I write one post a week now and yet the blog is about 25 hours of work each week. Email is one big contributor. Many many of you write in with specific questions and it takes a lot of time to answering every single one with specific advise.
[Some are really tough, this is the complete email: "What are two best multi channel metrics you recommend, I have a big presentation tomorrow". (!!!)]
In this post I want to share two recent "dear avinash" emails. I get these two issues very frequently, so obviously they are big concerns for all of you. Hopefully you'll find my answers to be of value.
# 1: Web Analytics Career Advice (Agencies):
I work for an agency, our clients use many different analytics packages, they grant me access and I have to look at this data to try and show them how our work is benefiting them.
I am fairly confident using Google Analytics, but with the rest, I have almost no experience, and I worry that I will mis-use the data. Also, with all of the clients, I have not been involved from the beginning, when they set it all up, etc. which I worry means I am missing out on something critical.
I try to contact the specialists within the client companies, to try and confirm that the data I am using is ok, but there isn't always a person that knows the package well, or, as you can imagine, they don't always have the time I might like to help me out (as they are the client!).
So anyway, I was wondering if you have any advice for people like me, who don't have close involvement with the web analytics packages they are working with, and don't have time to become experts in multiple packages.
Believe it or not this is a very common situation. And it sounds like such a tough situation to be in. My reply:
Here is the good news, with each passing day there seem to be fewer tools on the top tier which means that you don't have to learn too many tools! :)
There are two parts to your question that I wanted to address separately.
The kinds of metrics that you will analyze and look at and try to decipher will typically stay the same, or similarly close (unless you switch from dramatically different businesses). For example on any new site I actually almost always start with the things I have outlined in this post:
The post outlines the initial diagnostic type analysis I might do, the low hanging fruit that you can impress the client with right away and for each recommendation the post contains "stretch goals".
My recommendation is to try and get really good at that, understanding the base / advanced set of metrics and how you can use them because this will stay the same across your clients (though in some scenarios you'll come with slightly different metrics, like the ecommerce will have slightly different emphasis than non ecommerce).
As your career matures I am positive that you'll have your own arsenal of frameworks that will make the initial set of work straight forward. After that initial work what you do for each client will be unique because of their business, their politics, and the tribal knowledge you'll gather.
The second part of your conundrum is awareness of the tools. In this case sadly it is usually optimal to get some sort of training.
Most web analytics vendors are eager to give this to you, and in your case I am sure your clients will let you play with them. Your goal would be to get to know them a little bit but mostly to figure out how to get to the data that you need to across different tools. So for example where to find Top Landing Pages report in Omniture and CoreMetrics and WebTrends and ClickTracks so you can look at Bounce Rate for each page.
Again over time you'll get smart about the tools as well, worry not if you are not a expert on day one (focus on the first part above, web analytics frameworks).
One last thing, I think you have touched on this but one of the most important things to know is if the tool is installed right, for someone from the outside this can be killer because you might be using garbage data.
Some tools will give you a diagnostic utility, others don't have anything (for those cases we wait for Stéphane to build us something!) but for GA you can use this site:
It is a 100% free tool that will scan your site and tell you if the tool is implemented completely and correctly. Once you fix the errors you'll have confidence in the data you are analyzing.
# 2: Robots Are Out To Get Me: :)
I'm the "do everything web guy" for a small non-profit. Translation: over worked and under funded.
I'm asking if you can point me in the right direction for finding something out. My site gets 150,000+ visits a month. But the problem is that the bounce rate hovers around 70% and the % new visits is around 80%.
When I look at loyalty (got that from one of your blog postings), almost 80% visit only once (loyalty), almost 90% visited today (recency), about 70% visit for 0-10 seconds (length of visit), and almost 70% visit only one page (depth of visit).
There is one small issue I wanted to clarify first, Recency 90% visited 0 days ago would include everyone on your site who is new (because technically they visited the site for the first time, hence "0 days ago"). This is a little confusing and hopefully the team will fix it at some point. To summarize, 0 days ago is everyone on your site who is new (never visited) and those who visit every day (you!). Confusing, yes.
But let me stress that the odds are low (not zero) that robots are causing this.
My advice to you is to go under Traffic Sources, look at where your top three buckets are. Is it mostly search engines? Is it mostly Referring Sites? What's going on? Then dive deeper.
For example if it is Search Engines then which engines are sending traffic, what keywords and I would drill down to the keywords reports and look at the top 50 keywords and bounce rate for each, along with traffic.
Are the high bounce rate keywords relevant to you? That would mean something's wrong with your site in terms of delivering relevant content.
If those keywords are not relevant to you then you got indexed for sub optimal ones and you can see what pages and go address them (get "de-seo'ed" :) or ignore that traffic).
I would also go look at the top landing pages to the site (Content -> Top Landing Pages) and look at the top 25 landing pages to the site and their bounce rate. Pick the ones with high bounce rate and drill down on them and look at Entrance Source (what sites send traffic to this page and they have high bounce – unqualified traffic?) and Entrance Keywords (see above!).
My thought is that by this point you will start to unravel the mystery of what is going on. Especially if it is search the culprit is relevant content (or lack there of) on landing pages. Bye bye robots, hello copy writing! :)
One final recommendation for sites with high bounce, implement a free onexit survey solution like 4Q. Then your customers will tell you why they are bouncing.
E O M.
All joking aside you'll agree that the life of a Analyst is tough.
What did you think of these two "dear avinash" examples? Helpful?
What would you advice Stressed Agency Analyst and Worried About Robot Analyst? Would you advice something different?
If you have faced these situations then how do you deal with them? Please share your own stories and feedback with me and these two wonderful people. Thank you.
Couple other related posts you might find interesting:
- Web Analytics: A Puzzle or A Mystery?
- Standard Metrics Revisited: #3: Bounce Rate
- Excellent Analytics Tip #7: The Adorable Site Abandonment Rate Metric
- I Got No Ecommerce. How Do I Measure Success?
- Top Ten: Signs You Are A Great Analyst
- Web Analytics Career Advice: Statistics, Business, IT & Mushrooms