- Revenue Diagnostic TM
A carpet manufacturer partnered with Revenue Analytics to reassess its current pricing practices in a slow economy. Together they conducted interviews and a data deep dive to identify areas of opportunity in organization, systems and tools, with over $95M in potential incremental revenue opportunity.
- Promotions & Incentives
An automotive manufacturer sought to improve the effectiveness of its promotional and discounting practices. With the principals of Revenue Analytics, customer response to incentives was measured and optimal recommendations were made based on market segment and incentive type, resulting in a $800M gain in revenues.
The process of designing and building products, creating demand for them and getting them into the hands of customers is one of the most complex and capital-intensive endeavors in the business world.
Characteristically, productivity gains in manufacturing have come from cost reductions. Nevertheless, certain industry-leading firms have learned to apply sophisticated Pricing and Revenue Management analytics to the demand side of the profit equation in order to help temper cyclical patterns and outperform competitors.
Revenue Analytics has teamed with manufacturing clients in the development of these revolutionary approaches which employ a granular analysis at a deeper level to uncover opportunities for market penetration or price premiums.
These opportunities are often obscured by the complexities of an environment which may include tens of thousands of SKUs and must account for factors such as channel conflict, cross-product cannibalization, competitive actions and product lifecycle.
Our clients have recorded hundreds of millions of dollars in increased profit by identifying cause and effect for customer behavior and allocating incentive dollars to their most profitable use so that volume can be increased with less promotional spending.
Most companies would agree with the old adage, “50% of promotional spending is wasted… but we don’t know which 50%”. We help our clients utilize statistical modeling to measure the effectiveness of discounts at the most granular level, and:
- Identify ineffective discount and incentive spend
- Recognize the optimal discount amount and incentives type (e.g., payment terms or volume discount)
- Predict response to incentives by product, channel and customer segment
- Understand impact of discount and incentive decisions on inventory turns, production scheduling and supply chain
- Reduce the impact of cannibalization and channel migration
Many manufacturers are moving from analyzing what their customers currently purchase to what their customers could be purchasing by using sophisticated customer profiling techniques. We collaborate with clients to devise the business processes, tools, advanced analytics and models to:
- Understand buying patterns and trends at a customer segment and channel level
- Compare individual customer behavior to its segment to identify “at risk” customers, opportunities to sell higher volumes or additional product lines, and higher costs to serve
- Develop reports and alerts to facilitate field sales discussions at the individual customer level
The concept of integrating end customer demand with production and supply chain decisions improves coordination, operational efficiencies and total net margins. To truly link all decisions from “seed to shelf” is a complex process that requires a well-formulated plan and phased approach. We partner with clients to:
- Design the transformational plan to achieve integrated customer demand and supply optimization
- Design and deploy a knowledge platform to synchronize decisions across entire supply / demand continuum
- Develop comprehensive change management frameworks to ensure adoption of decision support recommendations and consistent execution across functional groups
- Integrate scenario planning capability to evaluate strategic alternatives and diagnose root cause of suboptimal decisions between pricing, promotions, distribution, production and procurement
For many manufacturers, product lifecycle is a significant driver of demand and must be accounted for in determining optimal pricing and discounting strategies. We partner with clients to:
- Create sophisticated measurements and metrics to determine individual SKU lifecycle stages
- Develop pricing, discounting and inventory strategies to maximize revenues throughout the entire product lifecycle
- Design business processes for proxying new product lifecycles
For manufacturers with thousands of SKUs, predicting how customers will respond to price points, discounts, promotions or incentives is educated guesswork. By conducting statistical analysis at a granular level, market response models can be developed for predicting customers’ price responsiveness. Our analytical approach leverages historic sales data, product data, competitive data, customer data and other available data sources to:
- Predict how customers will respond to various price points and discount levels, and identify ways to incorporate these models into decision processes
- Leverage market response models to identify SKU level opportunities for price increases or tactical price reductions to stimulate demand
- Incorporate competitive prices and potential competitive price changes into the market response model
B2B pricing is a unique challenge; each pricing decision has a significant impact on the bottom line. Ultimate success depends on the ability to develop both a sophisticated approach to modeling and clear, actionable recommendations for the sales force. We help clients:
- Leverage their existing customer data to model customer behavior and predict win probability and volume based on a particular bid
- Incorporate price sensitivity, competitive offers and forecasted demand-to-come into a recommended optimal price
- Collaborate with sales force to understand key customer drivers, value proposition and current pricing practices to ensure adoption of optimal price recommendations
Although traditional segmentation approaches are useful for mass marketing, they often do not help describe customer behavior and consequently are not optimal for pricing decisions. We work with our clients to:
- Understand strategic, share and profitability objectives and identify key customer attributes
- Perform clustering, CHAID and regression analysis to identify commonly held traits and behavior patterns among customer groups
- Develop strategies, business processes and methodologies for optimizing pricing, discounting and inventory allocation decisions across customer segments