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Pricing Research

Set prices that maximize revenue and market share. Meraki Research delivers pricing research grounded in buyer behaviour and willingness-to-pay data.

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Pricing is the most powerful marketing lever most companies underutilize. A product can be perfectly designed, brilliantly marketed, and widely distributed, and still underperform because the price is wrong. Set it too high and you suppress demand. Set it too low and you leave money on the table, or worse, signal inferior quality. The challenge is that most organizations set prices based on costs, competitive parity, or gut instinct rather than rigorous pricing research that reveals what customers actually value and what they are willing to pay.

Meraki Research provides comprehensive pricing research services that give companies the empirical foundation to make confident pricing decisions. We deploy a full range of proven techniques, from direct price sensitivity measurement to sophisticated choice-based approaches, selected and tailored to match the specific pricing questions your business faces. Our work covers new product launches, existing product repricing, portfolio optimisation, and competitive pricing strategy across both consumer and B2B markets.

Our pricing research practise is led by analysts with deep expertise in the statistical and behavioral dimensions of pricing. We understand that pricing decisions do not happen in isolation. They interact with brand perception, competitive positioning, channel strategy, and market share objectives. Every research engagement we design accounts for these interdependencies, so the results we deliver are not just technically sound but strategically relevant.

Our Approach: The Meraki Price Optimization Framework

There is no single "best" pricing technique. The right methodology depends on what you are pricing, the competitive context, the decision stage, and the level of precision you need. Our Price Optimization Framework matches the right analysis approach to your specific situation.

Phase 1: Pricing Problem Diagnosis

Before we recommend a methodology, we need to understand the business problem. Are you launching a new product and need to identify the optimal price point? Are you managing a portfolio and need to understand how price changes on one item affect demand for others? Are you defending market share against a low-price competitor? Do you need to understand the price elasticity of your entire category? The diagnostic conversation defines the scope, identifies the key questions, and determines which technique or combination of techniques will produce the most useful results.

Phase 2: Methodology Selection & Research Design

With the problem defined, we select the right approach. Our toolkit includes:

We frequently combine methods, for example, using Van Westendorp to narrow the range and then conjoint analysis to optimise within it. The research design also includes sampling strategy, Respondent qualification criteria, and questionnaire development.

Phase 3: Data Collection & Quality Assurance

Pricing research is only as good as the data behind it. We recruit Respondents who match your actual buyer profile, not convenience samples. For B2B pricing studies, this often means recruiting specific decision-makers within target organizations. Surveys are designed to present pricing questions in realistic contexts that mirror actual purchase decisions, avoiding the hypothetical bias that undermines many pricing studies. Every response goes through rigorous quality validation before analysis.

Phase 4: Analysis, Modeling & Price Optimization

This is where the Intersection of data and strategy produces actionable guidance. Depending on the methodology, our analysis may include utility modelling, demand curves, revenue optimisation simulations, market share forecasting under different pricing scenarios, and sensitivity analysis that shows how results change across Respondent segments. We do not hand you a single "optimal price" without context. We deliver a clear picture of the trade-offs across a range of price points, so you can make decisions that align with your broader business strategy.

Phase 5: Strategic Pricing Recommendations

Our final deliverable is not a research report. It is a pricing strategy recommendation backed by data. We present findings in terms your leadership team can act on: recommended price points, expected volume and revenue impact, competitive implications, and risk scenarios. We also identify pricing opportunities by segment, because the right price often differs meaningfully across customer groups. This is where our pricing research connects to market segmentation work, ensuring your pricing strategy reflects the different value perceptions within your market.

When Pricing Research Is the Right Investment

Pricing research delivers clear returns in specific situations:

  • New product launches where you have no transaction data to guide pricing and the consequences of getting it wrong are significant.
  • Price increases or decreases where you need to predict volume impact before committing to a change.
  • Portfolio pricing where you need to understand cannibalization risk and cross-price elasticity across your product line.
  • Competitive pricing pressure where you need data to determine whether matching a competitor's price move is necessary or whether your value proposition supports a premium.
  • Entering new markets where price expectations may differ from your existing markets.

