A discussion of advanced generation analytical methods for the measurement of change in consumer relationships

This paper discusses some emerging analysis techniques out of the social and medical sciences and pertain to the measurement of change over time. Some of the older techniques of measuring shifts in attitudes and behaviours are selectively reviewed. The goal of this paper is to outline some newer techniques from the structural equation modeling and dyadic analysis domains. Attention is given to the possible application of Latent Growth Modeling (LGM) and Multilevel Modeling (MLM). These complementary techniques are examined with regards to their ability to assist in tracking consumer-brand relationship growth. Some disadvantages of these newer techniques are outlined. Some more advanced method variants are then considered and it is concluded that they offer some real advantages that analysts should utilise.