BPTO

Brand-Price Trade-Off

Brand-Price Trade-Off (BPTO) is a specialised tool that helps answer pricing questions for consumer goods in a competitive context, such as:

  • How will revenue, profitability, and market volume perform after launching a new product at a specific price point?
  • How will revenue, profitability, and market volume perform after re-pricing an existing product?
  • Where will the NPD source volume from (cannibalise your other products or take share from competition)?
  • What is the effect of awareness and advertising on the adoption of new concepts?

The methodology borrows from the ideas and algorithms of conjoint analysis and Gabor-Granger. It is a choice-based technique that reflects consumers' differing preferences for SKUs/brands as well as budget and psychological pricing constraints.


Main outputs

NPD volume share simulation

NPD volume share simulation

Through simulation, we can estimate Conjointly's volume share following the introduction of our NPDs; performance is compared before and after adcepts are shown to the respondent. This helps to assess the effect that awareness/advertising has on the adoption of our NPDs.

The example study shows that NPD Lemon has the highest adoption rate, even before the adcept is displayed.

Movements in volume share

Movements in volume share

Movements in volume share show the increase and decrease in each of the current SKUs after introducing our NPDs. This helps to determine whether each NPD's increased volume share is derived from our existing SKUs or from competitors.

Our example study shows that each NPD’s market share sources different proportions from our competitors.

Price elasticity

Price elasticity

We're able to calculate the specific co-efficient of price elasticity of demand for our NPDs by selecting two points on our simulation chart (the approximate price elasticity of demand is automatically calculated and displayed in Conjointly). This helps us to understand how market volume will perform at the different price points our NPDs were tested at.

The example study shows that for Conjointly Kiwi, demand is elastic (i.e., an increase in price by 1% leads to more than 1% drop in volume). Revenue does not vary greatly, regardless of price point.

Revenue/Profits Index.

Revenue/Profits Index.

Through simulation, we can learn how our NPDs' revenue and profitability will perform at different price points. Revenue projections are displayed in the simulation chart by default (this can be switched to profitability) and are calculated by assuming 1000 units offered. Profitability is calculated using assumed fixed and variable costs through the formulas: Revenue = price * share * 1000; Profit = (price-$1) * share * 1000. Adjustments are also available by replacing market size with assumed 1000 units.

Our example study shows that for Conjointly Lemon, Revenue does not vary greatly, regardless of price point. Demand is elastic.

Van Westendorp Price Sensitivity Meter

Van Westendorp Price Sensitivity Meter

Van Westendorp results will show us a psychologically acceptable range of price for our NPDs. It can be used as a diagnostic to validate the recommended price from the main conjoint exercise.

Other outputs

Other outputs

Raw data is available as an Excel output — confidence intervals are provided wherever possible, and all reports are segmentable by respondent characteristics such as information provided from panel profiling, respondents' answers to panel responses to additional questions, screening questions, and your uploaded variables.

These results will help us to answer the following (and similar) questions:

  • Are the results significantly different with confidence intervals?
  • What are the performances of different segments?

When to use Brand-Price Trade-Off

The tool works best when:

  • You are investigating consumer goods (including durable goods, cosmetics, over-the-counter pharmaceuticals, and alcohol).
  • You are only looking at SKUs and price points (no other features of the product).
  • Price points are on a consistent scale (i.e. you are not comparing price per litre vs. price per kg).
  • There is existing competition (at least 3 competitor SKUs).

The tool works for pricing NPDs as well as re-pricing existing products.

The tool takes into account:

  • Price barriers,
  • Differences in price sensitivity by SKU/brand,
  • Effect of exposure to advertising,
  • Differences in behaviour by type of consumer (users vs. considerers), and
  • Individual differences in price sensitivity for each respondent.

This tool, however, does not take into account:

  • Unique products or products in an entirely new category without existing competition. Gabor-Granger should be used instead.
  • Psychological pricing (i.e. whether the price ends in .99 or .95): Monadic (“A/B”) price testing or Brand-Specific Conjoint is a better fit for this type of research questions.
  • Positive price elasticities (i.e. when consumers are willing to buy the product at a higher price point more than at a lower price point). Brand-Specific Conjoint suits such situations better.

