How a Retail Brand Revolutionized Customer Experience with Decision Intelligence Platform CX Sense

Blog / How a Retail Brand Revolutionized Customer Experience with Decision Intelligence Platform CX Sense

Are you facing the puzzle of aligning customer insights in retail? In a market driven by digital and physical interactions, piecing together a complete customer profile is challenging. 

Retailers confront distinct issues:

• Data Silos: Vital customer data is often split across systems – CRM, ERP, and POS.
• Disjointed Customer Experiences: Bridging the gap between online browsing and in-store purchases is complex.
• Ineffective Personalization: Fragmented data makes tailoring customer experiences difficult.

In this article, we delve into a case study where a retail company successfully navigated these challenges. We’ll explore their journey towards integrating data sources and enhancing customer engagement.

A Retail Brand Like None Other

As a leading player in the retail industry, this company specializes in providing a wide range of products to meet the diverse needs of its customers. Their extensive product catalog spans categories such as electronics, fashion, home goods, and more. They operate brick-and-mortar stores and a robust online platform, making shopping accessible and convenient for their customer base.

Customer Frustrations: Challenges Impacting Shopping Experiences

⚠️ Fragmented Data Led to Generic Recommendations: Customers expected personalized offers but often received generic suggestions due to fragmented data, leaving them disappointed.

⚠️ Lengthy Processes Resulted in Abandoned Carts: Lengthy and complex checkout procedures frustrated customers, leading to abandoned shopping carts.

⚠️ Out-of-Stock Items Caused Customer Disappointment: Customers faced disappointment when their desired products were out of stock, impacting their shopping experience.

⚠️ Supply Chain Delays Left Customers Frustrated: Delays in product delivery due to poor supply chain visibility frustrated customers and affected their overall satisfaction.

⚠️ Difficulty Finding Products Diminished In-Store Experiences : Customers encountered difficulties navigating the store and finding products due to inadequate signage and layout, leading to frustrating in-store experiences.

⚠️ Customer Expectations Misaligned with Product Availability: Customers were disappointed when they couldn’t find products promoted in advertisements or displays, showing a deep divide between merchandising strategies and product availability.

A Quick Look at the Data Landscape

• CRM Data:  Salesforce held valuable customer data, including contact information and interaction history. 
• ERP Data: The ERPs managed various aspects of the retail process, such as inventory, demand, and financial data. SAP APO provided insights into demand data, while SAP S4 HANA handled inventory data.
• Retail POS Systems Data: Point-of-sale systems collected transaction data, shedding light on customer purchases and sales trends.

However, despite the abundance of data, these systems operated in isolation, leading to several challenges:

• Limited Supply Chain Visibility: The supply chain team had limited visibility into actual inventory conditions.
• Marketing Isolation: The marketing department lacked real-time insights into supply chain conditions, hindering their ability to align promotions with product availability.
• Sales Disconnect: Sales teams at retail stores were unaware of inventory levels and couldn’t provide accurate information to customers, affecting customer satisfaction.

How Pluto7 Approached This Challenge

🔨  Establishing a Robust Data Foundation 

We began by establishing a robust data foundation, a vital step for advanced analytics with AI and ML. Our team swiftly integrated SAP and Salesforce data into Google BigQuery, leveraging Google Cloud Cortex. Remarkably, what traditionally takes months, we accomplished in just one week.

⚙️ Predictive Analytics with CX Sense 

Once the data foundation was established, we deployed CX Sense, our decision intelligence platform, on top of their existing ERP. This enabled us to do things like segment customers effectively, predict their preferences, optimize inventory in real-time, and provide personalized recommendations. For instance, we could predict which products a customer might be interested in based on their browsing history and offer real-time discounts at checkout.

🏭  Event-Driven Automation 

Up next on our agenda was near real-time inventory visibility. We initiated the process with Event-Driven Automation, which automated replenishment requests triggered by customer purchases. For instance, when a customer selects a product from a store shelf, this action automatically generates a request for restocking that specific item, ensuring it’s available for the next customer.

Retail Analytics Behind the Scenes 

Parallel to the customer experience transformation, we embarked on redefining inventory and merchandising management for store staff. Our primary focus was on harnessing real-time insights to ensure store layouts and strategies aligned seamlessly with consumer trends. These included:

• Enhancing inventory visibility with real-time shelf stock displays and camera tracking.
• Delivering cutting-edge analytics through a custom-built sales activity dashboard.
• Capturing the movement of products and customers around the store through RFID video heatmaps.
• Infusing trend data and machine learning into an intelligent planogram for dynamic store reorganization.

The Outcome: Retail Decisions Based on Data, Not Hunches

Through this transformation, the customer was able to achieve:

Personalized Ads: They served personalized ads by seamlessly blending Google Adtech, social media, and sales data, resulting in more engaging and effective advertising campaigns.

Accurate Demand Forecasting: By combining external demand signals, they achieved precise demand forecasting, ensuring that products were readily available when customers needed them.

Enhanced Customer Insights: The integration of sales data and customer behavior allowed them to sense customer needs and preferences more accurately, leading to tailored experiences at every level.

Effective Inventory Decisions: Real-time data empowered them to make effective inventory decisions, reducing instances of out-of-stock items and ensuring customers found what they were looking for.

Improved Campaign Performance: The ability to analyze customer data led to more successful marketing campaigns, boosting customer engagement and sales.

Revolutionize Retail with Your Salesforce and ERP Data: Uncover Hidden Customer Insights

In the fast-transforming world of retail, data is your most valuable asset. Don’t let it go untapped. Join us on a transformative journey into the heart of your Salesforce and ERP data. Discover hidden customer insights, streamline operations, and boost your competitive edge. Request a demo today and revolutionize your retail business. Your future success starts with the data you already have. 

Take that first step now.