Case Studies

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Case Studies

Marketing Mix Modeling & Optimization

Not only can you continuously improve year-over-year performance, but you can also adjust to combat a negative economy, minimize Cost-Per-Sale, maximize revenue, and set media ROI targets year-over-year, and much more.


Travel & Leisure

Client Need:

Establish a quantitatively grounded approach to media & tactic effectiveness measurement to enable management of feeder market ROI, maximize website traffic and reservations, and increase loyalty program participation.

Solution:

Marketing Mix Optimization & Reservations Forecasting Platform, Marketing Mix Manager® online reporting, optimization, and media planning support.

Results:

Coming out of its 2nd year in operation, our program has been central in generating significant successes:

  • All-media ROI UP 24% / Met Year-End All-Media ROI Target
  • Website traffic UP 39%
  • Loyalty Program UP 20%
  • Setting Annual Media ROI targets & measuring performance against target
  • Year-end reservation forecasts accurate to < 2%

MMMO_ROI (2)MMMO_ROI (1)

Auto Insurance

Client Need:

Quantify impact of a multi-media marketing mix on policy sales volumes in the property & casualty insurance industry. Media / Tactics included DRTV, Online, Direct Mail & Shared Mailers.

Solution:

Marketing Mix Optimization & Sales Forecasting Platform

Results:

Consumer Confidence is a strong leading indicator of consumer response. Negative impacts of declining consumer confidence can be partially mediated by effective and efficient media planning and strategy.

  • Optimizing the marketing mix with the same budget increased policy sales by 7% and decreased cost-per-sale (CPS) by 6%.
  • A decrease of 7% in budgets can maintain current sales volumes.
  • In a signal that media still works even in down economies, almost 1/3 (32%) of the policy sales at risk due to soft economic conditions were “won back” by media.
  • Accuracy of 3-month forecast outlook averaged 1.6% error per month.

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Retail

Client Need:

Quantify impact of a multi-media marketing mix on sales volumes, determine optimal budget allocations by medium, and understand implications for Cost-Per-Sales at varying overall ad budget levels.

Solution:

Marketing Mix Optimization & Sales Forecasting Platform

Results:

Overall, all medium and tactic (direct mail, online, in-store point-of-purchase, street teams, newspapers, and magazines) were dramatically underfunded.

  • Optimal allocation by medium: Optimal-Allocation-by-Medium
  • Additional analysis revealed that the optimum CPS would be generated at 3X current budget levels. Cost-Per-Sale-at-Varying-Spend-LEvels
  • Due to the low budget and the demonstrated effectiveness of the media / tactics, even 9X current budget levels would still generate a lower CPS than current budget levels.
  • Model forecasts quarterly sales with less than 3% error.

Call Center Service Quality Optimization

The customer experience during a service encounter is a fundamental aspect of your relationship with your customer and a key determinant of the value proposition.

Many times, the way in which a service issue is handled is more important than the occurrence of the issue in the first place.

Optimizing call center service quality to maximize the positive impact of a service encounter significantly increases customer loyalty and decreases churn.


Internet Service Provider

Client Need:

Optimize customer care service quality to maximize customer satisfaction with the service encounter in tech, billing, retention, and security transactions and thereby minimize customer churn.

Solution:

Quality to Marketing Management System (QTMMS) linking optimized service quality with customer satisfaction and retention results. Platform supported with optimization software & monthly quality-control reporting.

  • Internal quality metrics analyzed included: ASA, AHT, Service Level, Rep Attrition, Rep Training, Call Offered, Calls Handled, FTE’s, Cash Credit Per Call, Service Credit per Call, Cash Credit Per Save, Service Credit Per Save, 24-hr Saves Rate, 60 Day Saves Rate, 90 Day Saves Rate

Results:

QTMMS platform enabled significantly increased customer satisfaction:

  • Retention of 40k customers monthly
  • Generating $9.6 MM 12-month retained revenue per month ($115.2 MM annually)
  • 4-5% average bsolute churn forecasting accuracy.

In-Market Forecast Results

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2nd-in-market-validation-6-months-later

Customer Segmentation

Understand who your customers are, what they like and dislike, and how to communicate with them most effectively.

A meaningful customer segmentation is the first and most crucial step toward customizing communications across your customer base.

Customized messaging can increase response rates by as much as 25%.


