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Solutions Range optimisation

Product Range Optimisation

Most consumer goods companies will need to optimise their product range at some point in their product’s life cycle. Many factors prompt product range optimisation, including competing SKU launches or the need to replace old SKUs with new ones. Adjusting your product range requires careful consideration to ensure that you make the best decision for your company. Past sales data, as well as consumer research, are both vital in making a truly informed decision.

Conjoint.ly offers both automated tools and custom research services for product range optimisation, using our two main methods — TURF analysis and preference share simulations. These methods are employed through our MaxDiff and Conjoint analysis tools, respectively.

Conjoint analysis and Maxdiff can help you:

  • Take into account the trade-offs that people make between products, while including important factors, such as competing products and their price ranges,
  • Build an optimised portfolio of product variants that ensure the reach of the maximum number of consumers,
  • Create simulations of estimated projected volume, revenue, and gross margin,
  • Reduce costs and complexity through a simplified product range,
  • Minimalise market share cannibalisation between products within your product range.
Solutions Range optimisation

Product Range Optimisation

Most consumer goods companies will need to optimise their product range at some point in their product’s life cycle. Many factors prompt product range optimisation, including competing SKU launches or the need to replace old SKUs with new ones. Adjusting your product range requires careful consideration to ensure that you make the best decision for your company. Past sales data, as well as consumer research, are both vital in making a truly informed decision.

Conjoint.ly offers both automated tools and custom research services for product range optimisation, using our two main methods — TURF analysis and preference share simulations. These methods are employed through our MaxDiff and Conjoint analysis tools, respectively.

Conjoint analysis and Maxdiff can help you:

  • Take into account the trade-offs that people make between products, while including important factors, such as competing products and their price ranges,
  • Build an optimised portfolio of product variants that ensure the reach of the maximum number of consumers,
  • Create simulations of estimated projected volume, revenue, and gross margin,
  • Reduce costs and complexity through a simplified product range,
  • Minimalise market share cannibalisation between products within your product range.

Why is product range optimisation so important for your company?

Having an optimised product range allows you to maximise your customer appeal, by developing and marketing products that drive a larger share of the market or activate more customers. The product range will be optimised to satisfy market needs while reducing costs involved and cannibalisation between SKUs.

Main benefits of optimised portfolio:

  • Greater product reach with best product combinations
  • Reduced costs and complexity through simplified range
  • Test market potential or decide number of SKUs
  • Minimised cannibalisation for NPDs
  • Increased revenues with efficient category performance
Product range optimisation importance

Optimising your product’s market reach

When creating your product range, it is important to ensure that it will appeal to the greatest number of consumers. This is not simply choosing the products that each have a high individual reach, but instead finding a portfolio of products that will complement each other in a way to maximise the total reach of the portfolio.

Which product combinations will maximise your reach to the most customers? When there are issues such as limited shelf space, communication space and other budget constraints, it is essential to launch the best combinations to reach the largest number of consumers. It is particularly important for NPDs, as they are yet to develop their customer base.

It is vital to understand which products complement each other best, to reach the maximum market potential. This can be achieved using choice based questions, as it will prevent you from launching similar products for the same group of people and missing out on activating more customers who have a strong preference on other products given the same budget.

Choosing product combinations

Test market potential or decide number of SKUs

When expanding into a new market/sub-market, it is important to know the market potential for your product portfolio. To meet your objective within this category, you can decide the number of products and which of their features will optimise your portfolio. For example, your portfolio may need to cover both a variety of flavours and different sizes to maximise your brand’s market penetration.

It is crucial to keep the number of SKUs in your range efficient, due to the diminishing returns from increased costs. The costs for launching each new SKU include: development, producing, marketing, operating and shelf space.

The incremental potential market reach for every additional SKU with the best combinations (TURF ladder) will show you how many people can be reached by including an additional SKU, as well as the change in revenue. This can help you decide the optimal number of SKUs to include within your product range.

Reach of product portfolio

Using preference share simulations to perfect your product range

Simulations help companies analyse the market through a competitive context, through creating different possible scenarios. These simulations help to identify the most attractive products / product groups, set the foundation for market-orientated assortment and consistent product range expansion.

Using preference share simulations

Run simulations before modifying product range

Before making any changes to a product range, it is prudent to create a scenario plan, particularly when operating in a competitive environment.

A scenario plan will map out the expected impact of any delisted lines, the expected rate of switching to alternative products, as well as clear sales targets for any new products being introduced. It will also include scenarios regarding updating the entire range, launching new products, removing certain SKUs and so on.

Preference share simulation

Prioritise product development

It is important to learn the order of priority for launching your NPDS, to ensure an optimal range and a higher level of incremental acceptance of future NPDs. This helps to develop an action plan for the implementation of the assortment strategy to establish and maintain a customer loyalty.
Optimal product range

Fast and reliable results for range optimisation

Which range of flavours would produce the highest market penetration?

All Natural is a global snacks manufacturer. All Natural wants to start a new range of fruit drinks to complement their current range of snacks.

Example conjoint analysis report for preferences in ice-cream cones

We do simulation analysis with different price points and different variations of attributes.

Which SKUs should not be removed to keep the highest market share?

Download case study

Context

Comforty is a global personal care company which has many SKUs for its foot care product. Comforty wants to streamline its current product portfolio without losing much volume share in the market.

Goals

After research and extensive talks with their strategic team, Comforty would like to remove every possible redundant SKU no matter which range it comes from. The SKUs cover different sizes, different functions, different types of shoes for both female and male.

As both shelf spaces are limited at two channels, Comforty would like to know which SKUs to keep without losing much volume share.

Outputs

  • Brand specific conjoint found that the preference share for 20 different SKUs along with other competitors.
  • Preference share simulation compares the results of removing all extra SKUs and provides actionable insights to help Comforty to see the maximum preference share for each number of SKUs in the portfolio.
  • Comforty proceeded to cannibalise the range of insoles by removing 14 less competitive SKUs to maintain 10% lower preference share.

Conjoint.ly platform makes product research easy

You get agency-quality results at a fraction of the cost and time investment. One powerful end-to-end platform for insights teams for fast and reliable market research.

Powerful pricing research tools

Our methods are thoroughly tested and rooted in marketing science.

User-friendly interface

Design your pricing study with our intuitive interface for fully automated experiments

Response quality control

Let Conjoint.ly collect data for you, checking for the quality of responses.

Detailed interactive reports

Conjoint.ly will automatically analyse the data and prepare online and Excel reports.


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Do you need support in running a pricing or product study? We can help you with agile consumer research and conjoint analysis.

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Understand range optimisation in detail

Conjoint Preference Share Simulator

Conjoint.ly allows you to simulate shares of preference for different market offerings. Specifically, you need to describe offerings that are available on the market in the language of the attributes and levels that you chose to include in the study, and the system will estimate the percentages of preferences for these offerings.

Explaining TURF Analysis and When to Use It

TURF analysis (Total Unduplicated Reach and Frequency) is a statistical technique that ranks combinations of products by how many people will like these combinations.

Product Variant Selector

Conjoint.ly Product Variant Selector is a comprehensive methodology for testing up to 300 product ideas that helps you identify the most appealing product variants for your brand or product category. It combines several techniques that our team have developed and refined on full-service projects for FMCG brands.