Proven Leading Practices for Retail Industry Operations
Retail Best Practices Guide
Learn MoreUse Interaction Analysis and Quantitative Metrics to Staff Departments and Improve Customer Experience
Best Practice (Good)
Staff departments based on productivity, traffic and conversion rates on a department-level basis. Ensure that selective staff scheduling is based on data from interaction analysis (Customer Satisfaction Rate, Customer Order Fill Rate, Percentage of Order Pricing Failures, etc.) and other quantitative metrics (staffing to traffic and traffic type and/or staffing departments based on more micro trends within the store) layered onto fundamental Workforce Management Systems. This not only allows managers to staff their departments in a more accurate fashion, but it also ensures that staff scheduling is focused on promoting high productivity and optimal customer satisfaction.
Typical Practice (Bad)
Staff departments based on service requirements and both historical traffic and transactional data integrated into the company's Workforce Management System. This allows managers to accurately staff their departments in such a way as to ensure that all customers can be taken care of in a timely manner.
Benefits:
Service requirements and/or historical traffic and transactional data, while useful, isn't all that's necessary when determining how a retail company's departments are staffed. By going deeper and focusing on a set number of focused and clearly defined metrics (e.g., metrics that focus on productivity, traffic and conversion rates) on a department-level basis, and ensuring that selective staff scheduling is based on data from interaction analysis and other quantitative metrics (Total Sales by Aisle, Units per Transaction, Visit to Buy Ratio, Stocking Cycle Time, Customer Order Fill Rate, etc.) layered onto fundamental Workforce Management Systems, retail companies become better able to accurately staff departments with high performing and customer focused personnel. By using such focused and clearly defined metrics, retail companies are also able to improve the productivity and focus of their employees and company itself. Furthermore, by measuring various quantitative metrics and staffing departments to traffic and traffic type and/or staffing departments based on more micro trends within the store, companies are able to improve their ability to target the right customers with the right products at the right times, thus improving their satisfaction and overall company revenue.
Use Individual Customer Preferences and Personalization to Improve Promotional Offer Targeting
Best Practice (Good)
Use individual customer preferences to deliver targeted promotional offers (relevant, personalized and contextual offers) in a manner the current or potential customer prefers (mail, email, mobile, etc.) to improve customer acquisition and retention. Supplement customer resource management (CRM) systems with integrated marketing software that tracks online customer behaviors to narrow customer segmentation and create highly relevant promotional offers based on demographics, psychographics and behaviors.
Typical Practice (Bad)
Deliver direct mail promotional offerings (segmented by loyalty programs, spending levels and/or special lists) through batch and blast offers to reach as large a number of current and potential customers as possible. While many promotional content packages may be overlooked, batch releases or email blasts are the best way to entice a large number of people to visit the retailer (includes the brick-and-mortar store and online stores).
Benefits:
Delivering direct mail promotional offers through batch and blast offers often produces poor conversions while enticing current and potential customers to unsubscribe or blacklist the influx of irrelevant promotions. Using individual customer preferences to deliver targeted promotional offers (relevant, personalized and contextual offers) in a manner the current or potential customer prefers (mail, email, mobile, etc.), on the other hand, improves customer acquisition and retention by not only demonstrating that the company actually cares about the customer's interests, but also by offering customers what they want. To this end, companies are able to use historical data such as point of sale (POS) information, e-commerce transactions, loyalty programs, contact center notations and supply chain or fulfillment system information to gather the information necessary to personalize promotional offers. Furthermore, supplementing customer resource management (CRM) systems with integrated marketing software that tracks online customer behaviors further narrows customer segmentation to help create highly relevant promotional offers based on demographics, psychographics and behaviors. Effective customer segmentation may be based on customer demographics, customer behavioral patterns, customer preferences for known brands, etc.