Attitudinal Segmentation & Database Mapping Automotive

Client Need:

Client needed an actionable customer segmentation to customize direct response messaging to its customers and to guide creative development for mass media executions (proven to increase sales rates as much as 25%).

Solution:

Develop attitudinal segmentation based on client survey data. Develop discriminant function-based mapping model / mechanism to map (transfer) the segmentation beyond the survey sample to the company’s entire customer database based on 3rd party appended demographic data.

Results:

  • Segmentation produced four (4) actionable customer segments.
  • Mapping model generated segment flags for 100% of the 2.5 MM customers in the company’s database.

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Direct Response Target Modeling

Our direct response target models can help you significantly increase the performance of your online and offline direct response campaigns.

Coupled with our learning plan and continuous improvement processes, target modeling is a “must” component of effective direct response campaign management.


Target Modeling with 3rd-Party Data & Database Mapping Financial

Client Need:

Target new customers for financial services based on MRI syndicated survey data.

Solution:

Develop a discrete choice model predicting likelihood of customer opening the type of financial services accounts being marketed. A survey question measuring the desired behavior was used as the dependent variable. Survey demographics were recoded to mirror the values of 3rd party demographics which were used to map the model response probabilities to the client database.

Results:

Target model produced 8% response rate vs. 0.5% for a control group.

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Sales & Revenue Forecasting

Our forecasting performance is among the strongest in the industry.

These selected forecasting case studies demonstrate the forecasting accuracy of our marketing mix models across multiple industries based on weekly, monthly, and quarterly data.

Our forecasting system are ideal for year-over-year target setting and tracking YTD performance towards those targets.

Travel & Leisure

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Insurance

Actual-Sales-vs-Forecasted-Sales-insurance

Auto

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Retail

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Other Case Studies

Communications Company

Challenge

Quantify impact of a multi-media marketing mix on product sales of a high-end technology product launch.

Solution

MMMO Platform

Results

By analyzing historical product launches, we determined that 3 of the 4 media (online and offline) measured were historically under-funded; i.e. spending was below the threshold required to achieve critical mass and measurably impact revenue. The 4th media was over-funded; i.e. spending exceeded the economic optimum beyond which each additional dollar spent generated a diminishing return.

In order to maximize future product launches Polaris recommended re-allocating dollars from the 4th media to incrementally fund all other media. Specific allocations were determined based on the individual elasticities for each media as well as operational constraints unique to our client.

As a result of our analysis and subsequent optimization, products launched after the MMMO platform was established produced a 10% increase in sales for the same budget dollars and the platform is now in its second year of operation.


Travel Industry

Challenge

Quantify impact of a multi-media marketing mix on reservations.

Solution

MMMO Platform

Results

By analyzing historical media plans and reservations, we determined that 1 of the 6 media measured was historically under-funded; i.e. spending was below the threshold required to achieve critical mass and measurably impact revenue. Another was over-funded; i.e. spending exceeded the economic optimum beyond which each additional dollar spent generated a diminishing return. The other 4 were funded in excess of the critical mass threshold but at or under the economic optimum; however, in one case the contribution to number of reservations booked was minimal.

In order to maximize future product launches Polaris recommended eliminating two of the media measured and re-allocating dollars for the remaining 4 based on their individual elasticities.

By optimizing the marketing mix our client realized an 18% increase in reservations for the same budget dollars and the platform is now nearing the end of its first year of operation.


Automobile Manufacturer

Challenge

Quantify the impact and return of various media, a major sports sponsorship (World Cup), and consumer value perceptions (based on tracker survey results) on sales and revenue.

Solution

MMMO Platform

Results
  • Media (predominantly mass) drove 33% of ad sales and paid back $1.20 / $1.00 in a very low margin category.
  • Increasing weekly Gross Ratings Points from 50 to 70 increased sales by 28%.
  • Re-allocating 10% of the general market mass advertising dollars to high performing diversity markets decreased corporate cost-per-sale by 8%.
  • The World Cup sponsorship generated a 17% lift in sales during the promotional period.
  • The consumer value perceptions (based on quality / price survey data) generated 43% of total sales highlighting the significant contribution of consumer perception and valuation to the consumer purchase process.

Internet Service Provider

Challenge

Forecast customer churn rates and develop / measure intervention strategies

Solution

Customer Retention Management System – CRMS. Supported by volumetric forecasting platform with internal performance measures, customer service survey results, and brand loyalty results as inputs to forecast customer churn rates.

