How do we help?
We support in-house and agency based market researchers to ensure that results act as a reliable compass for plans, products and strategies. We ensure that the intelligence you use to guide decisions and advice is based on valid research that has been interpreted and reported accurately and impartially.
The value of any market research is underpinned by the rigour and validity of the sampling, interpretation, analysis and reporting of the data. It also depends heavily on the expertise you use to design questionnaires to eliminate bias. The summary below explains the main ways that we help you achieve more reliable and usable results from market research.
Marketing segmentation helps you understand the relevant characteristics and behaviours of discrete groups, whether they are customers, donors or products. This enables you to target each group with the most relevant messages or appealing offers, and avoid alienating people with irrelevant communications.
Whether you have ‘big data’ or just data, sophisticated market segmentation is essential for personalised marketing, customer retention strategies and for lifetime value analysis. Statistical methods produce accurate segmentation in the following ways:
- Identification of the variables that determine meaningful market segments (ones that really make a difference to customer behaviour).
- Robust analysis of the behaviour, preferences and motivations of different segments.
We will help you structure your surveys to achieve a result that can be relied upon. Our advice spans everything from questionnaire design and sample selection through to the analysis and interpretation of the results. We go beyond simple reporting to analyse, for example, who did or didn’t respond and assess whether this could bias the results. We can also advise you on the sample sizes needed to produce statistically significant results that you can rely on.
We are pioneering techniques to analyse social media posts that can help you understand what people really think about your business, organisation or product. The sample sizes are potentially huge and readily accessible, and the views expressed are the ‘unvarnished truth’ – not influenced by framing and bias that can sometimes affect formal surveys. Patterns in social posts can help identify emerging trends or warn of potential PR disasters.
We use statistical analytics and qualitative data analysis to help organisations turn verbatim comments – such as free text questionnaire responses – into useful data and actionable insights.
Know the return on investment from different marketing activities and you can spend a finite budget wisely. In the digital world, search engine marketing, social media and content marketing can operate alongside more traditional media.
Customer behaviour has always been difficult to predict with certainty and additional channels and marketing ‘touch points’ make understanding influences and behaviour even more challenging. A superficial analysis will yield simple and possibly misleading results.
We ensure that the statistical tools used to guide decisions are appropriate for the complexity of the task. Robust statistical methods ensure you draw accurate conclusions and target your budget appropriately. You also avoid the risk of discontinuing activities that have an important but less obvious influence in creating a sale.
We use a range of techniques including MaxDiff, Brand Mapping, Key Driver Analysis and CHAID to provide deeper insights into consumer preferences, behaviour and loyalty.
We help manufacturers and distributors ask the right questions in the right way. You get a result you can understand, use and rely on. For example, MaxDiff analysis is used to rank product features in terms of their importance to customers on a common scale. Comparisons and trade-offs between them can then be made.
Techniques such as brand mapping can be applied to individual products and well as brands. This method visualises how brands or products are perceived compared to competitors by plotting a two dimensional chart of ratings against two related parameters such as cost/value, value/market share or cost/distinctiveness. Data reduction techniques can aggregate multiple reference points or features so that complex datasets can be visualised, understood and acted upon.