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 Beginners Guide To Web Analytics.
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).
I have a sneaking suspicion that much of this activity is due to "non humans." I just find it hard to believe that such a large amount of my traffic spent less than 10 seconds. But at the same time, GA uses javascript tagging, and I thought that robots didn't bother to execute these (thus, being invisible to GA). If you could point me to resources/reports that I should look at to get to the bottom of this, I'd be indebted.
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.
You are right that most robots don't execute javascript so the behavior you describe (high bounce) would not usually be associated with them (and they won't bounce either unless the landing page has no links on it that go into your site).
There are a couple robots out there who execute javascript, but it is rare that they go after random sites, especially small ones. If you really want to double check then, for Google Analytics, go to Visitors the Browser Capabilities and look under Browsers and OS and Network Properties and if you see something really funny there (like a bit bulk of traffic from a "funny" source) then that could be a clue.
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.
PS:
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
Via 
I can definitely relate to "Stressed Agency Analyst". I think that if you cannot relate to that, at any level, then you probably haven't been working at your agency for long enough.
Agency Analyst life is fast-paced, high-stressed, chock full of various different types of clients and "mysteries", like Avinash likes to say. In a way, you're also a detective / federal agent of the web, discovering clues and solving puzzles.
There are probably dozens of recommendations one could give Mr. / Mrs. / Ms. Stressed Agency Analyst, but the one I'll give is to not rush, to take your time, and focus on the quality of your work and not the speed of it (I find that sometimes the demand for "ASAP" can become overwhelming – managing your level of "ASAP" can go a long way for you).
Thanks AK!
Dear Avinash,
Thank you for your time :-)
P.S. : Great post by the way.
Comment made by Joe Teixeira perfectly describes the reality of agency web analysts. Not only do we need to provide actionable recommendations on improving online marketing campaigns, but we also have to do the following. I’ve added some recommendations to some of these responsibilities- readers: feel free to chime in and add to the list
Be business savvy, understand the nature of the business/client that you work on. Ask yourself, what is the goal of the business, how does it relate to the advertising- this should answer what kind of metrics you want to measure. If the purpose of a website is to sell furniture, but the goals of the ads are to build awareness, you’ll want to look at engagement metrics on the website for users who were directed to the site from the ads. you can look at how well the ads affect sales too, but online conversions may not necessarily be the goal of the campaign (people may want to see furniture on the site, but not buy till they see it in person in the store)
Good grasp of the marketing campaign structure itself (how else would one prove good integration of search and banner/flash ad campaigns with the numbers to back it up) . Could be interesting if you test the results to see if the integration works as according to planned (does it really look as good as it does on paper?).
Know the differences in types of metrics that different data sources can provide (example: should you use comscore or hitwise), which should save you time in knowing where you can find the data. Also, stay on top of new reporting capabilities the vendors will offer. Requires some research on your end, but could be time saving in the long run.
Data cleansing – data shown you reports you retrieve may need to be modified, or is inaccurate. Lobby for dba help if you find yourself consolidating/revising massive amounts of advertising response data from different vendors (happens if you cannot track everything out of the ad-server- and also, the limitied capabilies of such tracking systems- which deserve a post in of itself which leads to my next point)
Customize reports with vendors if possible. Are you using doubleclick/atlas/pointroll/etc to retrieve reports? Is it providing you data that you need? If not, can you work with them to customize reports that will be tailored to your campaigns.
Know basic online marketing and site tracking concepts- probably doesn’t apply to people who are taking time out to read this post :)
Hi Avinash,
Both answers are excellent. Really good thinking on answering the second question. Keep posting more.. not one per week…
Hey Avinash – Love the post! I would definitely like to see more “Ask Avinash” questions answered on your blog.
Working for an Agency myself, I completely relate to the first questions and can see how having a guru like yourself weigh in.
Then there was the second question that was very helpful to simply walk through the question and proposed deconstruction of the problem.
For web analytics we have our KPIs, for great advices we have a KPW: Key Person’s Wisdom with an upper control limit called Avinash Kaushik :)
At eMetrics there was a great session called Advanced eMetrics Management with June Dershewitz (Semphonic), James Gardner (Aquent), Dylan Lewis (Intuit) and Mark Brooks (Mottley Fool). While most of the conference focused on tools, technologies, processes and such, this time it was all about the most important KPI: people. How to manage and grow your career. Really great panel and I wish they will make their presentation available.
