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These ten handy tools will give you everything you need to produce your own micro videos to post online. Vine has been popular from the moment it was launched, but it has now become a full on phenomenon. Better yet, it puts you in with a community of supportive creators who are always looking at new content. You can make professional looking videos with pretty much no know-how whatsoever, thanks to their easy to follow platform and useful automated features.
You can work on the project together, even from across the world, and see all changes as they are made. It is a powerful Powerpoint alternative that is much easier to use, and much more creative. You can make micro videos that loop and share them on your account, using your Apple or Android phone.
This gives your video a more quality look and feel, rather than the bland clip you may have had before. You may have noticed a trend on sites like Tumblr of non-looping micro videos, or collections of flashing pictures set to music. They support full movie editing, which is an interesting plus if your footage is a lot longer. The post 10 Handy Tools to Create Mini Videos: Marketing Through Micro Moments appeared first on Internet Marketing Ninjas Blog. Four years ago, just weeks before the first Penguin update, the MozCast project started collecting its first real data. Most of us know by now that Google isn't a quiet machine that hums along until the occasional named update happens a few times a year. Even before we dive into the data, there's a fundamental problem with trying to predict future algorithm updates. The Google algorithm is built by people, driven by human motivations and politics, and is only constrained by the rules of what's technologically possible. To give you a sense of the scale of the changes that Google considers, in 2010 we conducted 13,311 precision evaluations to see whether proposed algorithm changes improved the quality of its search results, 8,157 side-by-side experiments where it presented two sets of search results to a panel of human testers and had the evaluators rank which set of results was better, and 2,800 click evaluations to see how a small sample of real-life Google users responded to the change. Google's How Search Works page reveals that, in 2012, they made 665 "improvements" or "launches" based on an incredible 118,812 precision evaluations.
We don't have a public number for the past couple of years, but it is incredibly unlikely that the rate of change has slowed.
In March of 2012, Google released a video of their weekly Search Quality meeting, which, at the time, they said occurred "almost every Thursday". Maybe we can't predict the exact date of the next update, but is there any regularity to the pattern at all? I started by assuming that a regular pattern was present and looking for a way to remove some of the noise based on that assumption. This post was inspired in part by February 2016, which showed an unusually high signal-to-noise ratio. This pattern is less clear in other months, and I'm not suggesting that a weekly update cycle is the whole picture. Despite all of our conspiracy theories, there really did seem to be a 2015 Christmas lull in Google activity, lasting approximately 4 weeks, followed by a fairly large spike that may reflect some catch-up updates. The most frequent day of the week for these spikes seems to be Wednesday, which is odd, if we believe there's some connection to Google's Thursday meetings.
I've written at length about why I think algorithm updates still matter, but, tactically speaking, I don't believe we should try to plan our efforts around weekly updates.
Ultimately, instead of trying to predict when an algorithm update will happen, we should focus on the motivations behind those updates and what they signal about Google's intent. Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team.


