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Luxury auto manufacturer uses analytics to allocate operational resources.

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A leading luxury automobile manufacturer announces an exciting redesign for its flagship vehicle. The news generates a large volume of inquiries. However, due to the vehicle’s significant price point, only a relatively small number of vehicles are expected to be sold. As a result, local dealerships find it difficult to allocate resources appropriately.


Three key objectives are set:

1. Define the specific customer for the vehicle.
Only a very specific customer will be interested in this redesigned vehicle and capable of meeting the steep luxury price tag. The analytics team searches existing sales and marketing data to create an in-depth profile of this customer to ensure that sales efforts are not wasted on unqualified customers.

2. Optimize resource allocation.
To ensure that dealerships can properly allocate resources – financial and manpower – deep sales predictors are identified in order to optimize return on investment of resources at both the corporate and dealership levels.

3. Reduce operational costs.
The auto manufacturer also wants to reduce operational costs associated with the per-unit sales cost of each vehicle. An operational study that compares costs to the validity of each market segment is generated to assist with this goal.


For this project, the primary service required is:

Analytics Services (link to more info below)

Deep analysis of the company’s existing customer data gives a thorough understanding of the current customer base and what motivates women to purchase the manufacturer’s vehicle. Purchasing data tells what the existing consumers are likely to buy in the future.

But the true value to the retailer comes through the “prescriptive” aspect of the Analytics Services. The analytics team predicts future female consumer behavior, identifies emerging trends, and develops detailed personas for the retailer’s female consumer of the future. This information is synthesized and specific suggested courses of action are developed to address likely market shifts.

With these valuable insights generated through analytics, the company also requires:

Advisory Services (link to more info below)

Advisory Services works directly with company leadership and key personnel to apply the insights gained through analytics and maximize operations efforts. The Advisory Services team provides impetus and counsel as the retailer implements the prescribed courses of action. The retailer gains immediate expert advice, the ability to react at a moment’s notice, and flexibility to adapt strategies to best meet the consumers’ expectations.

Research Services (link to more info below)

Information is gathered from target female consumers regarding their feelings about the new product line and what emotional drivers will compel them to choose the retailer’s brand over another (see METHODOLOGIES listed below).


Three specific analytic/research methodologies are required:

  • Data Acquisition and Compilation
    Past customer inquiry and sales data is extracted as it pertains to previous versions of the vehicle. Customer attributes are audited for accuracy, completeness, and robustness. Intercorrelation among data points is investigated, and outliers are eliminated as appropriate. Ultimately, target customer profiles are created.
  • Survey Research
    Prior and prospective customers are surveyed to obtain demographic and socioeconomic information as well as additional insights into local buying patterns and behaviors including: level of interest, brand loyalty, primary sales drivers, and timing of purchases.
  • Segmentation Analysis
    High-level correlation analysis is performed to identify those characteristics most predictive of sales. Due to the scarcity of demographic attributes, segmentation is chosen as the most appropriate statistical technique. A CHAID analysis is performed to create a decision tree, whereby various nodes represent populations with significantly different likelihoods of the inquiry being converted to a sale. Powerful statistical methods are applied to ensure the final segmentation scheme is optimized with regard to performance and robustness. Each segment is rated and ranked based on likelihood to purchase.
  • Inquiry Segmentation and Implementation
    The final segmentation scheme is implemented into the company’s operational infrastructure. As inquiries are received, customer attributes are identified, and each prospect is placed accordingly into the proper segment. Based on the segment each prospect is placed into, operational strategy is shifted and a different level of resources is allocated toward serving that prospect based on their likelihood to purchase. Useful reporting metrics are developed and monitored to measure the effectiveness of the segmentation scheme and adjustments are made as sales numbers are recorded.


(Due to the confidential nature of research project, and client agreements in force, specific results cannot be shared. Outcomes have been synthesized based on an amalgam of results from similar projects.)

Not only does this turn out to be an excellent exercise in how to sell this particular vehicle, but in how to sell all the company’s vehicles in general. From the top down, the company’s employees learn the process of segmentation, and how it can be used to qualify and prioritize resources when dealing with prospects.

Specifically, for the redesigned vehicle, this new approach to operational strategy achieves the desired objectives of optimizing resources and reducing operational costs. The few vehicles they do have sell briskly, even at the lofty price, and the company notices residual consequences of the project – a dramatic rise in all sales conversion rates, higher staff retention rates, and improved inventory forecasting methodologies – all of which work in concert to further operational efficiency and increase margin.

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