Are You Excited That You Are Boosting Your Own Web Analytics

There is one person who will repetitively visit your website, you.  When consultants, trainers, or professional coaches decide to make online marketing a priority, they often begin checking in on the site to see changes or to inspire ideas.  While that level of engagement is great, it can cause false results on the analytic reports.

The last post was about critically analyzing web analytics and a good example recently came up.  A client was running three separate campaigns to boost site traffic.  The push was set up because they were testing three separate offers to see which call to action created the best conversion. At the end of two weeks the client called and said, “We’ve seen a boost in traffic of 30% this month (roughly 300 more visitors).” While a jump was expected such a marked change so quickly seemed excessive.

So we pulled up the analytics and began reviewing where the traffic came from.  As it turned out, some of the increased traffic was legitimate but about half of it was self-created.  This client had five trainers that were all being asked to provide their input on the calls to action.  As suggestions came in, the trainers would go back to the calls to action pages to review revisions.  Doing this several times resulted in the group creating a false 150 hits.

So why is this important?  The significance of the hits has two primary effects.  The first is that we never want to create false data that guides our decision making.  The campaign did have a good start but it was about a 15% increase.  Making a decision on the calls to action or traffic generating campaigns would not have had true tested data. The second effect is it can skew trends.  At the end of the second two weeks, the increase was just under 25%.  Had we not reviewed the hits it would have appeared as if we had peaked quickly and were now regressing, when in reality we were continuing to see gradual improvement.

For this particular example, the resolution was to implement filters for the IP addresses of the firm’s computers.  But as an illustrative example, it’s a reaffirmation of keeping a close eye on analytics and questioning results that seem overly positive or negative.

Critically Analyze Your Web Metrics

One of the biggest advantages to improving online marketing is the fact that data is instantly available to inform decisions.  However, sometimes data gets oversimplified and provides false “insight”.

Recently a client expressed concern that the referring links from their social media platforms was too low.  It was true that only a small fraction (about 2%) of their traffic was generated from their social profiles according to the website analytics.  The requested action was to get more posts on the social profiles to generate more clicks.

On the surface that seems like a reasonable response.  More activity will result in more traffic.  However, it was actually a misassignment of data and a lack of critically analyzing the data.  Most of their social posts either had no links or were linking to a blog not hosted on their website.  Increasing posts would likely have no effect on links back to the website because the posts were not set up to link to the website.

So instead of arbitrarily making posts, we focused on linking content back to the website by ensuring that at least half of the social posts included a link to the website.  At the end of the month, we had a more realistic figure on social engagement with about 15% of traffic coming from social platforms.

Misaligning web analytics is where “best practices” become a liability.  For example, a common best practice is that bounces are bad and they should be as low as possible.  That typically is true. But what if a page is promoting a social media contest with a link to your LinkedIn page?  If the page is effective, most of that pages traffic will show as a bounce.  So rather than looking at the page and saying, “it’s performing poorly”, some tracking from the site to the LinkedIn post need applied to find how many people moved on to the offer and how many left.

Avoid oversimplifying your web analytics.  A lot of “best practices” regularly get applied across the board with no critical thinking.  This typically results in wasted effort or negative impacts to marketing campaigns, or both.

Consistent Online Marketing Activities Are Required for Consistent Results

There seems to be a common misconception among trainers, consultants, and professional coaches that once you get your online marketing campaigns rolling that it then runs itself.  There is never a time where you should be asleep at the wheel.  Every online communication channel requires consistent activity and a lull in activity will almost guarantee a lull in results.

Online marketing is like any job.  If you stop showing up, you’re not going to get paid.  A relative of mine has been running a blog for several months and is just starting to get some traction.  He was asking about blogs and how difficult it can be to get off the ground.  I commented, “People seem to think once the blog is established that it runs itself.  It’s still hard work creating content consistently and maintaining relevancy.  And try not writing anything for a short period of time and see your stats fall off a cliff.”

He laughed and said, “It’s funny you say that.  I went on vacation for a week, when I checked my analytics my traffic sharply dropped.  By the end of the week my daily traffic was only at 25% of where it had been.  The numbers didn’t rebound to their previous state for another two and a half weeks.”

We’ve not done strict testing on his numbers but it appears to be a good rule of thumb.  If there is a period of inactivity on your online marketing, it will take twice that amount of time to recover.  This isn’t just for blogs.  It applies across the board to websites, social media, and email marketing.

Monitor Bounces: Websites

When reviewing website performance we tend to gravitate toward the positive interactions.  These are the metrics we hope will be high: visits, clicks, conversions, etc.  However it can be equally important to measure the negative interactions, opt outs and bounces.  By keeping those numbers low we increase the opportunities that the positive interactions have.  Bounces specifically can be important for uncovering site performance because it’s a direct indicator of how visitors react to our content.

Website bounce rates are when a visitor lands on a webpage and then leaves.  As a general rule a 50% bounce rate is average.  After all every visitor to your site has to leave from somewhere so non-existent bounce rates just don’t happen.  If bounce rates get down in the 20’s% range or less, then you have a high converting page.  This often only happens on landing pages where people come for a certain thing and have to complete a single item to get access to it.  Rates higher than 50% can be a signifier of problems with the pages content.

A word of caution when analyzing bounces, make sure to take the page content into account.  There’s an art to analytics as well as science.  Some pages will be prone to bounce rates and it’s not necessarily a negative sign.  A blog post, video, or article page are good examples.  This is even truer when promotions are sent out advertising these things.  It’s reasonable to expect that the majority of people that land on these pages will view the content that enticed them there and move on.  Some subset will likely click on to something else but the lion’s share of visitors will get what they came for and go.  A higher bounce rate on these pages should be expected.

By default many analytic programs will display bounce rates in a time layout (i.e. bounce rates by day).  This is helpful if a certain campaign is going on for a set amount of time.  However, pulling bounce data by page is often more useful for overall site analysis.  The reason for this is that the pages can be sorted by highest bounce rates.  This will bring your worst performers right to the top of the list.  Then you can move down the list and see which poor performers are expected to have a higher rate and which should be performing better.

Once the list of poor performing pages is compiled, it’s a matter of reviewing those pages and updating the content.  There is something that visitors expect to get from this page but aren’t.  Trial and testing is needed to modify the page so that it’s suiting visitor needs.

Think of your site as having a party.  Having a lot of people show up is a good start.  But if they all peek in the door and head somewhere else it’s not going to be much of a bash.  Bounce rates are a great way to find the pages that are turning your visitors off.  Use that information to make pages enticing and draw visitors in.