Feature Price Impact

The method first measures the synthetic consumers’ (personas’) willingness to pay (WTP) for the base product: the highest price at which they would still buy it. The base product is the product without any of the features you are testing. It then adds each feature to the base product on its own and measures the difference in lira.

When to use

Use this method when you want to put a lira value on a short list of features (1–5 features). It shows which feature can support a higher price, and which leaves willingness to pay unchanged or lowers it.

Features are not tested together, so the method does not measure the total value of a feature bundle.

What personas are asked

1. For every price on the price ladder, the persona is asked whether they would buy the base product. This gives the baseline willingness to pay.
2. For each feature, the persona is first asked, without a price, whether the feature would increase, decrease or not change the amount they would pay (the direction question). Then up to 4 price questions, starting from the persona’s baseline willingness to pay, find the new upper limit.
3. For each feature, the whole price ladder is asked again with the feature added to the product. This gives the demand curve with the feature.

The description you write for a feature is added to the product description and shown to the persona in that feature’s questions.

Before you start

• Population. During setup you can select an existing population or create a new one. See Creating a population for details.
• Product information. Prepare a recognisable product name and a short description. The price check estimates the market price from the product name.
• Price ladder. Set a realistic minimum price, maximum price and step for the base product. The same ladder is also asked for each feature.
• Features. Write each feature as a single, concrete change to the base product: use measurable wording such as “an extra 2-year warranty” rather than “better quality”.

Setting up the study

The steps below are for General Research. The differences in Fashion are described after the steps.

1. In the sidebar, click New Research and select the General Research card.
2. On the Choose Your Research Type screen, select the Feature Price Impact card.
3. On the Choose Population Mode screen, continue with Select Existing Population or Create New Population.
4. The design page opens with the title Feature Value Analysis. To use a design you saved earlier, select it from the Select from Saved Surveys card. If you change any field after selecting it, the selection is cleared.
5. In the Price Analysis Settings card, fill in the Product Name field. Optionally, write a short description in the Product Description (Optional) field.
6. Enter the Minimum Price (₺), Maximum Price (₺) and Price Step (₺) values. The resulting prices appear in the Price Points (N items) section. Add a price that is not on the ladder with Add Custom Price.
7. In the Features to Test card, type a feature name and press Enter or click the + button. Optionally, enter a short description in the field below each feature.
8. When the status line shows something like 3 feature(s) ready for analysis, click Next Step and choose Continue in the confirmation dialog.
9. Wait for the price check to finish. If your range is outside the market estimate, the Price might not be realistic warning opens. Click Cancel to fix the range, or tick I want to proceed anyway and click Continue.
10. On the Research Preview page, check the Experiment Summary card: Person Count, Price Point, Feature Count and Credit Usage.
11. Click Start and choose Continue in the confirmation dialog.
12. When the study finishes, the Your analysis is ready card appears on the progress screen and the report opens automatically within a few seconds. To go there without waiting, click Go to Reports.

If the personas are still being generated, the Next Step button reads Waiting…. If you leave the progress screen, the study keeps running in the background; you can find the finished study on the Reports page with the Feature Value filter. For the general flow of the wizard, see Starting a new study.

In the Fashion vertical

• Select Fashion, then the Feature Price Impact card. At the population step, choose Use existing population or Create a new population. Continue once the badge on the design page reads Popülasyon hazır (Population ready).
• In the Ürün kaynağı (Product source) card above the price settings, paste the link to the product page into the Product URL field, or upload a photo with Ürün fotoğrafı (opsiyonel) (Product photo (optional)). The card is described in detail on the Price Analysis (WTP) page.
• When you click Next Step, the button reads Validating price… while the price check runs. If the price ladder is far outside the market estimate, the Fiyat merdiveni pazar aralığının dışında (Price ladder is outside the market range) dialog opens. If it offers a suggestion, click Önerilen merdiveni uygula (Apply the suggested ladder); to continue with your own ladder, click Yine de çalıştır (Run anyway).

Settings and limits

With the default values, the ladder has 6 points from ₺500 to ₺1,000. If the number of points falls outside 3–16, a warning starting with Number of price points must be between 3 and 16 appears. After the fifth feature, the input field is disabled.

Credit calculation

The estimated credits are calculated with this formula:

credits = number of personas × (P + F × (P + 5))

Here P is the number of price points (including custom prices) and F is the number of features. The first P is the base product’s ladder. For each feature, P covers the full ladder for the product with the feature, and 5 covers the direction question and up to 4 price questions.

Example: 100 personas, 6 price points from ₺500 to ₺1,000 in ₺100 steps, and 3 features.

• 100 × (6 + 3 × (6 + 5)) = 100 × 39 = 3,900 credits
• With the same population and ladder, Price Analysis costs 6 × 100 = 600 credits.
• In this example, each additional feature adds 100 × 11 = 1,100 credits.

