Auswahlmodellierung Marktforschung

Quantitative Marktforschung ist eine auf offenen Fragen basierende Forschungsmethode. Sie basiert auf ausführlichen Interviews, Fokusgruppen und anderen modernen Techniken. Was ist der Unterschied zwischen quantitativer und qualitativer Forschung?

Bei der quantitativen Marktforschung werden Fragen mit einem numerischen Wert gestellt. Beispiel: „Wie war Ihre Erfahrung mit dem Kundenservice auf einer Skala von 1 bis 5?“ Eine andere Frage könnte lauten: „Wie hoch ist Ihr Jahresgehalt?“

Qualitative Forschung stellt Fragen, die sich nicht auf eine Zahl reduzieren lassen. Zum Beispiel: „Was ist Ihre Berufsbezeichnung?“ oder „Was hat Ihnen heute an unserem Service am besten gefallen?“

The researcher who is looking for scientific results will lean on Quantitative Forschung. It tends to be more impartial. They choose it because it is:

• Einfachere Kontrolle der Daten
• Unvoreingenommen und wissenschaftlich
• Für ein größeres Publikum geeignet
• Höhere Akzeptanz
• Zielgerichteter, da Forscher es häufig verwenden, um eine Theorie zu testen.

Was ist Choice-Modeling-Marktforschung?

Choice Modeling is a Quantitative Research technique used to measure what consumers like. It’s different from standard Surveys and Market Research methods. Moreover, these methods only capture a rough picture of consumer intentions, often not supported by science. Choice Modeling uses a controlled trial run, which finds and measures the factors that lead to a decision. It does so even outside the conscious awareness of the respondents.

Choice Modeling Market Research: How Industrial Leaders Quantify Buyer Trade-Offs

Choice Modeling Market Research reveals what industrial buyers actually value when forced to trade price against performance, warranty against lead time, and brand against specification. Stated preference surveys ask buyers what they want. Choice models reveal what they will pay for.

For a Fortune 500 leadership team setting price, configuring a portfolio, or sequencing a product launch, this distinction is the difference between a forecast that holds and one that collapses on contact with the market.

Why Choice Modeling Outperforms Stated Preference in B2B Industrial Markets

Direct preference questions inflate the importance of every attribute. Procurement managers rate uptime, service network, and price as “highly important” because none of them carries a cost in the survey. Choice tasks impose the trade-off the buyer faces in a sourcing committee.

The mechanics matter. Discrete choice experiments present rotating scenarios where each option bundles attributes at varying levels. Respondents pick one. The resulting utilities decompose into part-worths, and the part-worths feed a market simulator that estimates share under any configuration the team wants to test.

This is why choice modeling has become standard for OEM procurement analysis, total cost of ownership positioning, and aftermarket revenue strategy. The simulator answers the question a CFO actually asks: what happens to share and margin if we raise price 7 percent and extend the warranty by twelve months?

The Attribute Architecture That Separates Useful Models from Expensive Ones

The quality of a choice model is set before fielding. Attribute selection, level spacing, and the design of the choice set determine whether the output guides a pricing committee or misleads it.

Three architectural choices separate the work that holds up in a board review from the work that does not.

Attribute realism. Levels must span the range buyers will encounter, including the competitive option the sales team loses to most often. Models that omit the disruptive low-price entrant overstate share for the incumbent.

Interaction effects. In industrial categories, brand interacts with warranty, and service network interacts with geography. Main-effects-only designs miss the structure that drives the actual purchase.

Decision-maker specification. The specifier, the user, and the procurement signatory weigh attributes differently. Pooling them produces an average buyer who does not exist.

According to SIS International Research, choice models built on B2B expert interviews with both technical specifiers and procurement leads produce share predictions that track actual win rates within a tighter band than models fielded to a single role. The gap widens in categories with installed base analytics and long replacement cycles, where the user and the buyer have divergent utility curves.

Where Choice Modeling Creates the Largest Commercial Lift

Four decisions absorb most of the value choice modeling generates in industrial markets.

Pricing under competitive response. The simulator allows the pricing team to test reactions from named competitors at named price points. Caterpillar raising list 4 percent. Komatsu holding. The model returns share, revenue, and contribution under each path.

Bundle configuration. Aftermarket service contracts, extended warranty, telematics subscriptions, and financing terms each carry a part-worth. Choice modeling identifies which combinations capture the largest willingness-to-pay premium without cannibalizing the base product.

Feature prioritization in the bill of materials. Engineering wants every feature. Finance wants none. Choice modeling prices each feature against the margin it earns, which converts the BOM debate from opinion to evidence.

Launch sequencing across geographies. Part-worths differ by country. A predictive maintenance package that commands a premium in Germany may be ignored in Brazil. Sequencing the launch around the highest-utility markets compresses payback.

The Methods Behind the Method

Choice Modeling Market Research is a family, not a single technique. The selection depends on the decision.

Source: SIS International Research

The method gets selected to the decision, not to the analyst’s preference. A team running aftermarket revenue strategy uses menu-based choice. A team prioritizing R&D investment across twenty potential features uses MaxDiff. A team setting list price for a new excavator line uses CBC with hierarchical Bayes estimation.

What Strong Industrial Choice Studies Have in Common

SIS International’s proprietary work across industrial categories, from heavy equipment tires to specialty chemicals to construction spreaders, indicates that choice studies which integrate qualitative depth interviews before the quantitative phase outperform survey-only designs in predicting actual share. The interviews surface the attributes the buyer cannot articulate on a survey, including the unwritten rules of supplier qualification and the role of the regional dealer in the final decision.

Three patterns recur in the studies that change leadership decisions.

The model is calibrated against actual transaction data where available. Holdout tasks and known-share validation are non-negotiable.

The simulator is delivered to the commercial team, not held by the research firm. The pricing director runs scenarios against named competitor moves on her own timeline.

The output is segmented by decision-maker role. The specifier in a Fortune 500 plant has a different utility curve than the corporate procurement officer signing the master agreement.

The SIS Approach to Choice Modeling

SIS International has run discrete choice studies across FMCG, automotive, industrial equipment, and financial services in 135+ countries. The work pairs B2B expert interviews and ethnographic research with quantitative choice experiments, then delivers a market simulator the client controls. The methodology is built for decisions, not for reports.

Choice Modeling Market Research, executed at this standard, gives a leadership team something rare: a quantified view of how price, feature, and brand decisions will move share before the decisions are made.

Über SIS International

SIS International bietet quantitative, qualitative und strategische Forschung an. Wir liefern Daten, Tools, Strategien, Berichte und Erkenntnisse zur Entscheidungsfindung. Wir führen auch Interviews, Umfragen, Fokusgruppen und andere Methoden und Ansätze der Marktforschung durch. Kontakt für Ihr nächstes Marktforschungsprojekt.