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You can create your own looping videos that are only a few seconds long, and hey can launch you from obscurity to serious visibility in no time.
Pricing starts at $8 per month for personal, $22 per month for professional, and $33 per month for business. They offer a basic free account so you can try it yourself, which is great for micro videos.
Everything you need is already there in their database, you just string it together and fill in the blanks.
Now they are finally getting on board with promoting the video service that was always there, as they rush to compete with Vine. It works by stitching together ten photos and allowing you to reverse, repeat, or edit them.
Simple, easy, and effective, it is a great way to make short bits of digital content that get you noticed. If you need something business quality you can choose their Business account for $9.99 per month. Though I would honestly keep it as a tool for mini videos, which only take a short time to edit and refine. There are two options: upload from your computer files, or search a URL from YouTube, Vimeo, Vine, or other hosting services.
Detecting and interpreting Google algorithm updates has been both a far more difficult and far more rewarding challenge than I ever expected, and I've learned a lot along the way, but there's one nagging question that I've never been able to answer with any satisfaction. The algorithm is changing constantly and, even if it wasn't, the web is changing constantly around it.
Granted, Google won't replace the entire SERP with a picture of a cheese sandwich tomorrow, but they can update the algorithm at any time, for any reason.
Ultimately, the process resulted in 516 changes that were determined to be useful to users based on the data and, therefore, were made to Google's algorithm. In August of 2014, Amit Singhal stated on Google+ that they had made "more than 890 improvements to Google Search last year alone." It's unclear whether that referred to the preceding 12 months or calendar year 2013. This video and other statements since reveal a systematic process within Google by which updates are reviewed and approved. The simplest analysis that yielded results involved taking a 3-day moving average and calculating the Mean Standard Error (MSE).
We know Google also does large data refreshes (including Penguin) and sometimes rolls updates out over multiple days (or even weeks). It's possible that these approximately weekly cycles are related to naturally occurring mid-week search patterns, although we'd generally expect less pronounced peaks if change were related to something like mid-week traffic spikes or news volume. Many updates are very small and even some that are large on average may not effect our employer or clients. It's interesting to know whether that rate is, say, 5% or 7%, but ultimately what matters to you is whether or not you have a job.
We don't know exactly when the hammer will fall, but we can get out of the way in plenty of time if we're paying attention.
Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!


With more outlets in Singapore than any other operator you will always find a storefriendly conveniently located. Taking a ‘convenience store’ approach to self-storage, branches are located at convenient and accessible locations close to mass rapid transportation stations or popular traffic routes. Our first branch in Singapore opened in December 2011 and we now have 12 branches in Singapore with more in the pipeline.
Please Upgrade to a newer version or other web browser to get the best possible experience using our website. It is a cloud based video editing service that allows you to maintain full creative control between yourself and your team. You put in the words you want to say, and it creates an animation that can be shared with anyone. Magisto takes your chosen video, allows you to add enhancements and a theme, and put in a sound track. You don’t have to deal with any complicated software or gimmicks, just give it a little time.
Can we use past Google data to predict future updates?Before any analysis, I've always been a fan of using my eyes. Finding the signal in the noise is hard enough, but what does any peak or valley in this graph tell you about when the next peak might arrive? Predicting the weather in the real world is incredibly difficult and takes a massive amount of data to do well, but we know that that weather follows a set of natural laws. Now, we don't know how Google defines "changes," and many of these changes were undoubtedly small, but it's clear that Google is constantly changing. It doesn't take very advanced math to see that there are many more updates per year than there are weekly meetings. Analyzing an irregular time series (where both the period between spikes and intensity of those spikes changes) takes some very hairy math, so I decided to start a little simpler.
In other words, for every temperature (each temperature is a single day), take the mean of that day and the day on either side of it (a 3-day window) and square the difference between that day's temperature and the 3-day mean. Then, there's a 2-week gap to the next, smaller spike (March 3) and another 8 days to the one after that. There's a similar, although noisier, pattern in April 2015 (the first part of the 12-month MSE graph). Notice that that first January spike is followed by a roughly 2-week gap and then two 1-week gaps. Low or high unemployment is a useful economic indicator and may help you decide whether to risk finding a new job, but it doesn't determine your fate. Then post it on the site where you can share with others looking for content just like yours. Ultimately, no matter how complex the problem is, there is a chain of causality between today's weather and tomorrow's and a pattern in the chaos.
History can tell us about Google's motivations and we can make reasonable predictions about the algorithm's future, but those future algorithm updates are not necessarily bound to any pattern or schedule. It's very likely that releases are rolled out in chunks and are tied to some kind of internal process or schedule. While this is hardly proof of a clear regular pattern, it's hard to believe the weekly pacing is entirely a coincidence, given what we know about the algorithm update approval process. Likewise, measuring the temperature of the algorithm can teach us something about the system as a whole, but the temperature on any given day doesn't decide your success or failure. That process or schedule may be irregular, but humans at Google have to approve, release, and audit every change.



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