Optimise Products

ImproveFit — Conjoint analysis

Knowing what customers value before you build lets you design products and services that genuinely fit the needs and expectations of your target segments. Customers can reliably indicate their preferences and trade-offs between product features and benefits — even for a product that doesn’t exist yet.

ImproveFit breaks products down into the features that matter most to customers, features that map directly onto production decisions. By analysing customer preference at this level, we can show you how demand for a product would shift if one or more of its features changed, before you commit to building it. Our approach combines conjoint-based preference and choice modelling with simulation-based optimisation.

Pioneers of conjoint analysis in Romania

Mercury Research ran the first conjoint study ever conducted on the Romanian market, in 1998. Ioan Simu published Romania’s first article on the method, Conjoint Analysis: quantitative method for preference modeling, in Revista de Cercetări Sociale (Year 6, No. 1–2, 1999, Bucharest, pp. 79–98).

Since then, we’ve completed more than 60 conjoint studies over the past 10 years across sectors including financial services, telecom, FMCG, and healthcare. Our team is trained to international standards, including the AMA Advanced School of Marketing Research’s Experimental Design for Conjoint and Discrete Choice Modelling, the Sawtooth Software Conjoint Analysis Seminar in Rotterdam, and Burke Institute’s Practical Multivariate Analysis programme in the US.

Read the original article: Conjoint Analysis — quantitative method for preference modeling

MarketFit — Simulated market test

Before committing to a full launch – or even a real-world market test – the most reliable way to estimate a new product’s potential is a simulated market test. It replicates the real market experience for the customer as closely as possible, without the full investment in production, distribution, advertising, and PR that a genuine launch requires. It won’t be perfectly realistic, but it’s the best available estimate of how the market will actually respond.

How it works

1. Communication exposure – Customers are exposed to the new product’s communication, to estimate its power to generate trial.
2. Product experience – Customers try the actual product, allowing us to estimate repurchase rates.
3. Representative sampling – The sample is designed so results can be extrapolated to the entire target market.
4. Sales forecasting – Combined with your marketing plan for the rollout, the research data yields a forecast of future sales.

Flexible design, matched to your needs

MarketFit designs range from simple central-location tests – presenting the concept and product for evaluation in a controlled setting – to fully realistic experimental designs using actual advertisements, real stores, real customers, and real money.

TrialFit — Product test

A brilliant product concept needs to become an equally brilliant actual product. Once the new product is ready, the question becomes whether real customer reactions live up to expectations — and whether it genuinely outperforms competition for the target segment.

TrialFit tests the new product and its main competitor as blind monadic tests, evaluated in a setting relevant to how the product is actually consumed. This design does three things at once:

• Isolates competitive advantage from brand — the blind element removes brand bias, so what’s being measured is the product itself.
• Enables reliable comparison — the monadic element allows direct benchmarking against the main competitor, as well as against previous or future tests.
• Reduces testing artefacts — the relevant consumption setting minimises distortion in how consumers react, keeping results closer to real-world behaviour.

The outcome is a clearer basis for deciding how to develop the product further — measured against performance expectations (action standards), the main competitor, and previously tested products that went on to launch successfully.

PriceSpan — Pricing studies

Pricing sits between two risks: price too low, and customers start questioning your product’s quality; price too high, and they start looking at competitors instead. PriceSpan helps you find the range in between — the price that works for both your customers and your business, for an existing brand or a new product.

Our pricing research ranges from identifying the optimum price range in a non-competitive context, using Van Westendorp methodology, to complex conjoint-based studies that simulate how your price would perform within a full competitive landscape.

PackDrive — Package test

Packaging is often the last thing a customer sees before deciding to buy — and the first thing that shapes their sense of a brand on shelf. PackDrive helps you understand what a new package design will actually do in the market before you commit to it.

With PackDrive, you can:

• Assess how a new package design affects purchasing intentions
• Get concrete insights on how to improve the design
• Identify the risk of current brand users migrating away after the change

Minimising bias, built into the method

To keep results close to real shopping behaviour, PackDrive is built around a shelf-test methodology, evaluates the package within real buying and consumption occasions, and tests it against its actual competitive context on shelf.

ExploreFit — Concept test

Most new products begin as a marketing idea, and the concept test is where that idea gets its first real evidence. We believe every company occupies a unique place in its market — there’s no universal benchmark a concept must clear. A concept scoring 30% on purchase intention might be a weak idea, or it might be a strong niche product. ExploreFit is built to tell you which.

Beyond the standard measures — attractiveness, originality, relevance, credibility, purchase intention — we give you a genuine sense of where and how your concept would actually fit in the market.

ExploreFit is designed to:

• Reveal the full potential of your idea, through a segmentation built around how customers respond to the new concept itself, a separate analysis of price that lets us simulate purchase intention at different price points, and clear insight into how well the concept’s benefits actually function.
• Give you the right measures to judge whether the launch is worth pursuing, based on norms calibrated to your company, your brands, and your market — not a generic industry standard.