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Summary:

Ever wanted to see a graph of how much email you’ve received from particular person, or about a particular topic, over time? Graph Your Inbox is a Chrome extension that plots the results of Gmail search queries. It’s like having Google Analytics for your inbox.

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Ever wanted to see a graph of how much email you’ve received from particular person, or about a particular topic, over time? Graph Your Inbox is a Chrome extension that plots the results of Gmail search queries. It’s a bit like having Google Analytics for your inbox, showing the number of conversations that match a particular result for all time (month and year), by the days of the current month, and per year.

While it’s fun using it to plot things like the emails your Mom has sent you, as I played with Graph Your Inbox, it became apparent it could actually be quite a useful tool; you can use it to discover insights you may not previously have had. It’s especially useful being able to plot the results of more than one query on your chart, so you can see, for example, Twitter “follows” versus notifications of comments on your blog to see if there’s a correlation. You can plot the results of any Gmail search query, so you can use powerful operators like label:, has: attachment, from: and to: in your searches. If your results reveal a particular datapoint that’s interesting (a huge spike in your chart, for example), you can click on it to bring up a preview of all of those conversations to dig a little deeper.

Possible Uses

Here are some possible uses for Graph Your Inbox (your mileage will obviously vary, depending on how you use your email, what services you use and whether you receive email notifications of various actions):

  • Facebook friend requests versus LinkedIn connection requests. Chart your progress at growing your networks on these social services by measuring the number of connection requests you receive over time. Example queries:
    • "wants to be friends" from:facebook
    • "join my network" from:linkedin
  • Twitter “follows” versus comments on your blog. As I mentioned above, you could plot these to see if there was a correlation between activity on your blog and the number of people who are interested in following you on Twitter. Example queries:
    • following from:twitter
    • "new comment" from:wordpress
  • Mentions of a particular work project versus flight purchases. Do certain projects generate more travel than others? You could either chart specific mentions of a project name, or if you used a label, you could look for conversation tagged with that label. Example queries:
    • from:virgin "booking confirmation"
    • label:web-site-redesign
  • Mentions of particular clients to see if there’s a seasonal trend. If activity around some clients is higher at certain times, perhaps you can prepare for, and capitalize on, that period. Example query:
    • "Client X"
  • Mentions of particular client versus email from a particular person. Similarly, it might be interesting to see if an increase in the number of emails from an individual results in an increase in mentions of a particular client. Example queries:
    • "Client X"
    • from:someone@example.com
  • Twitter “follows” versus comments on your blog. As I mentioned above, you could plot these to see if there was a correlation between activity on your blog and the number of people who are interested in following you on Twitter. Example queries:
    • following from:twitter
    • "new comment" from:wordpress
  • eBay versus Amazon versus iTunes purchases. Are you gravitating towards one online retailer instead of another? Example queries:
    • "Your receipt" from:itunes
    • "you bought" from:ebay
    • summary from:amazon
  • Number of chat messages versus email on a particular project. You could use this to see if certain teams tend to rely more heavily on Google Chat rather than email. Example queries:
    • is:chat "Project X"
    • "Project X"

Getting More Out of Your Inbox

There is a vast amount of valuable information that’s stored in our inboxes. Not only hard data, like the information that’s present in the emails themselves, but statistical information, such as the frequency of communication with a particular person, which can indicate how important a contact they are. Unsurprisingly, there are several startups developing tools for extracting that information from the inbox and doing something useful with it: Liaise, Rapportive, Gist and Xobni, for example. Graph Your Inbox is much more limited than those tools: It only makes fairly simple charts; it’s only available as a Chrome extension; it will only work on emails you have stored in your Gmail inbox; and it won’t work on all Google Apps for Domains accounts. Despite its limitations, however, the ability to throw queries at your inbox to see what correlations there are is surprisingly useful; Graph Your Inbox is a neat proof-of-concept that shows that there could be a market for more complex and powerful analytical tools for email.

You can install Graph Your Inbox here. It doesn’t retain your data or send information to any server.

What interesting results have you found using Graph Your Inbox?

Related GigaOM Pro content (sub. req.): Email: The Reports of My Death are Greatly Exaggerated

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  1. This would be alright if it served a purpose. If you need to data mine your inbox then perhaps you have too much time on your hands. =)

  2. You really liked «Twitter “follows” versus comments on your blog.», didn’t you? You put the same example twice.

  3. Twitter “follows” versus comments on your blog – posted twice?
    Anyway, this is a great idea. Never heard of similar tools mentioned in this article, but will try to graph my inbox…right now!

  4. I tried this out and found some interesting results. I graphed the phrase “meet for coffee” and see a huge spike when I became self-employed. I charted iTunes versus Amazon receipts (you can see the definite bump of the app store).

    But the best one was graphing Netflix “we’ve received” messages. I could actually visualize my usage rates in a way that I’d never had before. (Netflix isn’t particularly interested I guess in showing me how often I actually use their service, which isn’t surprising).

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