The credit amount does not appear on the design screens. You see the estimated credits, together with your balance, in the Credit Usage row on the Research Preview page (e.g. 5.000/3.900). If your balance is too low, a red info icon appears next to the value and the study does not run; hover over the icon to see the Buy Credits button.

Credits are deducted after the personas’ responses are saved. In Fashion, no credits are deducted for a failed study; in General Research, a study that fails before any responses are saved does not use credits either. In General Research, the amount deducted is based on the responses the study saved. In General Research, if only the analysis step failed, the deducted credits are not refunded; when you click Back to Preview and then Start again, only the analysis runs again and no credits are deducted a second time. Opening a report and downloading files do not use credits. See Credits for details.

Reading the results

At the top of the report page are the Feature Value Analysis label, the product name as the title, and the New Research, Refresh, Download PDF, Download Excel and Delete buttons. On this page, Refresh only reloads the data on the page; it does not run the study again.

Summary cards

A paired persona, as used on the cards, is a persona with both an exact willingness to pay for the base product and a measurable willingness to pay for the product with the feature. Personas who refuse even the lowest base price are left out of the average difference.

Demand Curves tab

• Acceptance Curve (Demand): For the base product (Baseline (no features)) and each feature, the share of personas willing to buy the product as the price rises. Hover over the points to see Demand rate and Personas willing to buy. Click a series in the legend to hide it; double-click it to keep only that series. If a feature’s curve lies above the base curve, that feature makes more personas willing to buy the product at the same price.
• If a feature has no measurement covering all personas at every price, its curve is not shown and an explanation appears in the chart. This does not mean the effect is zero.
• Average WTP Change by Starting Baseline Price: Groups personas by their exactly known willingness to pay for the base product (the starting baseline price) and shows by how many lira, on average, each group’s willingness to pay changes when the feature is added (Curve or Columns view). This is where you see whether a feature has a different effect on personas with low and high willingness to pay.

Analysing by segment

A segment is a subgroup of the population (e.g. an age group or a socio-economic status (SES) class). In the segment views, you first choose a dimension (e.g. age or SES); the results are then split into that dimension’s segments. Segments with fewer than 5 personas are not shown; if no segments are left to show, the chart reads Insufficient segment data (at least 5 participants per segment required).

Segment Analysis tab:

• Feature Impact Distribution: Choose a feature with Product Feature and a dimension with Analysis. The chart shows the change in willingness to pay in each segment on the WTP Change (TL) axis. Hover over a segment to see the mean and median difference, the shares of personas affected positively, neutrally and negatively, and the number of Paired personas.
• Segment-Based Optimal Price: The price that maximises each segment’s revenue for the selected feature. The columns are Segment, Optimal Price, Optimal Revenue, Purchase (%) and Demand; you can download the table with Download CSV.

Crosstab tab:

• Price Sensitivity: Shows how segments behave at each price point, based on your Product Feature, Analysis and Metric selections. The Metric options are Demand, Revenue, Purchase (%) and Purchase-Rate Difference. Purchase-Rate Difference is the purchase rate for the product with the feature minus the base product’s rate, at the same price and in the same segment; it is measured in percentage points, not lira.
• Accept/Refuse Rates at … chart (the title ends with the price you select): Select a Price and a Segment to see each segment’s acceptance and refusal rates at that price.

To work with market segments, see Segmentation.

Exporting

• Download PDF: If the report has eligible segment dimensions, the PDF segment selection dialog opens, with no dimension ticked. Tick the dimensions to include (Select all selects them all) and click Generate PDF. The file downloads automatically when it is ready.
• Download Excel: Prepares an Excel file with all the data. The sheet names are in English; the headings inside the sheets are in the interface language.

The PDF report is also produced in the interface language. To get the file in the other language, switch the interface language first. Delete removes the report’s analysis results; it does not delete the study itself. See Exporting and downloading for details.

Tips and common mistakes

• Effects don’t add up. The sum of two features’ lira differences does not show the price you would get by offering both together.
• Read the Coverage row. If coverage is low, the Conditional Average Delta represents only a small part of the population.
• Build a realistic ladder. Set the lowest price at a level where most personas could accept the base product; personas who refuse this price are left out of the average difference.
• A missing curve is not a zero effect. Refreshing the report does not fill in missing measurements; you need a new study.
• Reuse the design. Find your saved designs in the Surveys library with the Feature Value filter. To run a design on another population, see Quick Research.
• Use the results in the right context. The results are language model output; they show the direction and size of an effect. Validate high-stakes pricing decisions with real consumers. See Accuracy and limitations for details.

Related pages

• Price Analysis (WTP)
• Priority Ranking (MaxDiff)
• Credits
• Reading a report
• Exporting and downloading