Search Marketing Insomniac…The Blog of Adam Henige

Well, today I had the honor of being co-emcee of the PACE Awards and it was truly a wonderful experience.  The CMPRSA honored the best public relations campaigns and tactics from the many great agencies in Mid-Michigan.  There was a great turnout, and it was my first chance to meet a lot of these people who have put in such time and effort in promoting causes that improve the lives of so many of us in Mid-Michigan.  The agencies behind Prop 2, a variety of enforcement acts, the City Market and so many more were honored for their fine work in community relations, crisis communications and B2B campaigns among others.

There was a definite air of excitement, and it was made that much more fun by my co-emcee Julielyn Gibbons, who was having fun with the event from the moment I walked in and seemed to know everyone in the room.  That was a big help for a relative newcomer such as myself.  Being co-emcee also got me a great seat up front and I had a chance to sit with some of the day’s big winners, including Anne Readette and Kendall Wingrove.  Also at my table were members of the Michigan State PRSSA team that made the finals of the Bateman competition.

To say I was surrounded by talented people would be a major understatement.  It was a lot of fun to be a part of, and as if to prove the 2.0 theme of the event, @netvantage had added a bevy of followers before I even left the parking garage at the Kellogg Center.  The award for the quickest add?   The Rossman Group’s own Kelly Rossman McKinney!  One more award to add to the collection the Rossman Group pulled in.

Anyhow, I just felt like summing up the day’s events, as it really was a pleasure to take part in it.  In particular, thanks to Amber Shinn for approaching us to get involved with the event.  I’m already expanding the Netvantage Twitter circle, and if anyone feels like following me directly, you can find me on my personal account @AdamHenige.

So far we have covered the importance of audio and proper framing techniques in our HTMYVTDS series (I really need to work on that acronym), and today we’re going to tackle what is often the most difficult issue for aspiring videographers - lighting.  Many an otherwise acceptable video has been ruined by shoddy lighting, and today’s aim is to arm you with enough practical lighting knowledge to keep things looking sharp.

First thing’s first, you’re going to need to invest in some lights.  Yes, I know most of us are on a budget right now, but there’s really no way around it.  However, most of us aren’t aiming to recreate the dramatic lighting of Hollywood’s finer moments here, we just want people properly lit so they appear to have some depth to them, and no hideous shadows.

For our purposes, we’ll assume we’re shooting a stationary subject, and here we’ll try to cover two basic approaches to lighting.  First, the ideal for a one person shoot is three point lighting.  Three point lighting has three basic components, a key light, a fill light and a hair light (or back light).  The image below demonstrates this basic setup.

Your key light should be the most intense, providing the most brightly lit component of your subject’s face.  Ideally, your camera will have zebra stripes on it, which should have only the most brightly lit areas on your subjects face (oftentimes on the forehead) showing some slight zebra stripes.  If there is a significant amount of zebra stripes, you’ll need to close the iris a bit or tone down the lights, and the opposite if there are no zebra stripes.

If you’re dealing with a more rudimentary camcorder, you’ll have to use your LCD or viewfinder and just eyeball it.  Basically, you want to make sure the key light is providing a bit of “pop” to the subject’s face, but not blowing it out to a glowing white.

The fill light should do just what it says, fill in the other side of the subject’s face, at a slightly lesser intensity than the key light.  This provides some depth to the image, as video often appears flat.  Overdoing the contrast might make your subject look like a bad horror flick, so beware of that.

The hair light has one primary purpose, and that is to separate the subject from the backdrop.  Hitting the back of the head with a pretty direct and focused light will help clearly define your subject as the focus of the shot.

For a visual example of three point lighting, here’s a short video on the subject:

With one light you will not have the option of a fill or hair light, so you need to do the best you can.  Ideally, you’ll want to soften the light as much as possible, so if your lighting kit comes with a softbox, an umbrella, or some other tool that will help diffuse the light, you’ll want to use it.  You’ll have to set your light up offset to one side of the camera or the other, so by softening the light you’ll reduce the hard shadows on your subject’s face, and by experimenting with their positioning relative to the light and camera, you can still get a bit of that key/fill look to the shot.

While a hair light is out of the question here, you’ll want to worry about the shadow in a one light set up.  Nothing is worse than a large silhouetted head bobbing around behind your subject that you don’t notice until you go to edit.  Be very aware of shadows, and do your best to keep your subject a reasonable distance from any walls.  If you have a soft light, simply pulling them away from the wall behind them will often remove any problems you may have with shadows.

If you’re looking for some real bargain basement lighting, check out products by Smith Victor.  Not all of their stuff is professional quality lighting (I’ve only used their low end products personally), but they will provide you with a couple of soft lights and a light you can use as a hair light, and with a little configuring can provide a nicely lit shot.

Good deals can be found on ebay here.

Google Analytics’ addition of advanced segments allows for nearly limitless slicing and dicing of data. But if you’re not an experienced hand with analytics, you probably don’t have time to fuss with it to learn EVERYTHING that can be done with the tool, you just need to know how to get some real value out of it quickly and easily. With that in mind, here’s a quick tip.

Whether you’re starting out a new SEO campaign, or have been working on one for some time, it’s always valuable to segment your organic traffic to see who’s coming in via branded terms (your company name, or the brand names of your products and services) versus more general terms. Most likely, you rank out well for your branded terms, but a significant value of SEO is to create awareness and capture potential customers who are not yet aware of your brand name(s). Using Google Analytics, you can set up a filter to continually track your non-branded traffic, and this is a great metric to look at to see if you are getting some tangible benefit from your SEO work as far as engaging new potential customers. Ideally, you want this number to grow over time.

