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.
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
.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.
Using an example study we conducted for a new line of Conjoint.ly soft drinks, we walk through the outputs that BPTO produces for new products and prices, including volume share simulations, movements of volume share, acceptable price ranges, price elasticity, and revenue/profit index.
The study examined different price points for Conjoint.ly's new line of soft drinks, and produced several outputs;
NPD volume share simulation. Through simulation, we can estimate Conjoint.ly'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 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. 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 Conjoint.ly). 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 Conjoint.ly 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. 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:Our example study shows that for Conjoint.ly Lemon, Revenue does not vary greatly, regardless of price point. Demand is elastic:
Revenue = price * share * 1000;
Profit = (price-$1) * share * 1000. Adjustments are also available by replacing market size with assumed 1000 units.
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.
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?
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;
- Conjoint exercise presents various brands along with current offering.
- Conjoint exercise presents various brands along with NPD before adcepts. The new proposition
is added to existing SKUs.
- Introduce NPDs through adcepts. Adcepts explain the NPD as a picture board or video.
- 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.
Setting up Brand-Price Trade-Off
Using our example study for Conjoint.ly soft drinks, we explain how to set up your own BPTO study, step-by-step.
Context: Launch of one of three NPD flavours for a new soft drink.
We are preparing to release a new product: a fruity soft drink can. The product will come in a 375mL can and we aim to price it higher than our 200mL can offering. However, the price is not set and needs to be assessed through pre-launch research.
To understand the pricing opportunities available, we'll the following research questions:
- RQ1: How will overall revenue, profitability, and market share perform at aimed pricing (40% higher than current)?
- RQ2: What are pricing opportunities for the new larger can?
- RQ3: What is the difference in value between the three flavours (Lemon, Kiwi, and Apple)?
- RQ4: How to convert existing consumers of soft drinks, and attract new users?
What inputs do you need for this study?
To begin, several inputs are required to provide sufficient information for your study;
- Category definition
This should be a clear category, such as “Soft Drink Can (fruit-flavoured)”.
- Your current competitor SKUs
- Your current SKUs
- Your NPD
Each of your existing SKU/s require:
- SKU names
- SKU packshots
- SKU price points (current and potentially several additional price points)
- Current volume share (physical volumes, not value share)
- You will also need an adcept if you want to measure the effect of awareness on NPD adoption.
Considerations for good inputsTo ensure your survey displays your inputs accurately for your respondents, there's a few points to keep in mind:
Your study will need at least four current SKUs (including your SKUs and competitor SKUs) — you should ideally select SKUs that cover at least 80% of the market by volume. Also, you may want to include highly salient SKUs (emerging brands that you want to compete against). If there are currently more than 20 SKUs in your market, please consider limiting the SKU count to 20 to optimise the study's sample size.
Price points should be on a consistent scale (for example, “$XX.99 per 800g” should not be mixed with “£XX.50 per 1 litre”.
Packshot images need to be of consistent quality and size.
We recommend providing 5 to 10 potential price points for each SKU (including current your SKUs, current competitor, and the NPD). For example, if you provide 5 price points, you can insert:
- Current price point
- A price point 10% lower than the current price
- A price point 10% higher than the current price
- A price point 20% higher than the current price
- A price point 30% higher than the current price
SKU names and prices can be supplied in a table format, for example:
Competitor SKU 1 $20 per 1kg $22 per 1kg $25 per 1kg $27 per 1kg $30 per 1kg $32 per 1kg $35 per 1kg Competitor SKU 2 $20 per 1kg $22 per 1kg $25 per 1kg $27 per 1kg $30 per 1kg $32 per 1kg $35 per 1kg Our SKU 1 $20 per 1kg $22 per 1kg $25 per 1kg $27 per 1kg $30 per 1kg $32 per 1kg $35 per 1kg Our SKU 2 $22 per 1kg $25 per 1kg $27 per 1kg $30 per 1kg $32 per 1kg $35 per 1kg Our SKU 3 $27 per 1kg $30 per 1kg $32 per 1kg $35 per 1kg $37 per 1kg $40 per 1kg Our SKU 4 $30 per 1kg $32 per 1kg $35 per 1kg $37 per 1kg $40 per 1kg $42 per 1kg $45 per 1kg Our NPD 1 $30 per 1kg $32 per 1kg $35 per 1kg $37 per 1kg $40 per 1kg $42 per 1kg $45 per 1kg Our NPD 2 $30 per 1kg $32 per 1kg $35 per 1kg $37 per 1kg $40 per 1kg $42 per 1kg $45 per 1kg
- Your NPDs should be tested against a wide range of options that potential buyers would likely also consider.
Setting up your studyOnce all your inputs are added, it's time to set up your study;
Step 1. Specify your category
- Name the experiment
- Enter the category name, e.g. "Soft Drink Can (fruit-flavoured)"
Step 2: Import SKUs and prices
Copy and paste the SKUs and prices from Excel (as in above example). If you don't have them available in the format, skip to Step 3.
Step 3: List SKUs
List all the SKUs for the test, including:
- Your current competitor SKUs,
- Your current SKUs, and
- Your NPD SKU/s.
Insert visual stimuli: Click on the highlighted icon.
- Drag and drop images into the pop-up window. Alternatively, you can copy them from the buffer or upload from your computer files)
- Arrange SKUs on the set-up page into appropriate categories by selecting the highlighted icon and
dragging them around.
Insert your NPD adcept/s. Adcepts bring your proposition to life — they can be either a picture board or a video that shows the product, with a short story, including benefits and reasons to believe. You can choose how long your respondents must view your adcept before continuing the survey.
Step 5: Specify potential prices
- List all prices. Click the “Add price” button to add more price levels.
- Specify the “text” of the price (i.e. what respondents will see) and the numerical values of prices for the model.
- Allocate prices to specific SKUs by ticking the check boxes.
- Optionally, review the price map. This view helps you check the distribution of prices.
Note that the greater the number of SKUs and price points you test, the higher the required sample size. A recommended sample size will be automatically calculated;
Step 6: Choose respondents
There are three ways to choose respondents, dependent on targeting.
Step 7: Save
- Save and customise: This tool also allows you to customise respondent interface, insert other question types, and apply advanced settings, e.g. setting up redirects and running the survey in multiple languages.
- Save and prepare for launch.
Final step: Launch
- Review your survey at least once before fieldwork starts.
- Even if you are running it in a fully self-serve mode, seeking at least one round of review from the Conjoint.ly team before the study is launched;
- Once you are ready, you can press “Launch”.