Use case: pricing research

Pricing research: what your market will actually pay

Establish willingness to pay with the established methods — Van Westendorp for the accepted price range, choice-based conjoint for price in a competitive set. Fielding, estimation and the simulator live in one platform. ISO 27001-certified hosting, GDPR-compliant, made in Munich.

Interactive DataLion dashboard with price curves, tables and filters for a pricing study

DataLion covers pricing research from fielding to analysis. Van Westendorp ships as its own chart type: it draws four cumulative price curves, shades the accepted price range and marks the optimal price point. Choice-based conjoint runs natively with design, fielding and estimation on R. The preference simulator reports preference shares and willingness to pay in currency.

  • 🇩🇪 Made in Munich
  • GDPR-compliant
  • DPA included
  • Hosted in Germany
  • 🌐 Interface in EN, DE, FR & NL

Trusted by research institutes, brands & insights teams

  • YouGov
  • Mediengruppe RTL Deutschland
  • SevenOne Media
  • Nielsen Sports
  • Spiegel Institut
  • Messe Berlin
  • Hartmann
  • 4 curves Van Westendorp price curves
  • PMC · OPP · PME computed price points
  • logit/MNL on R conjoint estimation
  • WTP willingness to pay in the simulator

Why pricing decisions still get made on instinct

  • The price question gets asked, but the analysis stops at the mean — the accepted range stays invisible.
  • Conjoint data goes out to an agency and comes back as a PDF nobody can recompute.
  • The pricing meeting is missing exactly the one scenario somebody now wants to see.

Van Westendorp: make the accepted price range visible

DataLion analyzes the four classic price questions — too cheap, cheap, expensive, too expensive — with a dedicated chart type. It bins the stated prices into fine price steps and draws four cumulative curves from them: two falling, two rising.

Where those curves cross you get the point of marginal cheapness (PMC), the point of marginal expensiveness (PME) and the optimal price point (OPP). The chart shades the accepted price range between the two limits and marks the optimal price point with a line — so the pricing debate starts from a picture rather than a spreadsheet.

  • Four cumulative price curves from the four Van Westendorp questions
  • Accepted price range shaded between PMC and PME
  • Optimal price point (OPP) marked as a line
  • Ready-made questionnaire template: price sensitivity (Van Westendorp)
Cumulative price curves of a Van Westendorp analysis in DataLion

Conjoint: price in the context of the whole product

Van Westendorp asks about price on its own. In reality customers trade price against features. That is exactly what choice-based conjoint captures — and it runs natively in DataLion: you define attributes and levels, DataLion generates a balanced choice design, fields it through its own survey and estimates the utilities with a logit model (MNL) on the R engine.

From those utilities DataLion computes attribute importance — the share each attribute contributes to the decision. If your design includes a price attribute, the simulator also converts utilities into currency amounts, giving you the willingness to pay for every single level.

  • Balanced, reproducible choice design across several questionnaire versions
  • Part-worth utilities estimated by logit/MNL on the R engine
  • Attribute importance in percent from the range of the utilities
  • Willingness to pay in currency as soon as a price attribute is in the design
Attribute importance and utilities of a conjoint analysis in DataLion

Play through price scenarios in the simulator

The built-in preference simulator answers the question that actually gets asked in the pricing meeting: what happens if we move the price up one step? You assemble competing products level by level — optionally including a none-of-these option — and see each product’s preference share recomputed immediately.

The sensitivity view sweeps each attribute through all of its levels and ranks them by how far they move the preference share. One picture tells you whether price or a feature is the stronger lever.

  • Assemble competing products, none-of-these option optional
  • Preference shares in percent, recalculated live
  • Sensitivity view: which attribute moves the share most
  • Break results out by audience via a screener question
Preference simulator with product scenarios and preference shares in DataLion

Willingness to pay by segment — with significance

An average price almost always hides the fact that segments pay differently. So break price acceptance and utilities down with live filters by audience, region, customer type or usage intensity. The conjoint analysis compares subgroups side by side and reports the base size for each column.

Differences between segments are significance-tested right in the table — at 80%, 90%, 95% or 99% confidence via z-test, chi² or t-test. If a weight variable is present, DataLion computes price acceptance against your target frame.

