3 Features Missing From Evernote

image

1) Smart Merging. When processing notes in Evernote, two notes about the same thing often show up. While you can merge them in certain views, it could be made much more functionally intuitive and easier, perhaps by dragging one note on top of another, using a contextual menu, or activating the feature before selecting two or more notes to merge.

2) Contacts. Of course you can keep contacts as notes tagged with “contact,” but there should be a better way. Rather than create an entirely independent system for contacts, just enable contacts that sync with GMail/Android/Yahoo/iPhone contacts.

3) Share from Web Clipper. The Web Clipper is great and allows you to clip portions of blog posts and articles to Evernote, but what if you would rather immediately share that with a contact? With #2 in place, the Web Clipper offers the option to send the clipped portion to one of your contacts, either as a link via SMS, or as an email, or even directly to their Evernote inbox for trusted contacts. (!)

7

Client: Evernote Corporation.

The Browser As App Interface


cc licensed ( BY NC SD ) flickr photo shared by Jason A. Samfield

When you visit a website, the browser should customize itself to the site you are visiting—becoming an extension of the site itself.

For example, while on Tumblr, you might see three additional icons to the right of the Chrome address bar: one for creating a new post, one for inbox messages, and one for account settings or to logout. Now, these icons already exist within the page, but the idea here is to allow a site to skin the browser to free up space within the browser window itself.

A set of icon links beside the address bar seems to be the easiest iteration to begin with, but these could evolve into actions. For example, these could be a set of filters that process a photo in the main window, or buttons related to commercial transactions on the page.

Perhaps the user can toggle between browser mode and the app interface mode.

7

One-Click File Management

image
cc licensed ( BY NC SA ) flickr photo shared by Ika-Ink

Imagine a magical piece of software that organizes your entire hard drive for you.  

Whenever it finds an .mp3, the software scans it, tagging it if necessary, and understands that it isn’t a song, but rather a podcast, converts it if necessary, and places it in the “Automatically Add To iTunes” folder. 

You specify whether to sort by date, person, place, or contents, and the program sorts all of your images into a logical file structure using facial recognition, location tags, file date, &c. That makes it easy to add them to iPhoto or Picasa, and saves you having to sort through and organize all of the imported images like you usually need to.

Likewise, it scans your .pdf’s and .doc’s for subject matter and organizes them into categories, understanding the difference between the .pdf version of a book and a .pdf of your bank statement.

You can see how you can apply this to the most common file types at first, with a handful of options and reiterate the software from there. 

It may be better to have it only partially-automatic. In other words, it may be best if it gets a one click confirmation from the user for any decision that doesn’t produce a certain confidence level. As it does this, it offers one or two alternate options for the file that the user can specify with a click.

And, most importantly, information about the files is anonymously relayed to a central location where you can see where the program gets it wrong and compare how different users chose to sort certain files so that the program educates itself and performs better for each subsequent user. So, if 1,000 people have a .pdf with the same header (even if the rest of the file is different,) and 900 of them said that it belongs in a folder called BANK STATEMENTS, then the software defaults to doing the same for you.

Finally, to find or manually manage a file, you’d use a graphic-based search within the software (or as a stand-alone OS integrated search.) This way, if you download an image of Olivia Wilde—and the software has already processed the download location, you’d simply search for PICTURES > PERSON > OLIVIA WILDE, or PICTURES > FEMALE > RECENT, or PICTURES > FUTURE GIRLFRIENDS.

7

Follow me on the Twitter.

The Hidden Information In Amazon Reviews


cc licensed ( BY NC ) flickr photo shared by sneeu

While I’m OK with reviews going to a five-star system by default, it is becoming clear that reviews are largely skewed toward being overly positive. Because of this, when we look at book reviews on Amazon.com, you’ll see that the majority, it would seem, are rated four out of five stars or above.

Objectively speaking, that one star may be more personal preference than anything else, so most books essentially have the same rating at a glance.

But, I noticed that while two different books might each be rated four stars, the bar chart on the product page of each book showing the number of reviews received for each star rating could look significantly different. I started to wonder if there might be extra information about the quality of a book in the characteristics of the reviews bar graph.

I think there may be signature qualities to the graph that can indicate whether a book is truly exceptional or so-so. First of all, we have to have a large enough sample, say 100 reviews posted before applying this heuristic, and of course, the accuracy of this should increase as we have more reviews (perhaps you could couple the data with bn.com reviews, &c.)

Secondly, you’d want to look at the slope of the curve of the line that would be created if we made the bar chart into a line graph—-and this slope should look like an exponential curve (the exact equation TBD.) Specifically, look at the slope between the first point (five-star review number) and the second point (four-star review number). I would hypothesize that there is a sweet spot where the slope is not too great (where you have a cult-like following of devoted readers and reviewers) and not too small (where there is significant hesitancy to give it five stars, i.e., there is something lacking.) Here are two screenshots showing the difference produced by these effects (and both of these books have four star ratings.)

New-earth
Tipping-point

Now compare those two to the appearance of this graph:

48-laws

One particular important characteristic I believe is the relationship of one-star ratings to two and three-star ratings. A great book will have one star ratings from someone, but most often (with notable exceptions in politics and religion) the graph will show more four-star ratings than three-star, more three than two-star. But, the relationship between two and one-star ratings is a bit more complex. If there is a sharp upturn in the number of one star ratings versus two and three-star ratings, this might be a cautionary characteristic, but it may be the case that a small upturn is actually a good thing (as a great book is more likely to be attacked.) As mentioned earlier though, you need to control for certain subject matter.

Other characteristics could include the ration of three-star to five-star reviews, for three-star ratings are often the most objective and critical. So, a book with a lot of five-star ratings and a high number of three-star ratings relative to that number might temper the overly positive initial appearance.

In short, I believe you could offer a web application that would allow someone to paste an product link into the app and it would offer its analysis based on these refined criteria. It’s like reviewing the reviews, and you could do it for other products other than books, where each would require a bit of fine tuning.

7