Crowd Analysis- Can you Notice a Pattern?
‘Crowd Analysis’ — Does that word ring a bell? Let’s take a moment reminding all analytical tools like Google Analytics, Moz Analytics, Pinterest Analytics, Twitter Analytics, and the gamut of data that these tools analyze in day-to-day lives.
Being a marketer myself, I and my team understand the importance of Analytics. It is significant to use a wide selection of valuable analytics reports regularly to determine the successes and failures of your online campaigns. This analytics can help you so much? For analytics person, it’s a victory to collect and provide valuable analytics reports. Let’s drown down more about Crowd Analysis.
Crowd Analysis- Deep Diving into the Concept!
The practice of interpreting data on the predictable or natural movement of objects/groups is basically crowd analysis. The subjects of these crowd tracking analyses i.e. masses of bodies (particularly humans) that include how a particular crowd moves and when a movement pattern alters.
Basically the data is used to predict future crowd movement, crowd density, and plant responses to potential events such as those that require evacuation routes. Crowd analysis’ applications can range from video game crowd simulation to security and surveillance.
Crowd density indicates the number of objects/people per unit area whereas Crowd flow involves the speed that objects in a crowd move in space. Significantly, analyzing density and flow for the management and optimization of the crowd and to predict their movement patterns. At a decisive capacity, flow begins to reduce as crowd density increases.
Insights from People
As living in the era of Big Data, we can surely say that the amount of data available is colossal and mind-boggling. Perhaps, not all data is useful. Technically, we only use the data that is interesting and of use to us.
There is an acute risk of this useless data inundating the senses of those looking for critical information on the internet. Let’s look at the real, physical world. As it is online, it can now be just as easy to collect information here and crowd analytics is all about this only. Collecting, aggregating, and finding uses for the information that relates to people going about their daily lives.
Crucial for Marketers?
Marketers can directly use this technology in the field. What can you do to ensure your marketing performs more efficiently? First things first, test your ads by observing how particular demographics react to your advertising. Are you getting enough exposure to the correct demographic groups? Do members of all groups are responsive (stopping and taking notice) in your display? It is easy to track engagement on digital signage or even just window displays.
For more effective results, one should tie in the data you accumulate from video analytics software with other data that you collect. Similarly, you could combine the data collected from your displays with other factors such as the weather, to determine the best, most profitable, time, and place to undertake particular campaigns.
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Real-World Case of Crowd Analysis
Let’s talk about Crowd Artificial Intelligence, Sociology, and Simulations.
Have you heard about swarm intelligence? It is the analysis and application of crowd movement that can contribute to the modelling of group behavior. Basically, it is based on biological and artificial models of people. Social instinct behavior is applied to complex systems that model multiple agents and their interactions.
The accuracy and relevance to real-life situations are clear as crowd simulations are based on group dynamics and crowd psychology. Before a system can simulate how the simulated moving objects, or agents, will interact with each other and with the environment, it generates a realistic crowd simulation with the given input. The goal is to replicate a crowd’s movement patterns given a large number of agents in a given space.
We are in an epoch when there is a treasure of data available. Undoubtedly it is important to refine data to make it information, so it is of utility. In the real world, until now it has been much harder to evaluate objectively data than it has been online. Technology has finally caught up with demand here.