Google Insight for Search ad randomly popped up on top of my gmail inbox. In a quest of searching for a good post for Teckitech, i clicked on it and found it quite amazing and much similar to Wolfram Alpha.
A result from Google Insight for Search usually contains:
- a graph with the search volume, indicating interest over time for your terms, plotted on a scale from 0 to 100; the totals are indicated next to bars by the search terms (read more about how we scale and normalize the data)
- a breakdown of how the categories are classified
- lists of the top searches and top rising searches
- a world heat map graphically displaying the search volume index with defined regions, cities, and metros
It is also said to “analyzes a portion of worldwide Google web searches from all Google domains to compute how many searches have been done for the terms you’ve entered, relative to the total number of searches done on Google over time. You can choose to see data for select Google properties, including Web search, Image search, Product search, and News search (certain properties aren’t currently available in all countries/territories).”
And the data seems to be updated once a day with the previous day’s information. However, rarely “there may be slightly longer delays between updates”.
The data from Google Insight for Search can be used freely but it is adviced you review their Terms of Service. If you choose to use the information you found, it is advised to appropriately attribute it to Google.
Some examples of using this service are:
Choosing advertising messages:
Insights can help you determine which messages resonate best. For example, an automobile manufacturer may be unsure of whether it should highlight fuel efficiency, safety, or engine performance to market a new car model.
When the three features are entered into Insights, we can see that there’s a considerable amount of interest in car safety. With this information, the manufacturer may want to consider incorporating car safety into its marketing strategy.
Insights can be used to determine seasonality. For example, a ski resort may want to find out when people search for ski-related terms most often.
In this example, the same time frame (June through May) is being compared across several years.
The results are fairly consistent throughout the years: interest picks up in August and peaks in December and January. With this information, the ski resort can anticipate demand and make informed decisions about the appropriate allocation of everything from its advertising budget to staffing to resort resources.
Creating brand associations
Insights can be a helpful tool in creating brand associations. Take, for example, an advertising agency that needs to build a compelling advertising campaign for its client, a computer hardware company. The agency needs to know what competing brands are doing: how should they position their client’s product against them?
When comparing laptops or notebook, it’s useful to apply the Category filter, whereby the data will be narrowed down to just Computers & Electronics.
Carefully examining the resulting top related searches and the rising searches can help the agency better understand competitors’ offers, thereby creating a campaign to differentiate their client’s brand.
See some more examples and updated information.
Tell us what you think of this application. How are you planning to use this application?