My name is Pedro Laboy and I am a business strategist. My specialties are marketing and
branding. My tools of choice are technology, social media, and analytics. My name is
Pedro Laboy and I am a business strategist.
An illustrated history of content from Mashable.
Social sharing in 2010. From ReadWriteWeb.
How exactly does one estimate the reach of a blog placement?
Estimating the reach of a display (banner) ad is a straightforward process. We can tell how many times the ad was served, how many people interacted with it and how many of them clicked through.
For blogs, this task is bit more complex and at times not possible to estimate. First, a blog’s “media kit” only provides Monthly Unique Visitors (MUV). Second, there is no mechanism for tracking exactly how many people view the placement.
Some brands take a simplistic approach to estimating the reach of a blog placement. For example, some simply divide the MUVs for a blog by thirty days to get an estimate of how many visitors viewed a post when it was in the top spot on a blog. However, the daily number of visitors ebbs and flows–there be many unique visitors that frequent the site every day, but there may also be several days that do not fit a typical linear pattern.
For instance, let’s assume that a blog has 10 MUVs, and that they visit the site every time content gets posted. Even if brand’s content gets posted only once, you would still reach 10 MUVs. If the visitors only read every other post, you would reach half. This is the reason why blogs do not give daily numbers.
Another approach would be to use a tool such as Quantcast to estimate daily visitors but given the example above it could lead erroneous assumptions. Furthermore, there are many external events that may affect a blog’s daily unique visitors. Some events are known and anticipated. For luxury brands, it critical to secure placements during Fashion Week or on Oscar night and celebrities are dressed in designer labels—but a placement during Superbowl Sunday would likely fall flat. There are also unpredictable events that may cause certain days to have an abnormal number of visitors, whether it be higher or lower.
In my experience, the actual reach of a blog placement is closer to the monthly number than to the daily one.
FeedMagnet is a new social media aggregator developed by a former colleague, Jason Ford. FeedMagnet is quite a bit different than social media tools such Gist or Seesmic. Both of those are consumer tools designed to help manage an individual’s interactions on social sites. FeedMagnet is for companies or organizations.
The initial product is essentially an aggregator for marketing purposes. Let’s say your company has 5 executive tweeting plus official company accounts for Twitter, Flickr, and YouTube. FeedMagnet would let you pull content from all of those sources into a single, integrated stream – with videos and photos embedded directly in the content (so you don’t have to click over to TwitPic or YouTube). Once the content is integrated together, you can filter it, moderate it – and then the real value is in getting to post that content back on your website. I have created the graphic below to help you visualize how the technology works.
In addition to pulling in user feeds from a person (i.e. @pedrolaboy) or a company (i.e Coca-Cola) it can also pull in search queries. So let’s say you have a website that sells Rock Band for the Wii. You can run a series of searches on Twitter, YouTube, Vimeo, Flickr, and other media sites to pull in user-generated content of people talking about and playing Rock Band. You can then filter the content based on keywords (to exclude curse words for example) and moderate the content if you choose (to make sure nothing obscene gets through). Once you get everything set up, you have a feed that is rich with photos, video, and text of people enjoying Rock Band that you can put right on the purchase page on your site to increase conversion rates. Here is another graphic using Echo to illustrate how FeedMagnet works.