Here’s what you need to do :

1. Open the advanced segments tab (in the upper right corner)
2. Click on “create an advanced segment”
3. Under Dimensions (in green) click on “traffic sources” and drag the “keyword” tab into the Dimension or Metric rectangle into the ghosted box in the middle of the screen
4. For the value, add your most common branded keyword.  For us, we could do this in one easy keyword “Netvantage“, you may have to add multiple “or” statements for your different brands, so try to be broad but be sure not to add something that will exclude general searches
5. In the “Condition” tab for each, select “Does not contain” and then give your segment a name and  select test to make sure that you’ve set things up properly.  If you see a significantly lower number of visitors in your test segment, you’ve probably done things right.

Armed with this data you can see if your organic traffic, and your SEO campaign, are bringing potential new customers to the table, or engaging those who are already well aware of your business.

Why keyword density isn’t (and is) important.

Among the SEO creme de la creme, keyword density is a phrase not even worth re-hashing, but for many, it remains a mainstay in their SEO lexicon.  Obviously, I’ve run my own experiments and seen my own successes in the past with upping my keyword density, which is why I’ve lauded its success, despite “knowing better”.  I’ve always had some knowledge of term vector theory, and had an understanding at only the highest of levels, but never actually sat down and tried to walk my math-retired mind through it to truly get it.

Disclaimer: I do not claim to be an expert on term vector theory. If you see inaccuracies, please feel free to comment or shoot me an email.

What I aim to do here is explain why so many SEO big shots (correctly in their circumstances) disregard keyword density, and then show why it can be beneficial in other circumstances.

First, I’m basing this on Salton’s Vector Space Model of information retrieval (or IR…you know, what search engines do).  Basic elements of this model include:

• Term frequency
• Maximum term frequency in a document - the number of times the most frequent phrase (of the same length as the target phrase) appears in a document
• Document frequency
• Total documents

The equations of interest are:

• Term weight: term frequency/maximum term frequency in a document*log(total documents/document frequency)
• Inverse document frequency, which is just the second half of the term weight equation: log(total documents/document frequency)

Now the term weight is the article of interest from a ranking standpoint.  If we assume this is a part of the search algorithm, we would like a high term weight (but much like the wheel on The Price Is Right, without going over).  Keyword density is discounted in this formula as it’s only a ratio of one document, disregarding the surrounding environment, which this model takes into account.

Keyword density makes us feel warm and fuzzy because we can calculate it.  But, in the grand scheme of things, that usually means very little.  Why?  Because in the term vector model, we’re dealing with unknowns.  We do not know the exact document frequency, and we do not know the exact number of documents in the database.  Further, if you look at the equation, the logarithmic function helps create the inverse document frequency, which helpts to normalize results.  Let me explain this with a tangible example.

Let’s say we have two pages optimizing for the phrase “Netvantage Marketing”.  The first page has a frequency of three for this phrase, while the other has a frequency of six.  The maximum frequency for a two word phrase on each is six.  Theoretically, one would think that the document with higher frequency of “Netvantage Marketing” would have a higher term weight, but that’s dependent on the other variables.  The inverse document frequency is largely impacted by the number of documents containing the term, the document frequency.

As the true document frequency number, as well as the total documents are unknown (unless you’re willing to believe Google’s ever changing number of results), you’re really just shooting at a moving target.  Here, the page with the term frequency of 3 actually has a higher term weight.  So, to some extent, one cannot confidently say that a higher “keyword density” or term frequency will actually lead to better results.

As you can ascertain, the more documents a term appears in, the more it’s marginalized, thus causing less impact when changing frequency.

So this is why people, particularly in competitive markets pay little or no attention to “keyword density” and instead focus on writing good content.  The way to win in the SERPs for those markets will be through links.

However, the more I dug into this, the more I realized that term vector theory and term weights actually validate the positive results that people claim to get (me being one of them) when it comes to increasing keyword density/frequency.  In lesser competitive markets and when going after long tail terms, the math actually makes sense.  Consider that in these markets the document frequency doesn’t fluctuate or grow at the rate of hyper-competitive markets.  That said, changing the term frequency can have more of a dramatic impact, especially when considering competitor sites probably aren’t well optimized on page and probably don’t have great link strength.  Check out this simplified example of this scenario:

If the environment doesn’t change much, the effect of the number of total documents has little effect, it’s the document frequency’s stagnation that allows for a (seemingly) sustained advantage in this non-competitive market.  So, if you’re in such a market, by all means, fiddle with your keyword density/frequency, you might see some serious results through improving your term weight.

Now whether or not this is how search engines use term vector theory/term weight, I can’t say for sure, but hopefully this either sheds some light or starts a good conversation on the subject, as I’m still evolving my understanding.

First off, it needs a new name.  I’m taking suggestions.  As an SEO, I have to put my ego away and finally realize that using my own name in the title isn’t an optimal way to bring in traffic.  My mother is going to be crushed.  Send me your suggestions…even if they’re crazy.

Secondly, I went dofollow a while back, and haven’t publicized it until now.  So yes, as long as you don’t do anything gratuitously spammy you can benefit with a little link juice from my recently minted PR4 blog.

Yep, that’s right.  Last week was the latest PageRank update and I’ve officially returned to my previous PR4 status, making my blog’s home page the most important property we own.  Everyone in the office is going to hear about this…a lot.