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What You Need to Know About the #NewTwitter Posted: 15 Sep 2010 04:11 AM PDT Posted by JoannaLord Well yesterday was a big day on Twitter, wasn't it? I don't know about you but I was glued to the live stream of the not-so top secret Twitter press conference at exactly 3:30 pm and watched closely for an hour and a half while @Ev and @Biz told us all about the new "bigger and better" Twitter.com.  The founders outlined many of the recent achievements they have seen with the growth of their community and announced the release of a brand new interface for Twitter.com, which will be rolling out to all users over the new few weeks (it's important to note that currently only 1% of users have access to the redesign, that decision was not so well received.) The new  interface has a renewed focus on the user experience with in stream multi-media expansions, more search capabilities, and an all around sexier more fluid feeling. I went crazy yesterday playing with the new interface and wanted to share way too many screenshots and my thoughts on the new layout. I am excited to hear what you guys think all of these changes mean, so let's do this, shall we? What are the big changes to our beloved Twitter.com? 1. Redirect users back to THEIR WEBSITE – Whoa! I have to admit I got a little fiesty yesterday when I saw my stream fill up with tweets that said things like "that is it?!" and "its just a new interface, what's the big deal?!" Twitter has over 160 million users, but as we all know many of those users use second party Twitter clients rather than the web interface itself. Ev noted yesterday at the conference that Twitter mobile users are up 250% year over year, which was the motivation for them to release their own mobile apps earlier this year. While this mobile surge has meant huge growth for the community it hasn't done as much for their on-site value. The announcement yesterday was important because it was their first real attempt to redirect those millions of users to a more compelling on-site experience. Whatever the long term goal is for Twitter.com the website, yesterday's announcement was a huge step toward a more united community of users. This.is.a.big.deal.folks.  (The new Twitter.com... ohhh pretty!) 2. A whole lot more space for .... uhmmmm advertisements? So now that we have refocused our attention and time back to Twitter.com what will they do with it? Well sell us things obviously. As you can see below there sure is a lot more space for Twitter to fill. You will notice the "Sponsored Tweets" and the "Who to Follow" elements are more prominent. In addition to that you will see some open areas (that look a lot like traditional ad space units) laced throughout the platform. In general I think its pretty clear that they used this UI redesign to give themselves more options for the up and coming advertising platform we keep hearing about. (Notice all that space they get to play with!) 3. Focus on other tweets, searches…you know uhmmm NOT your tweet During the press conference Ev mentioned specifically that Twitter is a unique community of users in that not everyone actually tweets. He noted plenty of people use it just to listen or research...very "search enginey" if you ask me (yes I just made that word up). The new design certainly focuses less on my actual tweet and more on the experience I am having as a Twitter user. You will see the "search box" was moved to top right, and has much more functionality than previously. I can see tweets with my searched word(s), "tweets with links" & that word, "tweets near me" with that word, and see profiles or people that include that searched word. This is a far better experience all around if you ask me, again compelling users to stay on Twitter.com rather than leave and search elsewhere. Smart move people, smart move. (New search experience...man I love Pumpkin Spice lattes from Starbucks) 4. Media, media, media oh my! This is probably the change you are hearing most about. The new platform has the ability to view pictures and video in stream, by expanding from the left column (your tweet stream) to the right column (now used more as an expanded view). In addition to seeing whatever multi media you clicked on you will also see people mentioned in the tweet you expanded, a brief history of that user's tweets, and the latest tweet that tweet may have been in response too. Uhmmm sound confusing? Basically the expanded view of any tweet is now much more of a comprehensive story of that tweet. No longer on the web client will you be clicking from profile to profile to read a full conversation and get context. This new layout has put the story of a tweet together for you in one place. It's smooth, trust me...you will like it! (The new platform when you expand an image... Hi Matt!)   (The new platform with expanded video...ohhh puppy!) 5. All sorts of other little things You are not losing your backgrounds (phew!). Atleast right now we still have them. Also you might want to revisit your right column profile color--it's bigger now. Direct messages are up in your navigation (quite seperate from the other functionality actually) and are much more streamlined in my opinion. You now click in and see the number of DM exchanges, and can expand to see them all clearly. I was happy to see this. However you no longer see a "number" which was the only way us web client users knew if we had a new DM (unless we got an email notification) so be careful not to miss those new DMs! The new platform still does not support multiple users, sorry folks! Retweets. I still don't really like them, so don't hate me when I say that I am stoked they made the ability to shut off retweets from someone so much easier! It's in there next to the option to get a user's tweets on your cell. Both options are right there and a simple click to change. Easy smeasy for sure. The new platform makes replying to multiple people challenging. No longer can you hit reply and aggregate user handles in one tweet, each "reply" click pulls up an individual tweet box. Ugh, yuck. I hope they change this soon. (When you hit reply a box pops-up...still a bit buggy right now) "Trends" have some serious face time. I think we will find a lot more focus as marketers on getting our topics on the "trend" list (organically or not maybe eventually purchased) as I can imagine this will be much like scoring first page Digg