There are lots of business implications of the forecast data:
Having predictable trends for a search query or for a group of queries could have interesting ramifications. One could forecast the trends into the future, and use it as a “best guess” for various business decisions such as budget planning, marketing campaigns and resource allocations. One could identify deviation from such forecasting and identify new factors that are influencing the search volume as demonstrated in Flu Trends.
Some business categories are more predictable than other categories
- Over half of the most popular Google search queries are predictable in a 12 month ahead forecast, with a mean absolute prediction error of about 12%.
- Nearly half of the most popular queries are not predictable (with respect to the model we have used).
- Some categories have particularly high fraction of predictable queries; for instance, Health (74%), Food & Drink (67%) and Travel (65%).
- Some categories have particularly low fraction of predictable queries; for instance, Entertainment (35%) and Social Networks & Online Communities (27%).
- The trends of aggregated queries per categories are much more predictable: 88% of the aggregated category search trends of over 600 categories in Insights for Search are predictable, with a mean absolute prediction error of of less than 6%.
If you were to launch a brand new business from scratch it might make sense to target a less predictable category since it would be more open to new market entrants & they would not appear on the radar of competitors as quickly.
And Google now make their Insights for Search charts embeddable in third party websites via iframes. 🙂 Given that, I just added those data points to our keyword tool below the keyword data our tool returns, which is like having an instant second opinion on the keywords.
This allows you to instantly estimate the seasonality of a particular keyword. And if our search volume seems somewhat inflated and/or you are uncertain if it is accurate then you can look at the search volume graph for more data. If the keywords graph is quite spiky for a non-seasonal keyword (or if it has no data returned) then there is a good chance that there is a bit of noise in the data.
More: continued here