Survey flow

The survey flow consists of four separate exercises, with the purpose of introducing both our existing SKUs and competitor SKUs before introducing respondents to our NPDs:

1. Conjoint exercise presents various brands along with current offering.

Brand-Price Trade-Off's conjoint exercise presents various brands along with current offering

2. Conjoint exercise presents various brands along with NPD before adcepts.

The new proposition is added to existing SKUs.

Brand-Price Trade-Off's conjoint exercise presents various brands along with NPD before adcepts

3. Introduce NPDs through adcepts.

Adcepts explain the NPD as a picture board or video.

Brand-Price Trade-Off introduces NPDs through adcepts

4. Conjoint exercise presents various brands along with NPD after adcepts.

This can be followed by diagnostic questions, such as Van Westendorp Price Sensitivity Meter, as well as additional questions.

Brand-Price Trade-Off's conjoint exercise presents various brands along with NPD after adcepts

Complete solution for pricing research

SURV

Survey Tool

Fully-functional online survey tool with various question types, logic, randomisation, and reporting for unlimited number of responses and surveys.

GC
Range optimisation
Features and claims

Generic Conjoint

Feature and claim selection and measuring willingness to pay for features for a single product.

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MaxDiff (aka Maximum Difference Scaling or Best–Worst Scaling) is a statistical technique that creates a robust ranking of different items, such as product features.

CT
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Claims Test

Efficiently test up to 300 product claims on customer appeal, fit with brand, and diagnostic questions of your choice.

BSC
Pricing research
Range optimisation

Brand-Specific Conjoint

Pricing, feature and claim selection in markets where product characteristics vary across brands, SKUs, or price tiers.

PVS
Range optimisation

Product Variant Selector

Identify winning product variants from up to 300 different ideas (e.g., designs, materials, bundle options) on customer appeal, fit with brand, and diagnostic questions of your choice.

BPTO
Pricing research

Brand-Price Trade-Off

Test pricing of new and existing consumer goods in a competitive context using elasticity charts, revenue, and profitability projections.

GG
Pricing research

Gabor-Granger Pricing Method

Determine price elasticity for a single product and identify revenue-maximising price level.

VW
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Van Westendorp Price Sensitivity Meter

The Price Sensitivity Meter helps determine psychologically acceptable range of prices for a single product and approximately estimate price elasticity.

AB
Concept testing

A/B Test

Perform focussed comparisons between two items to determine which performs better.

MT
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Monadic Test

Ask respondents to evaluate product concepts and digital assets one-by-one to get a read of their preferences and perceptions with various question types.

AT
Concept testing

Ad Test

Test the effectiveness of your advertisements using a comprehensive research method

DAT
Concept testing

Digital Asset Test

Test the effectiveness of your digital advertisements in an online environment

IT
Concept testing

Image Test

Test the effectiveness of your images in an online environment

BNT
Concept testing

Brand Name Test

Efficiently test potential brand names to identify the best one to represent your business

BNE
Concept testing

Business Name Evaluator

Efficiently evaluate potential business names to identify the best one to represent your brand

DNLC
Concept testing

Domain Name Likability Check

Efficiently test potential domain names to identify the perfect new home for your brand

PDT
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Product Description Test

Validate your product descriptions before release

PNT
Concept testing

Product Name Test

Efficiently test potential product names to identify the best one to reflect your brand

PCT
Concept testing

Product Concept Test

Determine the best concepts through focussed testing

VT
Concept testing

Video Test

Test the effectiveness of your videos in an online environment

IS
Concept testing

Idea Screener

Perform preliminary screening to find your best product ideas.

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Package Test

Discover the best packaging for your products

TURF
Range optimisation
Features and claims

TURF Analysis Simulator

Conduct automated TURF analysis on results of any Conjointly experiment (or an outside dataset) using this user-friendly TURF analysis tool.

DIY

DIY Experimental Design

Allowing advanced choice modellers to upload their own experimental designs and perform data collection on Conjointly.

KANO
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Feature and Pricing Suite for SaaS

Kano Model

Ensure product-market fit and maximise your user acquisition and expansion, by differentiating software features according to your users' needs.