Pricing research is less valuable when the market is purely commodity-driven with fully transparent pricing, or when the purchase decision is entirely dictated by procurement processes that override buyer preferences. In those cases, competitive pricing intelligence and cost analysis may be more practical starting points. We will tell you honestly if a full pricing study is not the right investment for your situation.

What We Deliver

Every pricing research engagement produces a specific set of outputs:

  • Price sensitivity analysis showing acceptable price ranges, optimal price points, and the boundaries where demand drops sharply.
  • Demand and revenue curves that forecast unit volume and total revenue at each tested price point, with confidence intervals.
  • Market share simulations modelling how your share changes under different competitive pricing scenarios.
  • Segment-level pricing insight revealing how different customer groups value your product differently and respond to different price points, often connected to broader segmentation research.
  • Executive pricing strategy presentation with clear recommendations, supporting data, risk scenarios, and implementation guidance.

Timelines vary by methodology. A Van Westendorp or Gabor-Granger study can be completed in three to four weeks. A full conjoint-based pricing study typically requires five to eight weeks from design through final delivery.

Industry Applications

Consumer Packaged Goods Optimize shelf pricing across SKUs, pack sizes, and channels. Understand how price gaps between your brand and private label alternatives affect market share.

Technology & SaaS Determine pricing tiers, feature bundling, and upgrade price points that maximize customer lifetime value without suppressing adoption.

Healthcare & Pharmaceuticals Establish pricing for new therapies, medical devices, or health services that reflects perceived value, competitive alternatives, and payer constraints.

Financial Services Test fee structures, interest rate sensitivity, and the perceived value of premium service tiers for banking, insurance, and investment products.

Retail & E-Commerce Optimize pricing strategies across categories, understand promotional price sensitivity, and model the revenue impact of everyday-low-price versus high-low pricing approaches.

Manufacturing & Industrial Quantify the value of technical specifications, quality certifications, and service bundles to support value-based pricing in complex B2B selling environments.

Frequently asked questions

Conjoint analysis is the most sophisticated approach because it measures how customers trade off price against multiple product attributes simultaneously. Simpler techniques like Van Westendorp or Gabor-Granger measure price sensitivity directly but do not capture the interaction between price and features. The best choice depends on your questions. If you just need to know the acceptable price range for an established product, a simpler method works well. If you need to optimise price alongside feature configuration, brand positioning, or competitive alternatives, conjoint is the stronger option.

This is one of pricing research's most common applications. We present new product concepts at different price points using realistic descriptions, visual stimuli, or prototypes. The key is creating enough context for Respondents to make meaningful value judgments. For highly innovative products where buyers have no reference price, we use techniques like MaxDiff to understand which features drive the most value, then layer pricing questions on top. The results are not as precise as testing an established product, but they are far more reliable than guessing.

Yes. Discrete choice modelling and competitive simulations allow us to model scenarios where competitors react to your pricing moves. For example, we can estimate your market share if you raise prices by 10% and your primary competitor holds steady, versus if they match your increase, versus if they cut prices in response. These scenario models are not crystal balls, but they give you a structured framework for anticipating competitive dynamics rather than reacting to them.

Sample size depends on the methodology and the number of segments you need to analyse. A basic Van Westendorp study may require as few as 200-300 Respondents. A full conjoint analysis with multiple segments typically needs 400-1,000+ completed surveys. For B2B pricing studies, where the population of qualified buyers is smaller, we may work with 100-200 Respondents but use more observations per person. We always design sample plans that balance statistical reliability with practical constraints and budget.

This is a fundamental challenge in pricing research, and it is why methodology selection matters so much. Direct questions like "how much would you pay?" tend to produce downward-biased answers. Our preferred techniques avoid this problem by embedding price in realistic choice contexts. In conjoint analysis, for example, Respondents choose between complete product profiles that include price as one variable among several. They cannot simply optimise for the lowest price without giving up features they value. This mirrors real-world buying decisions and produces results that are far more predictive of actual behaviour.

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