Retail Analytics

Our solutions include application modules designed to support many areas in the complex world of retail management.  The key components of the application are:

Product and Price Analytics

• Product Selection
• Price Elasticity
• Product Co-movement
• Product Cannibalization

Sales and Marketing Solutions

• Customer Acquisition
• Relationship Deepening with Existing Customers including Recommendation Engines
• Customer Retention
• Targeting for Special Offers
• Optimization of Product and Promotion
• Sales Management

Inventory Management Solutions

• Self-learning inventory management
• Purchasing management

A graphical representation of the application is below, followed by a high level overview of each component.

click to enlarge

Product and Price Analytics

Product Selection – Solutions to make product and sale item decisions at multiple levels including store, region, state, and others.

• Forecast item and category movement based on the behavior of previous sales/events
• Recommend the optimal mix of products to stock at store level
• Decide product mix for sales events – by managing drivers such as over or under stock of inventory or margin expectations.  Our models can help the companies understand the impact of the selected product mix on operations, inventory management and profit.

Price Elasticity – These solutions include a group of powerful of tools to support pricing decisions and help managers balance profit and unit volume

• Analytical tools to guide decision making when balancing the need to move the most units possible with the need to also make as much profit as possible.
• Price optimization tools designed to calculate the perfect price to balance unit sales and profit
• Discounting optimization – It’s often the case that for some products, the discounts are unnecessarily deep, or alternatively not deep enough, to obtain the desired product movement and revenue.  Our solution will help managers determine the best discount that strikes a balance between product movement and margin retention.

Product Co-movement – Solutions designed to assess and management co-movement behavior.

• Analytical reports that tell you which products will co-move during the normal business and sales event.  These tools support store level decision for instance, a store can display items that co-move close together in the store or put items that co-move on a slight discount to drive more volume.
• With this information, companies can work with vendors whose products co-move to help sponsor events.

Product Cannibalization – When the products go on sale, it’s possible that customers buy those products and substitute the sale product for another product they may have purchased.   When this happens, companies can drive volume but end up with lower profits

• Tools to forecast the results of putting items on sale on the volume of like non-sale items and the impact to overall profit
• Improved  decision making on which products to put on sale
• Tools to analyze the cost of cannibalization

Sales and Marketing Solutions

New Customer Acquisition – Solutions to help retail companies acquire new customers including:

• Behavioral segmentation to determine the actual customer demand segments
• Segment analysis for insight into buying behavior for specific customer groups
• Guidance to build targeted marketing campaigns for specific segments and the most appropriate way to deliver the messaging including direct mail, email, print, TV and Internet marketing for each segment.

Relationship Deepening with Existing Customers – Acquiring customers is expensive and time consuming and often companies don’t have the tools to maintain and deepen their customer relationships.  These solutions help companies develop existing customer loyalty.

• Segmentation and prediction tools to determine next likely purchase for groups of customers
• Customer behavior analysis, including nearest neighbor models (similar to the Amazon recommendation engine)  to predict the next product purchase
• Sophisticated loyalty program management solutions to build brand loyalty and deepen relationships.

Customer Retention – Even with best efforts, there are customers who will reduce their spend and select competitor offerings.  These tools are designed to anticipate these issues and proactively manage retention.

• Solutions to anticipate customers who will be returning their products and/or not completing their contracts.
• Predictive tools to help companies understand which customers are most at risk of reducing or stopping their purchases

Targeting for Special Offers – When retailers have manufacturer driven special offers, it’s difficult for them to know which customers are most likely to accept the offer.  These tools are designed to help retailers do the following:

• Identify best customers to target with offers driven by manufacturers providing discounted pricing
• Identify manufactures who are the best candidates for successful special offer campaigns.

Marketing Optimization – When deciding how to allocate marketing dollars, managers tools to remove the complexity caused by trying to understand the performance of historical campaigns in changing market conditions.

• Optimization programs designed to suggest the best possible mix of marketing programs based on user driven criteria including profit maximization and unit movement.
• Flexibility to set minimum and maximum spend in categories and optimize the results
• Simulation tools to predict outcomes driven by all categories of marketing spend.

Sales Management – These solutions are designed to help retail companies manage their sales associates.

• Very accurate sales forecasting at employee, store, region and other levels which match the company’s organizational structure.
• Multi-dimensional segmentation to allow companies to focus on key salespeople who have the propensity to improve or who are at risk for declines in performance.
• Tools for salespeople to retain customer information and develop a personal relationship with their customers.

Inventory Management

Inventory Management Solutions – Managing inventory based on pattern recognition and using self-learning algorithms allows companies to optimize their inventory and keep the lowest amount of working capital allocated to inventory possible while fulfilling customer demand.

• Self-learning inventory management tools that automatically review the behavior of individual items and set appropriate order amounts
• Inventory segmentation tools that use five dimensions to create a manageable group of inventory categories where purchasing rules can be applied.  The dimensions are: item movement, variance in item movement, minimum order quantity, cost and lead time.  By segmenting in this way, the true nature of inventory movement can be managed and predicted.
• Purchasing management tools to create suggested inventory order quantities and manage vendor relationships.

Conclusion

The retail market is experiencing unprecedented change and a very tough consumer environment.  Fortuitously, retailers are collecting and storing more data than at any time in history.

Those companies that successfully leverage the intelligence hidden in their data will make better pricing and product decisions and also optimize sales and marketing activities and inventory acquisition and allocation.  The result will be that they will outperform their peers in the areas of revenue growth, costs management and delivering shareholder value.

Many books have been published about leveraging data including “Super Crunchers” and “Competing on Analytics.” We believe that by working together we can offer the market what these publications advocate (and more!) by creating the world’s first Quantitatively Driven Companies ™.  In essence, we’ll embed solutions into business processes and drive higher sales, support better planning and optimize operations.