Have you ever tried to optimize your website based on demographic data about your visitors? I haven’t. Yet. That’s why I decided to look into it. The first step: find out the demographic profile for your website visitors.

The good thing is that such data is accessible. The reliability depends on how it is calculated and the sample of traffic that each demographic data tool has access to. Where to start?

To get accurate demographics data you only need details about a sample of random visitors. The bigger and the more random the sample, the more accurate the data.

Demographic data by Google and/or Facebook

Yes, Google does provide demographic data for most of the websites out there, though you need to dig in for it  little. You can get details about the localization and language of your visitors from your Google Analytics account:

Google Analytics is pretty much it, when it comes to data about your visitors. However, Google Analytics is just that: a tool that provides statistical data about your visitors, based on which you can improve your website.

While it can do many other things, it pretty much sucks at them. So, what shouldn’t you do with Google Analytics?

Google Analytics is not a financial tool

Yes, there is eCommerce tracking but it is only meant for adding revenue data to your traffic data and do correlations between them. I’ve seen hundred of eCommerce implementations and I am yet to see one that fits exactly the reality.

Why isn’t it 100% accurate? Chargebacks, plugins that block Google Analytics, pages that load slowly and are abandoned are just a few reasons.

This is a guest post and the views of the author do not necessarily reflect the views and opinions of padicode.com. The author, Traian Neacsu, is the co-founder and Director of Search for Pitstop Media Inc, a top rated Vancouver SEO company.

Unless you’ve been living under a rock for the last few years, you have heard of A/B or multivariate testing for websites, aka conversion rate optimization. 2011 being coined by many “The Year of the Conversion Rate Optimization” and the fact that you’re reading this blog makes me think that you already familiar with jargon like CRO, LPO, MVT or A/B/. And, if you a smart marketer or website owner, then you already tried and reaped the benefits of website testing for conversion optimization.

Thanks to tools like Google Analytics, anybody can have access to valuable web analytics based on which to improve a website. Not everybody succeeds though.

What makes a good and mature approach to dealing with analytics data? How do pros and beginners deal with web analytics in different scenarios?

A new web analytics feature comes up

Boys play a few hours with it, apply it to random sets of data, take a few screenshots and jump up to write a blogpost or tweet around about how amazing the new feature is.

Men ask themselves: Does it help me and does it help now? If the answer is yes, they go through the documentation, try the feature on small sets of data on which results can be easily validated.

Based on the value the new feature offers, it will be included or not in the personal framework for analyzing the performance of a website.

E as in engagement. E-spot is the mix of timing and website elements that make a visitor convert (buy, sign-up, fill in a form, etc). With some users, the E-spot is reached very easy while with others there is just rejection or bounce.

Engagement is one of those things everybody wants but few can really define in a measurable way and if there is no measure, there’s no scientific way to act on it. How do you go about finding, measuring and acting on the E-spot of your website? Here are a couple of suggestions:

Dig deep into data. Segment.

Being a web data segmentation freak helps as Engagement is best understood when looked at from different angles and perspectives. Sales are an undisputed proof of engagement as well as “I want to know everything about what you do” forms for generating leads.