Product Portfolio Optimization Research

Product Portfolio Optimization Research

The main goal of product portfolio optimization research is to support business decisions to maximize the reach, revenues, and profits of a company’s product line(s) by selecting the right product combination.

Why You Should Do It

This type of research provides a solid foundation for decision making when companies want to:

• Add new products or product upgrades/changes without cannibalization.
• Discontinue a product.
• Expand the product portfolio to reach new market segments.
• Reduce product portfolio by consolidating overlapping products.

The Approach

Product portfolio optimization research is based on quantitative research with the help of survey methodology.

The most common approaches used for this type of research are TURF (Total Unduplicated Reach and Frequency) and conjoint analysis. However, we can use different research designs depending on the product complexity and research objectives. See Analytical Plan below.

Target Audience Recruitment

Relevant Insights can recruit B2C and B2B qualified participants through our sample provider partners for qualitative and quantitative research.

We determine the sample parameters from discussions with your team and assist with developing screeners. We also manage participant incentives.

Implementation

In direct collaboration with the client team, Relevant Insights will:

1. Recommend the data collection mode based on sample parameters and the industry in which your organization operates. Surveys can be conducted online or with a hybrid approach (online, phone, in-person).
2. Develop questions and metrics to support an analytical plan that meets the project’s business and research objectives.
3. Discuss recommendations for sample size and sample sources. Sample size requirements will depend on the product category, target audience and incidence rates, among other factors.
4. Program, test and host the survey. In addition to testing the programmed survey for errors before its launch, the survey will be deployed to a small sample to detect any potential issues with actual participants before its distribution to a large sample.
5. Monitor the field and provide daily reports on its progress and any issues that may arise.

Analytical Plan

More often than not, product portfolio optimization research uses trade-off approaches from the conjoint analysis family to tease out the optimal product line configurations.

The most common conjoint analysis approaches are:

• Choice-Based Conjoint Analysis (CBC) – Multiple product configurations that can make a line are presented simultaneously.
• Adaptive Choice-Based Conjoint Analysis (ACBC) – Preferred product configurations are discovered with a set of exercises aimed at identifying which attributes are relevant and which rules are used by the intended target audience to make choices.
• Menu-Based Choice Analysis (MBC) – Preferred product configurations and lines are estimated from build-your-own product scenarios.
• TURF analysis (Total Unduplicated Reach and Frequency) – This is a technique initially used in media research to understand media reach. However, it has been extensively used in product research to design the size of product portfolios with product combinations to reach as many potential buyers as possible.

The study design selection will depend on study objectives, product complexity, creative materials available for testing, time and budget constraints.

The metrics obtained will depend on the selected study design and may include measurements of:

• Most preferred product configuration.
• Product feature preferences.
• Optimal product line configuration.
• Impact on cannibalization.
• Reach and frequency by product line size (TURF).

Reporting

Relevant Insights can provide different levels of reporting based on budget and time constraints including:

• Raw data only.
• Product optimization simulators.
• Cross-tabulated tables by key variables.
• Short summary report with key findings.
• A full detailed report with analysis, charts, tables, quotes, and graphics in an appealing format.

Typical Project Duration

Six to eight weeks.

Factors that can affect project duration include:

• The incidence rate of the target sample: The lower the incidence rate, the longer we need to stay in the field to gather the required data
• Client team responsiveness: A delayed response to requests for feedback at different steps of the project will stall a project and affect the delivery date

Investment

The cost will vary depending on:

• Data collection method (online or hybrid).
• The analytical plan selected.
• Sample specifications and sample size.
• Reporting requirements.