I’m not sure how many of you out there have read Avinash Kaushik’s new book, “Web Analytics 2.0” but if you haven’t yet managed to feast your eyes on this beauty, then I would strongly advise you to get your hands on one. I’m normally not subject to book reviews, I normally leave that to the dedicated bookworms of Amazon.com, so I’m not going to delve into that here…
Let’s get straight down to business, shall we?
There’s a chapter located within the great tome of “Web Metrics 2.0”, Avinash’s colossal phone-book sized effort at disinterring the myths of forgotten web metrics, called ‘web metrics demystified’ that details four dimensions of analysis that will help you expose the trivialities of a number of useless SEO metrics out there that do nothing but waste your time and energy with vacuous reporting, complex tiers and vague relevancy. In this chapter, Avinash hinders upon web metrics being highly subjective to the nature of the business. Despite most ireful analysts viewing this statement as stale and far-fetched, the common sense here is too hard to ignore. Whether you’re a business owner or a search analyst, you can devote an insane number of hours to analytics tools that don’t necessarily quantify the most important data from your website.
On the chapter ‘demystifying’ web metrics, the author presents a set of rules for selecting and refining your way through a myriad number of web metrics that exist out there…
“In a world where metrics and ket performance indicators are a dime a dozen, how do you know which one is your must-have darling?”
The first lesson taught is that your web metrics should be uncomplex. You shouldn’t be using the enigma code book as a guide to generating complex and speculative formulas that determine what the user had for breakfast after he/she has clicked a button. If you develop this complex formula, who is really going to benefit from it if only you understand it and it would be easier teaching Japanese to a monkey over explaining it to someone else. The metrics that you decide to use for a website should be simple, with a logical explanation behind them so they can be easily picked up by someone else working with you. If someone else doesn’t understand the metrics, then how can you expect them to take action on your findings? Keep it simple so others can interpret, take action and subsequently get the job done.
The second lesson is relevancy, and I think that this one is pretty common sense stuff. The universally accepted notion is that all metrics will be subjective to the business model of your company or your client’s company. The metrics that you identify need to be relevant to measuring the success objectives that are unique to you and your website, or the client and their website. In order to gauge the relevancy of the metrics to your business align the needs of the business with key statistical indicators – there are a number of these, but I’ll list a few: Task completion rates, share of search percentages, Visitor loyalty and recency, RSS and blog subscribers, percentage of valuable exits, conversion rate percentages such as cart and checkout abandonment, days and visits to purpose… The list goes on. Make sure you know what the core metrics are and do your research thoroughly! The most common mistake made by web analysts is that they stick to their comfort zones when selecting web metrics, and some indicators that they’re comfortable using may not align directly with the needs of the business.
The third lesson mentioned is that your web metrics need to be timely. The bottom line here is that you should set up your reporting models and analysis intervals when the business needs it most. One month is a good starting point for most businesses, including online retailers because it gives you and your client ample time to test the cause and effect of different implementations. You can’t get lazy with your metrics, reporting and tracking needs to be timely in order for your business to gain any benefit. Avinash mentions that some people have even stressed real-time mentions, but I completely agree when I say that this is utter garbage… Real-Time…? You’ll find yourself doing more reporting than actual work.
The fourth lesson is that metrics should be instantly useful. I don’t need to be putting this in my own words, because the author sums it up perfectly in a single sentence:
“Instantly useful is when you understand quickly what the metric is and you can find the first blush of insights as soon as you look at it.”
Now, the author mentions something called ClickTracks but I’m pretty sure you’d still get the same pretty picture using Google Analytics. Make sure you’re staying on top of your main referral sources so you can easily ascertain what elements require more work and which elements don’t. The premise of this point is that a great, useful metric allows you to look at it at a glance and you instantly know what needs attention.
Not a bad insight, right? If you haven’t checked out this book we highly recommend it. We should know, we have 4 copies