Results

CRMS tested twice in-market (six-months apart) after rollout. Approximately 1% forecast error over entire out-of-sample period (approximate average absolute weekly error = 5%). Platform supports client retention reporting. System enabled a 10% decrease in customer churn year-over-year.


Consumer Electronics Company

Challenge

Develop meaningful survey-based customer value segmentation approach to enable two-year value scoring of customer database and lead targeting.

Solution

Discrete Choice Modeling and Value Driven Segmentation

Results
  • Series of five discriminant function models accurately predict volume of purchase and 2-year value of prospects / leads across multiple products.
  • Models used to regularly score customer database and target prospects “in the market” for new products.
  • Profiles of five value segments (low value to high value) successfully leveraged for messaging in direct response media.

Communications Company

Challenge

Determine impact of seven-month major brand campaign (1,000% increase in average monthly brand spend) on the company’s value proposition (i.e., quality / price relationship from the customers’ perspective).

Solution

Quasi-Experimental Time Series Intervention and Decomposition Analysis

Results

Major brand campaign drives an 8% increase in perceived value of the company’s products and services (based on tracker survey) and generated a 2.8% increase in market share.


Automobile Manufacturer

Challenge

Determine impact of basic and advanced training on compensable customer satisfaction and loyalty survey results at the store / unit level.

Solution

Pooled time-series linkage of training to a Customer Loyalty Index (CLI) at the store / unit level.

Results

Basic training significantly improves the customer experience resulting in higher CLI’s at the store / unit level. Each base training module completed increases the CLI by 0.11%. Advanced training had no impact on customer loyalty, due predominantly to lack of structure of the advanced modules, leading to a reorganization of the advanced curriculum.


Call Center – Customer

Challenge

Accurately represent the customer experience from service contact through to completion and develop metrics appropriate for the administration of employee variable compensation programs.

Solution

Customer Satisfaction Indices (CSI’s) based on structural equations and indexing techniques supported with weekly reporting.

Results

Final CSI models reflecting the customer experience from report to completion immediately rolled into client compensation programs and are in 6th year of use. CSI’s track syndicated research and accurately reflect industry positioning throughout the year.


Call Center – Employee

Challenge

Establish a metric to measure and manage employee satisfaction, commitment, and retention suitable as a compensation element in leadership variable compensation programs.

Solution

Employee Satisfaction Index (ESI) based on structural equations and indexing techniques supported with weekly reporting.

Results

Final ESI models reflect 13 organizational dimensions critical to the satisfaction, success, and retention of employees (e.g., job equity, role clarity, pay, culture, tools, leadership, communication, etc.). Results immediately rolled into client’s leadership variable compensation programs and are in 2nd year of use.


Call Center – Employee

Challenge

Increase employee retention throughout a call-center organization through effective management of key drivers of attrition.

Solution

Employee Retention Management System (ERMS) linking measures such as employee satisfaction, center performance, pay / incentives, leadership, etc., to employee attrition and optimizing performance to minimize attrition.

Results

Employee attrition decreased 20% in test centers preceding corporate rollout.


Call Center – Employee

Challenge

Quantify the impact of employee retention on customer retention to evaluate ROI of employee retention programs and initiatives.

Solution

Pooled time-series linkage of employee satisfaction metrics, attrition, and customer satisfaction results to customer retention at the service center level.

Results

10% decrease in employee attrition results and more than 20k retained customers annually.

List of Services

Econometric Modeling

  • Marketing Mix Modeling & Optimization
  • Multi-Touch Attribution
  • Volumetric & Demand Forecasting
  • Brand Equity Metrics & Optimization
  • Linkage to Internal Service Quality Levels
  • Retention Forecasting & Optimization

Market Research

  • Customer Survey Development, Fielding, Analysis & Reporting
  • Syndicated Research Forecasts
  • Syndicated Research Mapping to Client Databases
  • Feasibility Studies

Discrete Choice Models & Segmentation

  • Buyer, Clone & Response Models
  • Customer Churn Models
  • Customer Upsell & Migration Models
  • Customer Lifetime Value & Optimization Models
  • Multi-Dimensional Customer & Messaging Segmentation
  • Multi-Phase / Product Communication Stream Management Models

Measurement, Tracking & Reporting

  • Experimental Test Design
  • Pre-Promotion Forecasts
  • Post-Promotion Sales & ROI Reporting
  • Productionalized Reporting