Industries 

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 promotions at the most granular level, and:

• Identify ineffective promotional spend
• Recognize the optimal promotional amount and promotional vehicle (e.g. free services for 3 months or 12 month discount)
• Predict response to promotions and incentives by product, market, channel and customer segment
• Determine optimal promotional roll-off price to minimize churn and maximize revenues
• Understand impact of promotion decisions on migration, cannibalization and cross-product interactions

Many companies in the communications industry 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 level (e.g., time shifting and cord-cutting)
• Compare individual customer behavior to its segment to identify opportunities to upsell or sell additional products
• Develop reports and alerts to facilitate call center discussions at the individual customer level

For the vast majority of companies, 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 these behaviors. Our analytical approach is to leverage 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 product 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
• Identify areas to stimulate upgrade behavior while minimizing downgrade and churn

Product value varies depending on customer needs, perception of service quality and ability to differentiate product offerings. By using detailed transactional level analysis, bundle optimization allows our clients to:

• Package a variety of service offerings together to improve take rate and revenues
  
• Identify optimal price points to minimize churn and maximize upsell
  
• Manage cross-product effects such as cannibalization and migration

In our experience working with communications clients, we have found that the best pricing strategies are well-defined, communicated throughout the organization and actionable. Developing the right pricing strategy requires combining strategic objectives with granular data analysis. We partner with clients to:

• Educate stakeholders about potential pricing strategies that fit their current operating model and strategic objectives
  
• Perform detailed analysis to determine value proposition vis a vis competition at a customer segment level
  
• Compare value proposition analysis to potential pricing strategies to determine ideal strategy by segment
  
• Ensure a rational price structure across channels and substitutable or complementary products
  
• Create change management plan to communicate pricing strategy throughout the organization

With hundreds or thousands of offerings and the diverse preferences of individual consumers, companies in the communications industry struggle to determine rates that maximize contribution. Understanding rate responsiveness by micro-market segment and cross-product interactions are keys to improving rate increase decisions and ensuring profitability in this industry. We partner with clients to design custom rate increase optimization models and processes that:

• Incorporate price sensitivity and current competitive offers by market
  
• Provide clear, actionable rate increase recommendations for end users
  
• Allow a transparent view into key customer behavior drivers behind recommendations, rather than a "black box" solution
  
• Incorporate scenario planning capabilities that allow for "what-if" testing based on parameter changes
  
• Include a comprehensive change management process to identify challenges and constraints, generate visibility, build consensus and lay a foundation for success

Although traditional segmentation approaches are useful for mass marketing, they often do not help describe customer behavior and consequently are not optimal for rate and promotions 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 rate and promotion decisions across customer segments