Robyn Ordman is relatively new to the Market Research scene, joining the team at D&M Research in May last year. Though Robyn intended to pursue her PhD following an undergraduate degree in psychology and Masters of Research, she was itching to gain some real-life work experience.
Being able to play with tangible data and seeing immediate and implementable outcomes has remained thrilling for someone who has always been a knowledge-seeker. Her key roles at the company include assisting in the delivery of insights, and she is also building her repertoire of statistical analysis by exploring market research-specific software such as Q. Demonstrating a strong ability for interpreting data and reporting key findings in a succinct and intelligent fashion, Robyn remains motivated by the supportive and creative team that surrounds her.
Having a sense of humour of the ‘dad joke’ variety has helped her fit right in with the D&M crew, and she looks forward to continuing her journey in Market Research alongside them. Outside of the office, like a true Bondi girl, she loves to hang around the beach, eat good food, and laugh with friends and family.
We are all aware of the criticisms that surround the Net Promoter Score (NPS), yet it still remains a widely utilised measure across almost every industry. Though many studies have questioned the validity of NPS as a tool for predicting business growth, few have actually crossed the segments (Promoter, Passive and Detractor) by verbatim sentiment. Prior dealings with clients across multiple industries have demonstrated that although Promoters typically say positive things, Passives and Detractors do not cite mainly neutral and negative reasons as expected. In fact, a large proportion of Passives have only positive things to say, while the majority of Detractors cite neutral reasoning.
We aim to replicate these findings in the financial services, with the survey focusing on participant’s main bank. We will also collect how many actual recommendations participants have given in the past 12 months, and correlate that against the NPS scale. We expect that the average number of recommendations given by Passives will not be significantly lower than the average for Promoters. Finally, we will perform a cluster analysis across all gathered metrics (NPS, verbatim sentiment, and actual number of recommendations in the past 12 months) to help generate an optimised segmentation for the metric.