Used to be that you first had data. Then you did analysis to figure out the patterns and trends in it. Now you imagine the pattern and Google Correlate Draw checks if there is a search term that correlates to your pattern. This is awesome.
In case you can’t yet make out what the fuss is. Imagine how a person picks a dress to buy, they find a dress that fits them. Now reverse it, pick a dress and imagine finding a person who would fit it. See that!
Google Correlate Draw Examples
Note: the blue lines are what I drew and Google Correlate plots out matching data in red.
Sine wave-ish cycle
Correlate Draw’s approach brings out interesting possibilities. The basic idea of search using something other than text has been attempted before. For example i)Google Goggles, search for images or ii) Voice interface to search term entry or iii) Shazam, search for songs based on recorded snippet, all try to think of search as an activity that transcends looking for “textual” information.
But what is intriguing about Correlate Draw is its ability to search, or should we say match?, for patterns in quantitative data. And that too using an intuitive drawing interface. That twist of expressing a search query as a drawing is what makes this so interesting.
Imagine this. What if an research analyst in a financial firm ‘draws’ stock price movement patterns and have the system bring up companies whose stock price correlates with it? What if every time-series data could be searched in this manner?
There is also the UX aspect. The variation that can be expressed in a drawing can never be matched in a regular search interface. You could have textboxes to capture certain terms, sliders to express value within a range, a drop down to capture a single item out of a set and so on. But the expressiveness in a drawing would be hard to beat.
Anyway, those are my thoughts. What do you think about Correlate Draw? How far can you push this idea?