Trend data is any collection of information that can be quantified in ways that allow trend analysis. If a phenomenon is happening and the facts about that phenomena are changing, then it is important to measure the change, then use the measurements, along with other factors, tostate the probability that future change will go in a certain direction.
The raw material for such work is data. Data comes in many forms, with new forms coming every time a new system for collecting data is implemented. When the grocery store’s “customer convenience card” is swiped during the checkout process, trend data is being collected about everything that the customer buys and does. This way the stores will have data that tells not only whatis going on over time with each customer who buys a product, but what is going on over time for all customers who buy all products.
This is how the store is also able to predict when customers will be wanting cash with their transaction, are using more debit than credit cards. The predictions ask the basic questions: which products will customers prefer to buy, and in what quantity or size? How much cash should we order from the bank and on which days should we have extra cash? Will the next sale on one item result in more sales of other items?
The trend graph is the simplest graph to make and to understand, yet it yields tons of information. The vertical bar represents quantityand the horizontal bar represents the passage or increment of time. A single dot represents how much of something occurred duringa given minute, hour, day, week or so on. When lines are drawn to connect the dots, peaks and valleys will show up.
The trend graph is used as a visual representation of changes in activity, such as website visits, purchases, usage, consumption, desire, interest or any behavior that is being quantified. The length of time that a person spends on a site, the number of people who visit a person’s blog, the number of views for a YouTubevideo, or the preference for one product over another can be measured over time.
And thus, we have trends!
But more is needed. The next step is to find out why the changes occurred, or to see if a predicted change went as expected. In most cases, something was done with the expectation that it would cause the change in behavior or action: There was a sale, a new and flashy ad, or there was a news report that put a person or topic in the public spotlight.
In many cases, something goes viral simply because of word of mouth popularity, followed by media reports and aggregator placement that is based on the popularity. This happens with amateur YouTube videos that are published with no advertising or publicity, whatsoever.
Viral trends and the related data: the number of views, number of repeat views, length of time that the visitor is involved, and what the visitor says, for example, are vastly important to advertisers, members, site management and business because they are unpredictable, volatile and powerful social movements that can have major impacts on sales, demand, and advertising.
The corporations do not have any control over viral complaints about their services and products as the customers see the issues. Conversely, product demand can go sky high overnight due to a positive viral trend in a social networking forum or a video that demonstrates the product. This can cause sudden surpluses of rejected products or sudden shortages in products that have high demand.
After the quantified (or numeric) data is collected and the trends are seen, there is a need to identify cause and effect. There are the predicted effects of well planned and orchestrated events, such as ad campaigns or protests. There are unpredicted effects that show up when it is difficult to find the cause. There are weak results that come from the most powerful attempts to get the results. There are strong effects that come from the weakest of causes, as with the amateur YouTube videos.
Trend data collection and analysis allows some amount of prediction that is based on past events. This leads to ideas about the probability of future events. And more often than not, savvy trend data collection and analysis involves a lot of money that comes from a lot of individuals and is gained or lost by a lot of businesses.