Research methods: Statistical Analysis
Our specialist in-house research team is able to conduct advanced statistical analysis. Whether this is to cluster your audience into distinct segments, to uncover the key drivers for product recommendation, brand perceptions or purchasing habits, or to simply explore brand reach.
We are experienced in analysing data beyond standard data tables, using advanced statistical techniques and machine learning methodologies to unearth hidden insight to help drive key business decisions.
We offer brand mapping using correspondence analysis to uncover how your brand is perceived in the market place. How strongly is your brand associated with the key features / traits that compose your market? Is your brand distinguished from competitors or does it fall into a highly competitive brand space? And how can your brand strategy be altered to gain competitive advantage? These are some of the insights that brand maps provide and as the results are plotted in two dimensions the output is clear and intuitive to interpret.
Brand maps can be broken down via any sub-population of interest, allowing you to visualise differences in brand perception between, for example, your core consumers and the wider market or a range of other metrics. As well as this brand zones can be identified where features and brands cluster forming distinct market areas, this can uncover latent areas and opportunity where particular areas of the market are under-serviced or where few brands operate.
Total Unduplicated Reach and Frequency (TURF) is a technique used to understand the optimal combination of products to reach the greatest proportion of the market possible, given a defined number of products to enter the marketplace.
Why use TURF?
TURF can be used to capture a new audience which your product line may not currently reach, to help decide which products to develop and bring to market, as well as to understand the impact when adding a new product to a current line and to help make use of a limited budget or shelf-space in order to maximise sales and improve audience reach.
Why use DRG?
We implement both forms of TURF in our analysis; the ‘Greedy method’ and the ‘Enumeration method’ to find the optimal solution, but also to observe the tipping point where market reach plateaus.
Gabor-Granger Pricing Method
The Gabor-Granger pricing method measures the willingness of consumers to pay for your product at a set range of price points (otherwise known as the price elasticity). This technique provides insight into consumer price tolerance and helps to inform which price point will optimise market reach.
A plot of the ‘price elasticity of demand’ is shown below, this shows the proportion of consumers that would consider purchasing a product at each given price point.
Price points are kept equally spaced and are designed to capture a realistic price range – focusing on adapting pricing rather than re-inventing a price strategy. A more price sensitive market is defined by a steeper demand curve, whereby with increasing price – demand decreases more sharply.
Predicted revenue vs price charts are also useful to visualise the effect of price on predicted revenue, meaning optimal price points can be uncovered to maximise business revenue.
Want to know more? Submit an enquiry using the form or call us on 01434 611160 and a member of the team will be in touch.
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