Find the relationship between your brand and brand attributes
Correspondence analysis is a statistical technique used to analyse and visualise associations between categorical variables. Traditional crosstabs are useful, but it can be difficult to observe meaningful insights or patterns, especially where you have a lot of data. Correspondence analysis employs advanced mathematical techniques to simplify and condense complex data into an easy to interpret visual representation.
At Lonergan Research we provide expert interpretation and insights to help you discover meaningful patterns.
HOW CORRESPONDENCE ANALYSIS WORKS
Our correspondence analysis methodology:
- Data Collection: We collect categorical survey data and organise it into crosstabs, or other suitable formats.
- Correspondence Analysis: Technically, we create a chi-squared matrix by computing the residual difference between the data and expected values. Using a mathematical technique called singular value decomposition, we can plot the data on a single ‘correspondence map’, where items that are closely associated are near each other, and items which are not closely associated are further apart.
- Interpretation & Insights: Correspondence maps are really effective at summarising the data, providing a high level overview of the associations between variables. Interpretation can sometimes be tricky, and it is not always suitable where relationships between variables are complex and nuanced. We provide expert interpretation and insights to help you discover meaningful patterns.
- Brand and product positioning: Identify associations between brand or product attributes with customer perceptions.
- Market and customer segmentation: Identify market or customer segments based on categorical variables such as preferences or purchase behaviour.
- Customer satisfaction: Uncover hidden factors in survey responses that contribute to customer satisfaction or dissatisfaction.
Need expert help? Contact Lonergan Research