Topic 1: Methods used for footfall counting in a shopping mall.
Shopping mall owners measure marketing effectiveness with footfall count in the shopping mall as it leads to sales from that shopping mall. Footfall count helps in:
- Identifying traffic patterns across hours, days, weeks, months, seasons, and even years from a single mall are critical in determining the commercial success of an shopping mall.
- Allowing the shopping center’s management to make the right decisions on how to allocate marketing budgets, as well as effectively plan staffing arrangements.
- Accurate assessment of the impact of special promotions.
- Calculation of commercial efficiency by comparing visits and sales.
- Optimization of infrastructure use.
- Comparison of the performance of different sites.
Method used for footfall counting: A people counter is a device used to measure the number of entrance per unit time. The correctness of the measurement is entirely dependent on the sophistication of the technology employed. The device is often used at the entrance of a building so that the total number of visitors can be recorded.
Different technologies used as people counters are:
Tally counter: A hand-held tally-counter would be used; one press per person. If the counter is press 1000 times by the attendant then the footfall counter will be considered as 1000.
Infrared beams: The simplest form of counter is a single, horizontal infrared beam across an entrance which is linked to a small LCD display unit at the side of the doorway or can also be linked to a PC or send data via wireless links and GPRS. Such a beam counts a ‘tick’ when the beam is broken, and the beam is broken when a person enters the mall.
Thermal imaging: Thermal imaging systems use array sensors which detect heat sources, rather than using cameras as in computer vision systems. These systems are typically implemented using embedded technology and are mounted overhead for high accuracy. Since thermal imaging systems detect the heat emitted by people, they can be susceptible to external weather conditions that reduce the amount of heat emitted from a person walking in from an outdoor environment.
All the people counter devices have to be properly placed at the main entrance of shopping mall so that footfall count is effectively measured.
Topic 2: Difference between ‘Observation’ and ‘Experiment’ research designs.
In observational studies, the researcher observes and systematically collects information, but does not try to change the people (or animals, or reagents) being observed.
In an experiment, by contrast, the researcher intervenes to change something (e.g., gives some patients a drug) and then observes what happens. In an observational study there is no intervention.
Examples of observational studies:
- A survey of drinking habits among students;
- A researcher who joins a biker gang to study their lifestyle (note, as long as the researcher does not try to change their behavior, it’s an observational study);
- Taking blood samples to measure blood alcohol levels during Monday morning lectures (yes, you are intervening to take the blood, but you are not trying to change the blood alcohol level: it’s just a measurement).
Examples of experiments:
- Making a law student drink beer to see whether lawyers argue better when drunk;
- Encouraging bikers in one group to stop smoking those funny-looking cigarettes to see whether they get less belligerent;
- Warning one group of students that you are going to take blood alcohol levels next Monday to test for alcohol, and comparing their levels to another group that you did not warn.
When do you do an observational study?
- When you merely want to collect descriptive information: “Is the incidence of diabetes rising?”
- When you want to report on the causes of a problem without disturbing the natural setting (I want to find out why students do not attend lectures)
- When you can’t do an experiment: “How fast does the earth move around the sun?”
- When it’s not acceptable to do an experiment: “How much does not wearing a condom increase the likelihood of HIV infection?”
Posted by: Sarvesh Singh_13PGP049.
Other Members of Group 2, Section A: Abhishek Kumar, Charan Kumar Karra, Naureen Fatima, Pavan Kumar Tatineni, Pittala Priyanka, Poulomi Paul and Ruchi Sao