  • Live filters by audience, region, customer type or usage intensity
  • Subgroup comparison with the base size shown per column
  • Significance at 80/90/95/99% — as stars or letters
  • Weighted analysis against the target frame of your sample
DataLion table showing price acceptance by segment with significance markers

Launch pricing studies with ready-made questionnaires

You do not have to build a pricing study from scratch. DataLion ships ready-made questionnaire templates: price sensitivity by Van Westendorp with the four canonical price questions, and a Gabor-Granger price test with stepped purchase-intent questions. Both are bilingual and adapted in minutes.

On publishing, DataLion creates the project, dataset and codebook with value labels automatically. Stated prices are analyzable right away — no recoding, no export to SPSS. For the Gabor-Granger test you assemble the demand curve from the standard chart types; there is no dedicated Gabor-Granger analysis.

  • Bilingual templates for Van Westendorp and Gabor-Granger
  • Auto-codebook with value labels — analyzable at once, no recodes
  • Invite by anonymous link, QR code or one-time token
  • Demand curve for the Gabor-Granger test from standard chart types
DataLion survey editor with the question types of a pricing study

What you can build with DataLion

  • Van Westendorp pricing study

    Four price curves, accepted range and the optimal price point.

    See the template →
  • Conjoint with a price simulator

    Utilities, attribute importance and willingness to pay.

    See how →
  • Price acceptance by segment

    Weighted and checked for significance.

    See how →

See DataLion with your own data

Start free with your own raw data. Or book a personal demo of the path to a finished dashboard.

Top rated

4.5 out of 5 stars on G2 and OMR Reviews

What users say about DataLion

  • via G2
    Very professional company, attentive to the customer needs, provider of a great software and service.
    Generoso M. · CRM Analyst, Automotive
  • via G2
    The contacts at DataLion are very committed. If you have problems, you can count on help. DataLion reacts quickly to requests for new functions.
    Robert Q. · Managing Director
  • via G2
    User-friendliness, especially for market research topics. Structured backend with many customization options.
    Verified user · Market Research
  • via G2
    The embedding function allows us to generate insights of our data for our audience and customers by far less than half of the usual time needed before.
    Verified user · Leisure, Travel & Tourism
Read all 16 reviews on G2 →
We now work much more efficiently, giving us more time to take care of the derivations and insights from the data for the customers.
Jens Falkenau, Vice President of Market Research · Nielsen Sports
Read the case study →

The platform in detail

Go deeper

Common questions about pricing research with DataLion

Can DataLion run a Van Westendorp analysis?
Yes. The four price questions have their own chart type. It bins the stated prices into fine price steps, draws four cumulative curves and derives the point of marginal cheapness (PMC), the point of marginal expensiveness (PME) and the optimal price point (OPP) from where they cross. The accepted price range is shaded and the optimal price point is marked with a line.
How do I establish willingness to pay?
Through choice-based conjoint. DataLion generates a balanced choice design, fields it through its own survey and estimates the utilities with a logit model on the R engine. If the design contains a price attribute, the preference simulator converts those utilities into currency amounts and reports the willingness to pay for each level.
Does DataLion support Gabor-Granger?
As a questionnaire, yes: there is a ready-made bilingual template for the Gabor-Granger price test with stepped purchase-intent questions. You then assemble the demand curve and the revenue view from the standard chart types — there is no dedicated Gabor-Granger analysis of the kind that exists for Van Westendorp.
Does DataLion estimate conjoint with hierarchical Bayes?
No. Estimation runs as an aggregate logit model (MNL) on the R engine and produces utilities at sample and subgroup level. Individual-level utilities via hierarchical Bayes are not included. Utilities computed elsewhere can be imported and visualized in DataLion.
Can I analyze willingness to pay by audience?
Yes. The conjoint analysis compares subgroups side by side via a screener question and reports the base size per column. On top of that you can break any price analysis down by segment with live filters, compute it weighted, and test differences at 80 to 99% confidence.

Ready to prove your price instead of guessing it?

Try DataLion free with a ready-made pricing-study template — from the four price questions to the simulator. Or book a personal demo.