Telmar's TNT+ data-mining programme has other two tools in its arsenal which can help you glean insight from the figures you unearth from a data-run - positioning maps, and correspondence maps.
A positioning map, or P-Map, plots data items onto an X/Y axis graph, putting your run into a visual form. A P-Map is especially useful for presenting data to clients in a very understandable format.
Typically, two columns of variables are selected to be used as the X and Y axes of the graph. The P-Map function then plots the values - the bigger the plotted circle, the larger the variable's audience. For instance, in the P-Map below, the bigger circles are magazine titles which deliver greater numbers of the specified target market.
This P-Map plots the age of magazine readers (on the vertical) versus their gender (on the horizontal). Magazines listed in the top right quadrant appeal to younger women. Titles such as Jet Club, Bona and True Love are shown to clearly dominate this market, while Glamour is the most suitable for young women.
Conversely, the bottom-left quadrant would be titles which appeal to older males. Titles which fall close to the quadrant axes have a broader appeal, such as Dish/Skottel which appeals to slightly older men and women, compared to Your Baby which is very securely located towards the female side of this P-Map.
On the age axis, NAG is the youngest title, The Gardener is the ‘oldest', and Marie Claire is somewhere in the middle.
You can create a P-Map with any two sets of variables - men aged 16 - 24 and their sporting preferences, or your target market split between the X-axis and Y-axis with radio stations, print media or brands as variables to be plotted.
A correspondence map, alternatively, takes you a step beyond the demographics. It is a statistical analysis tool which is used to understand a market or brand, and can be particularly valuable when trying to identify potential market gaps.
It calculates the most discriminating factors about your market or brand, helping you identify what makes your target market different to another brand's. Consider two men, both 24-years-old, both in LSM 6, but one drives a Toyota and the other Ford. By doing a correspondence map using variables such as SAARF Lifestyles or SAARF Attitudes, you would get a better understanding of how these men differed, over and above the demographics. For instance, why they decided to buy the different brands.
The correspondence map below shows several commercial radio stations and the activities in which their listeners participate, according to AMPS 2008AB. 5FM and 94.7 Highveld Stereo's listeners are equally likely to buy a video or computer game, but 5FM's listeners like clubbing and going to dinner parties, while beauty treatments come out more prominently with Highveld's listeners.
One word of caution though: remember that you're looking at a 2D picture of something which in reality has multiple dimensions. You must look at the stats behind the correspondence map to back up what you're seeing.
For example, in the graph below, “attending funerals” could be as important to SAfm's listeners as it is to Jacaranda 94.2's, but because Jacaranda's greater influence compared to SAfm (it has a more distinctive profile when defined by these variables), the station exerts more pull over this variable, rather like the greater gravitational pull of large bodies in outer space.
To create a positioning or correspondence map, first set up your TNT+ run and then crosstab the data. Go to the File menu and click on “Correspondence Analysis” or “P-MAPS” and the programme will do the rest.
