Traditionally, quantitative research is used in the back end of the marketing process to guide final decision making. Typically, it uses large-scale numbers that give businesses confidence in making investment decisions. But quantitative research is a relevant marketing tool throughout the entirety of the product development cycle, not just to validate.
Having significant numbers at your disposal builds confidence along the way and allows for an early reformulation of decisions that can save businesses thousands of dollars. This then means that the new product is more likely to be commercially viable (or least mitigate early fails).
Product development should make use of a variety of quantitative methods from conception to validation to ensure a successful product launch. Here are the key benefits of a quantitative pathway to success:
- Uncover a consensus on product attribute preferences and hierarchy, that will drive purchase likelihood for both current and potential customer
- You may have stumbled upon a fantastic new product to bring new customers to your brand, but will it alienate or cannibalize current customers?
- Quantitative research allows testing of different product attributes to gauge the reaction from both current and potential customers and build strategic outcomes for launch decisions, product specifications and even packaging and communications briefs.
- Identify evidence regarding cause and effect relationships between factors relevant to the product and purchase behavior
- Quantitative research can establish just how significant changes in attributes can affect purchase intent.
- At the most basic level, simple questioning can provide ratings on basic metrics. At a more complex level, statistical models can identify the trade-offs that take place when you adjust various product attributes.
- Test specific hypotheses about the product
- Hypotheses both large and small can be tested against hard numerical data to guide decision making.
- Smaller hypotheses can be tested with lean and agile quantitative research methodologies to get answers quickly and efficiently.
- Larger and more strategic hypotheses warrant a scaled-up approach with more complex techniques and well-crafted questionnaires.
- Identify and size market segments
- Breakdown your target market into manageable chunks through segmentation. Different customers may respond differently to new products or changes in current products, they may buy your products for completely different reasons.
- Combine primary quantitative research with your own sales data to further enhance the effectiveness of your segmentation, making findings more actionable. Quantitative research will help you be able to describe the characteristics of all relevant customer segments to internal and external stakeholders.
- Project results to a larger population of customers
- One of the primary principals behind quantitative research is sampling. The goal with sampling is to best define a target market, randomly select members of that target to act as respondents, and then use the results to make assumptions and conclusions about the target.
- If you combine this with third party population data, you can create reliable projections on just how many people feel a certain way towards your brand or product.
- Provides a recommendation for a robust launch decision
- It’s likely through the development process that you will arrive at 3 to 5 different versions of a new product, and you just cannot decide which one you should launch, and rightly so. It is unwise to decide purely off the opinions and anecdotal evidence put forward by you and your team.
- Quantitative research helps by taking the choice out of your hands, by sizing the response to each version and using results to project the success when launched to the broader population.
Dipesh is fascinated by how and why people make the decisions they do. We all have our quirks when it comes to consumer decision making and he enjoys the challenge of finding out what these are. Dipesh has over 10 years experience in market research, having worked for both large and boutique agencies. His quantitative experience has seen him work across a number of methodologies, including brand fundamentals of tracking and U&As; consumer choice in the shape of conjoints and MaxDiffs; audience pieces such as segmentations; and NPD concept testing.
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