Our research studies give our clients the evidence to make important decisions with confidence and certainty. On your behalf, we seek to understand the facts of the marketplace, overcoming the bias of speculation. Our work provides management with the data and clarity to act and the courage to stay the course.
Quantitative Methodologies
Customer Satisfaction Modelling
Satisfaction modelling is a quantitative technique we use to measure the operational performance of an organisation according to its customers, with a hierarchy of importance to help management understand what is ‘driving’ satisfaction in the business and target specific areas for improvement.
Stated importance (asking customers what they value most) is an inaccurate predictor of actual behaviour. We employ inferred importance using multiple linear regression to accurately assess the impact of each performance area on overall satisfaction.
Customer satisfaction is typically tracked over time to monitor risks to the business, such as customer defection, and to measure the effectiveness of strategy initiatives.
Choice Modelling
Choice modelling is a quantitative technique we use to understand the value individuals place on various product attributes when they make purchase decisions. By evaluating difficult trade-offs, choice modelling allows us to learn which attributes individuals most value.
Choice modelling can be used:
• To understand customer preferences
• To estimate product demand
• When designing a new product line
Segmentation
• Deep customer insights
• Campaign structuring and tracking
Segmentation identifies the groups of consumers with similar needs that exist within the overall market.
One of the most actionable segmentation solutions is linked to demographic or other criteria that allows an organisation to target each segment separately.
Our segmentation research will identify the existence of each segment, and the difference in needs between the segments.
Business Outcomes [Propensity Modelling]
Business Outcomes are those measures of behaviour that an organisation ultimately wishes to influence through changing internal performance levels. Forethought has worked extensively with clients across a number of industries to examine internal performance measures with respect to the externally identified drivers of business outcomes such as retention and contestable loyalty.
Forethought focuses on the measurement of customer satisfaction and the linkages between satisfaction and business outcomes. In analysis to date, very strong relationships between a customer satisfaction and customer retention have been found. Effective internal measures can be used to monitor performance on these key drivers and to predict defection.
InMate®
InMate® is a predictive defection modelling methodology used to identify and understand drivers of defection.
The methodology uses a suite of research and analysis techniques:
• Data modelling to identify the drivers of churn;
• Draws upon both primary research data and client-held data; and
• Derives the hierarchy of importance of the defection drivers.
It is designed to detect those customers who are at risk of defecting and therefore provide an opportunity to avert this. At its most fundamental level, InMate® presents a two-pronged attack on understanding defection. This approach uses both professed and inferred reasoning in drawing conclusions to provide convergent validity.
InMate® is able to identify those customers who are staging or planning their departure giving an accurate representation of the true size of the problem. From this, the cost of defection can be extrapolated allowing our clients to accurately estimate the cost of lost customers in forgone revenue.