Brilliant post Avinash, I am always impressed at how practical and directly useful your posts are.
Have you considered starting a “ask avinash” forum where we can all benefit from your wisdom when you answer the questions you get? If two random emails you shared here are of so much value I wonder how much more we can benefit from having visibility to all of them!
Keep up the great work for the web analtyics community.
Sam
(PS excellent presentations at the eMetrics summit, the one on tuesday on Actionable Web Analytics was the highlight of the conference.)
Reading about other’s experiences always relieves any kind of frustration that I may be feeling at a particular time. It’s just taking the time out of our busy, fast-paced, and high-stressed days to read posts like these.
I value every post that you include on your blog Avinash and the comments from other individuals.
So thank you!
Wonderful post – I love “Dear Avinash”. I think it would be a great recurring feature. -Jen
Joe: “Manage your ASAP” – I sense a great slogan here!
Flavacado: Your generosity is greatly appreciated, you have given some brilliant advice. I think you helped Mr. / Ms. Stressed Analyst way more than I did!
Thank you so much, it shows that you have had lots of experience (and dare I say battle scars :)).
Stephane: You are exceedingly kind but I think you have your limits totally wrong.
Sam: I have thought of a forum but I am already running on fumes and could not possibly do justice to such a worthy cause. I do appreciate the suggestion.
Also as every reader of this blog knows, the awesome Web Analytics Association has a great forum on Yahoo groups. Please check it out:
http://tech.groups.yahoo.com/group/webanalytics/
Jeremy, Nicole, Jen: Thanks for the encouragement, I am going to try and do more future “dear avinash” posts.
I honestly did not think they might be of value, this post was something I published in a pinch (12 speeches in five countries in the next four weeks!).
-Avinash.
Avinash,
As always, another brilliant post. Thank you. The “dear avinash” examples were extremely helpful.
I’d like to share my 4Q experience with ‘bounce rate’.
I run a few different Ecommerce sites and I ran the 4Q survey on all. One of the sites is relatively small in terms of traffic and content and although didn’t have a high bounce rate – it didn’t get enough (by my definition) page views. Some I attributed to not relevant keyword traffic (we had products related to the keyword while people were searching for information related to the keyword). I always wondered why they wouldn’t stick around and at least look at more products. When 4Q was released – I ran the survey and had my answer within a few days from one of the survey respondents. It had to do with navigation. I changed it up the same day and boy the page view graph looks so much sweeter now. :) (I understand higher page views aren’t necessarily a better thing – but for this particular website higher page views are important.)
The navigation being the issue is something I would never have guessed. I run another Ecommerce site which has higher traffic and a similar navigation structure and 4Q revealed navigation was working very well for that site.
I was amazed at how 2 ecommerce sites with similar navigation structures were working so differently. It had to do with the subject matter and the keywords that were driving the traffic. No amount of number data could have solved this for us so quickly.
4Q is brilliant and very useful and I just had to share this in relation to the second example and bounce rates.
Can’t thank you enough for your contribution with 4Q. Thank you.
Manjula
Excellent post, Avinash.
Im always amazed at your analysis skills which you use to give effective practical solutions. Your suggestion of using the Top Landing Pages to drill down further to find the source of “unqualified traffic” was a prime example.
Am looking forward for more. Please keep them coming :)
Jahangir
[…] “Dear Avinash”: Stressed Agency Analyst & Robots Are Out To Get Me! (Avinash Kaushik) […]
Avinash, one of our new clients here had the same problem as your second example. There were thousands of visits that hit one page, and stayed for less than 5 seconds. After some digging, I found that all of the bad traffic came from just two sites. They were a sort of 'referral services' that the client had signed up for.
I can't really do anything about what he signs up for, but I could block that traffic from being reported so it doesn't pollute my data. Would you recommend that?
It's nice to know that I'm not the only one who has to deal with this kind of thing.
Thanks for the blog Avinash.
Are you ever going to speak in the Southeast United States? Like perhaps… Atlanta?
Great stuff! Thanks for sharing, one fresh
idea and you can change the world, keep
up the great work.
For the first example, it would be highly recommended to use debugger tools to figure out how the sites are tagged, manually, especially in areas most reported on. There's no shortcut around it, it is important to know how the data is collected and spot any issues to increase accuracy of reports.