time...similar atleast. You can see they are now top right, whoa in your face! They are calling this a "preview" on the interface, and when you get it you will have a notification box where you must manually click into it. You can also (atleast right now, I guess its going away in a few weeks) chose to "leave the preview" and return to your old interface. I don't think you will want to, but to each their own ;) That about sums up the big changes I am seeing. As for what it all means? I think this is a renewed focus on Twitter.com - the site not Twitter -  the company. Both Evan and Biz alluded to lots of changes coming down the pipeline, and there is a clear energy of excitement in the stream. I don't know about you but I am certainly going to playing around more on the web interface both as a user and a marketer. I think we will have some interesting opportunities coming our way...uhmmm both as users and as marketers ;)   Looking for other insights? Checked out @ev's stream from yesterday, he gave a play for play Read the official blog post about it Watch a video and learn more about it from Twitter Do you like this post? Yes No

Build Your Own Weighted Sort (GA Style) Posted: 14 Sep 2010 11:26 AM PDT Posted by Dr. Pete If you're a Google Analytics fan, you probably already know that Google released a new and incredibly useful featured called Weighted Sort. If you haven't seen it, here's a quick example – let's say you want to know which of your referring sites have the highest bounce rate. You could pull up your referrers, sort by bounce rate, and get something like this: Fascinating, right? I now know that I lost 7 visitors due to 5 sites. If I could just get that bounce rate down to 60%, I'd have 3 more visitors. Wow. What did you really want to know, intuitively? Probably something more like this: That's better – it's not the absolute highest bounce rate you wanted to know about, but the most important high bounce rate referrers. In a nutshell, that's the question weighted sort tries to answer. How It Works So, how does weighted sort work, exactly? Avinash Kaushik wrote a fascinating and very transparent post on the method behind Google's weighted sort algorithm. I encourage you to read his post and I don't want to copy it, but I'll try to do a very basic review here. Google uses something called the "Estimated True Value" (ETV). ETV essentially says this – if the count column of the sort (in this case, Visits) is very low, assume that the column of interest (Bounce Rate) is roughly the average for the data in question. In other words, if a row has 1 visit and the average bounce rate is 75%, then set the ETV of bounce rate for that row to 75%. Since 1 visit isn't enough, statistically speaking, to make any really conclusions, we'll essentially ignore it. On the other end of the spectrum, if you have a very high visit value, assume the bounce rate is accurate as is. Simple enough, right? What about values in the middle? Well, Google sets the ETV somewhere in between the average and the row's bounce rate. Exactly how much of each they use is the tricky part. The Equation This is where Avinash's post ends and mine really begins. I should warn you – it's not going to get Ben-complicated, but there is going to be some math. After a bout of 4am insomnia, I pieced together a simplified weighted sort equation. I'm going to present it first, explain it, and then provide an Excel spreadsheet with some real-life examples. Let's assume we've got a data set exactly like above – visit counts and bounce rates for a set of referring sites. We're going to need 4 sets of variables: V = Visits for Row X B = Bounce Rate for Row X MV = Max Visits for the data set AB = Average (mean) Bounce Rate for the data set For any given row, the ETV of Bounce Rate – ETV(B) – can be represented by the following equation: ETV(B) = (V / MV * B) + ((1 - (V / MV)) * AB) Crystal clear, right? It's not really as bad as it looks. Let's take an example – say we have the following data (same 4 variables as above): V = 100 B = 80% MV = 500 AB = 60% The ETV(B) will consist of two components: V / MV * B = 100 / 500 * 0.80 = 0.20 * 0.80 = 0.16 1 - (V / MV) * AB = 1 - (100 / 500) * 0.60 = 0.80 * 0.60 = 0.48 ETV(B) = 0.16 + 0.48 = 0.64 Pay attention to the parts in bold – since 100 visits is 20% of the max visits for this data set, this row gets 20% of its bounce rate from the actual value and the rest (80%) from the average value for the data set. So, essentially, how much we use the "real" bounce rate for the row is a function of the proportion of that row's visit value to the visit value of the top referrer. Build Your Own Want to try it yourself? You can download my Excel spreadsheet and see the formula at work across a larger data set of actual referring visits from my own site. Although this replicates a function you already have in Google Analytics, it can be used for all sorts of applications that you don't have in GA, including PPC metrics (Visits by Quality Score, for example). There are actually four sheets in the Excel workbook: Basic ETV formula Google's ETV sort Weighted ETV formula Log-based ETV formula Those last two require a bit of explaining. In my very simple model (1), I calculate the average bounce rate by just taking an average across all the rows (for this data set = 70.6%). The thing is, that's not how Google calculates the average bounce rate. They actually weight it by the number of visits, which makes perfect sense. So, in Google Analytics, my bounce rate for this data set is 74.6%, which is what (3) shows. If you compare (2) to (3), you'll see that my weighted formula only differs in the Top 10 by rows #8 and #9 being swapped. My approach is a pretty good approximation for this data set, but it's still just an approximation. If you have a very large range of visit values (1 to 100,000), you might find that rows with smaller but still interesting counts (1,000+) get unfairly ignored. Sheet (4) is a more complex formula that uses the Log (base 2) of visits instead of the raw visit value. This has the effect of de-emphasizing the visit count in favor of the "real" bounce rate for that row. If you're still with me at this point, I hope you'll play around with the spreadsheet. If you find issues with your own data sets or discover some better/cooler way of doing it, please share it in the comments. Do you like this post? Yes No

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