in-store services for customers by analyzing their purchase and browsing history to identify their needs and interests. This information can be linked to loyalty programs to drive impulsive purchases.

3. Customer Journey Analytics

Now more than ever, the quality of the customer experience drives sales and customer retention. And marketers continuously need to understand customer’s needs and connect with them. This requires having data-driven insights that track each customer’s journey and history across channels. To precisely understand customer’s need and their journey, retailers need to integrate data from every channel — structured and unstructured — and analyze it for holistic insights. The results provide patterns and insights that answer many questions such as Which campaigns motivate customers to buy more or Which offers drive customer retention and referrals? or What combinations of campaigns convert leads to customers most effectively?

4. Predictive Analytics for Targeted Promotions

To acquire customers at a lower cost and to have a competitive edge, retails have to target customer promotions effectively. This means the retailers need to have an accurate 360-degree view of customer’s prospects. By combining various data such as customer purchase histories and profile information, as well as behavior on social media and other channels can help the retailer better understand the interests of its customers. These insights also help to precisely target their customers by placing relevant ads and special promotions. This way, the retailer is likely to get higher conversion rates at reduced customer acquisition cost.

5. Operational Analytics to increase efficiency

To gain a competitive edge and to drive business performance and returns, retailers must have an efficient supply chain and product distribution system. However, faster product life cycles and complex business processes make it harder to build such an efficient system. Retailers must find a way to optimize asset utilization, budgets, performances and service quality, and retail analytics can help a long way.

With the right retail analytics solutions, retailers can have valuable insights by analyzing data from various sources such as CRM, ERP, mainframe, geo-location, log, sensor, machine data, and public data. These insights provide information such as current trends, patterns, and outliers. It also helps to make correct decisions that drive performance, increase uptime, and reduce operational and capital expenditures.

Retail is a very customer-centric sector and retail data is the key to understanding customers. With retail analytics, retailers can study consumers’ shopping patterns to uncover trends and valuable insights that drive sales. From the supply chain to consumer demand, retail analytics is critical to creating effective marketing and operational decisions. Relying on analytics and hard data rather than guesswork enables retailers to make smarter decisions that lead to higher profits and provide better customer satisfaction.