Here’s the first batch of answers to last Friday’s ‘web marketing statistics question time’. (Some of the questions needed long replies so I’ve split them over today and tomorrow.)

There are some powerful tips in both the answers AND the questions themselves – I hope you’re able to use this information with great effect.

Karin H. made more of a comment than a question — but it contains a great tip about how to combine more than one statistic.

The most important/useful stats tell her “which search result page on any search engine my visitor found the page he/she landed on”.

And that’s a powerful technique to optimise any site.

Let your statistics package (hopefully you have one and are tracking web stats) tell you which specific pages visitors land on the most — and which keywords they used on the search engine to find your page.

Then optimise your pages around those keywords.

In other words, give visitors what they were looking for and you’ll get far greater levels of sales and response.

Great tip thanks Karin.

Juliette Player asked a question about the “Average time on site… what is viewed as an ‘improvement’ to this fig?”

She made the observation that “if the visitor is having to dig around in the site for what they require then they will spend longer on the site; however, with improvements in navigation etc. they might find what they need more quickly and therefore spend less time on the site.

So in some ways isn’t a reduction of this figure an improvement?”

Great question, and you’ve hit the nail on the head!

Big business marketers who focus on building brand use the time on site to measure less tangible metrics like ‘brand exposure’.

However, for e-commerce and smaller businesses who need more tangible response, time on site is only important when tweaking it (either way) improves response in the form of actual sales or enquiries (sales lead generation).

The key is all about getting visitors to take action.

If a tweak to a site (like making phone numbers more prominent) means more sales are taken offline, then site performance will improve, but the overall time on site reduces.

So yes you’re absolutely spot on.

And there are two things from this — don’t isolate statistics (which is why I get all my most critical stats compiled into a dashboard each week so I can easily correlate them side by side) and secondly, realise that what a statistic means to one business may have a totally different meaning to another business.

Example: Time on site on this blog is relatively low because most visitors are regular readers who are keeping up with what I write.

So they visit, read the latest article, and then go.

An e-commerce site on the other hand hopefully has a higher time on site as people browse around — but it all comes back to what you said above about improved navigation. If they are coming to the site from the search engines for a specific product and are able to find it quickly, and make a quick payment or telephone enquiry then you have a good site even if the time on site is relatively low.

Cindy King asked a number of great questions about web statistics with the main one being “Please help me choose how to set statistic tracking up.”

For most business sites I recommend Google Analytics. And because they provide detailed instructions on how to add it to any site, I think they’ve saved me the job of explaining it here.

Actually, for WordPress blogs it’s even easier — just install a plugin and let that do the work for you.

Sign up for a Google Analytics account first, then run a Google search for ‘google analytics wordpress plugins’ or similar and there are loads of time-saving plugins you can download for free to help you add it to your blog.

Burton Kent asked “How to effectively track leads through your sales funnel?”.

Now looking at Burton’s blog I see he is quite technical, which explains his question which is quite advanced.

He specifically asked “If I have an adwords ad, which leads to a signup to my email newsletter, which leads to a sale of my book, I’d like to track all of them through each step.

There are lots of different ways of doing this.

The challenge as you’ve no doubt realised is that a signup to your newsletter can happen today, and the same person buying your book could happen weeks or months later, after they’ve cleared their cookies. So Google Analytics may not see it’s the same person.

What you can do is track on two separate levels, and then ‘join’ the data for analysis later.

So for example — and assuming your keywords are divided into specific categories as much as possible — get your Adwords to send a URL code to your squeeze page.

A line of PHP script parses the code from the URL and adds it as a hidden form field.

When someone signs up to your newsletter, the code can be stored as a custom field in AWeber (or whatever database you use.)

Finally, as people on your list buy the book, you’ll be able to cross reference with the newsletter data and determine which AdGroup they came in on.

And then you’re in a really powerful position to optimise your campaigns based on profitability, not just initial conversion.

Burton also asked a second question which I’ll mention here because it contained a critical element to making the most of web statistics to help a business grow.

He asked “How can I use statistics to come up with specific elements to test, optimize and otherwise improve? (Stats in themselves are worthless unless you use them somehow.)”

Coming up with specific test elements is the key to putting all this together.

There are SO many stats that it’s all too easy to not do anything with it.

In the last session of my Stats Faceslap programme I explain how to identify which stats are most important based on the type of business you operate (online or otherwise). I’ll be announcing the launch of that programme any day now, but in advance I’ll give few pointers.

FIrst of all, forget trying to use ALL the possible stats. Work out which stats are the most critical to your business, the strip those out for analysis each week and for comparison with previous weeks so you can see trending.

Google Analytics can provide a tonne of information, but on it’s own it will miss other critical data related to email marketing, RSS, search engine keyword rankings and back-link counts (all explained in Stats Faceslap).

So the key is to pull all the most critical stats together for side bvy side comparison and forget the rest.

Also create a test plan — a schedule of what you want to improve and HOW you intend doing that. Then weekly stats give you the feedback to see how you’re doing.

And Burton’s comment that “Stats in themselves are worthless unless you use them somehow” is so true.

For years I’d ‘occasionally’ log into my stats package and view them with interest, but not really implement any changes as a result. It was a total waste of my time.

These days I have a system to collect stats from the various sources, that eliminates all the stuff I don’t want to see — and I have a plan to actually use those stats to improve sales and profitability.

Answers for the remaining questions will be posted tomorrow.

-Ed.