Google Labs, ever exploring the syntax and context of language, offers an algorithm it calls NGram, which maps the frequency of words or phrases in books published from 1800 to the present. I Ngrammed a few words to see what kind of trajectory the app would plot. Here are some of the results:
‘Happiness’ seems to have peaked in 1820. The next few years will determine whether it’s making a comeback, or continuing its downward trend. Relative to the results of other queries, this is a smooth curve, which suggests that we can only see the change in frequency over long periods of time. We don’t notice that ‘happiness’ is less frequent from one year to the next, but it is.
You can also plot multiple comma-separated words or phrases on an Ngram. In this graph, we see that ‘good’ (blue line) fluctuates over time, while ‘evil’ (red line) is constant. This suggests that if ‘good’ and ‘evil’ were investments (which in a way they are) good has more upside, while evil offers a low but predictable yield over time.
But then there’s this: ‘Virtue’ is the blue line; ‘Vice’ is the red. No doubt about what sells.
‘Improvisation’ shows a steady upward curve, with spikes up and down in the last 7 years. Based on the 200-year trajectory, we are due for an even bigger upward spike in the near future. Let’s ride that wave!
Here’s the Ngram link. Play with it! NGrams are useful for observing how ideas fluctuate over time in terms of their significance and meaning. When expressing your brand’s narrative, it is wiser to invest in trajectories than it is to take positions. What’s trending today on Twitter is a position. The events that led to the trend are its trajectory.
“Getting to yes” is a popular phrase among business managers. (It is the title of 
