Comments on: Data Quality Sucks, Let’s Just Get Over It

By: Trending Upward | Are you a skeptic? Come on, I know you are!

Trending Upward | Are you a skeptic? Come on, I know you are! — Wed, 06 Aug 2008 00:06:07 +0000

[...] A lot of skepticism around analytics centers around the fact that the numbers are never perfect. Cookie deletion, cookie rejection, turning off javascript can all skew numbers. True. But, let’s heed Avanish Kaushik’s advice and get over it. Why? Because it doesn’t matter. Why doesn’t it matter? Because it’s *off* consistently across your site. That’s why trends are so important. You can argue that the statement, “I got 1,500 visits last month” may or may not be perfectly true. You can’t argue, however, the truth to the statement, “our visits are up 10% over last month.” See the difference? The 1,500 number doesn’t mean anything anyway, even if it were a concrete, true, golden number. Putting it in context with the previous month (or other date range) makes all the difference. You can do the same thing with all your other metrics. [...]

By: Gilligan on Data by Tim Wilson » Blog Archive » Capturing Web Traffic Data — Two Methods that Suck

Wed, 02 Jan 2008 23:21:22 +0000

[...] First off, it is largely a waste of time to try to completely reconcile data from two different web analytics tools. This post really isn’t about that. Mark Twain, Lee Segall, or perhaps someone else coined the saying, “A man with one watch knows what time it is; a man with two watches is never quite sure.” The same is true for web analytics. Thanks to different data capture methods, different data processing algorithms, different data storage schemas, and different definitions, no two tools running concurrently will ever report the same results. The good news, though, is that most tools will show very similar trends. WebTrends preaches, “in web analytics, it’s the trends that matter — that’s why it’s part of our name!” But, even in the broader web analytics community, this is widely accepted. Avinash Kaushik had a great post titled Data Quality Sucks, Let’s Just Get Over It way back in 2006, but it still applies. Read more there! [...]

By: Judah Phillips at Web Analytics Demystified » Blog Archive » Part 1: Your Web Analytics Data Quality Stinks and Here’s Why!

Sat, 11 Aug 2007 16:56:08 +0000

[...] Sampling, sampling, sampling. My friend Avinash Kaushikdoes a good job covering issues around sampling in web analytics. I recommend reading his post! I’ll add that statistical methods applied to web analytics data are completely valid; however, sampling at the site, page, or database level opens the possibility that you miss key data. Sites looking for the “long tail” of visitors and using data sampling or other data trimming methods may not find it. [...]

By: Tooling Around on the IBM Information Server

Tooling Around on the IBM Information Server — Fri, 27 Apr 2007 04:33:54 +0000

Blogtipping Day: fixing the world one data quality problem at a time…

If you slapped the words “data quality” on a hotdog stand someone would offer to buy it before the end of the day. Data quality tools are hot properties so I am BlogTipping three vendor blogs….

By: Web Analytics is so 2006

Web Analytics is so 2006 — Mon, 02 Apr 2007 02:02:43 +0000

[...]
I’m hearing it all over. There’s a new day on the horizon, a day when we in the web world recognizes that none of this is really an exact science anyway, so why pretend?

I’m hearing it all over. There’s a new day on the horizon, a day when we in the web world recognize that none of this is really an exact science anyway, so why pretend?

Enough with the weighted regressions and Taguchi Methods already. It’s time to take the anal out of analysis. Instead of Web Analytics, I propose Web Casualytics. Or Fuzzylytics maybe. Or Estimytics.
[...]

By: People Over Process » Blog Archive » links for 2007-02-17

People Over Process » Blog Archive » links for 2007-02-17 — Sat, 17 Feb 2007 07:26:12 +0000

[...] Data Quality Sucks, Let’s Just Get Over It » Occam’s Razor by Avinash Kaushik “We should simply not expect that data quality will exist on the internet, atleast for now.” Nice list of “my butt hurts!” type excuses… (tags: via:mrchippy data integration databases web2.0 ajax stats) [...]

By: Andy Choi

Andy Choi — Tue, 07 Nov 2006 18:41:25 +0000

Insightful post! Just wonder if you have tried any of the data quality tools from the enterprise software world?

By: this just in » Please Configure Google Analytics Correctly

this just in » Please Configure Google Analytics Correctly — Sat, 02 Sep 2006 02:46:44 +0000

[...] We all know that web analytics data quality sucks and we’re all OK with that. Thanks Avinash! But there comes a point when the data quality is just abysmal. This usually means that there is something wrong with the web analytics application configuration. [...]

By: Chris Furlong

Chris Furlong — Fri, 30 Jun 2006 18:03:10 +0000

Excellent post. I wish that more people outside the analytics community understood that you are never going to get two different tools to give you the same numbers, and that your time is much better spent doing analysis.

By: this just in » It’s The Trending

this just in » It’s The Trending — Mon, 05 Jun 2006 16:33:49 +0000

[...] Second, Avinash Kaushik has a fantastic blog post titled Data Quality Sucks, Let’?s Just Get Over It concerning the quality of analytics data and how to make informed decisions based on your comfort level with the data. He stresses that you will not get 100% accurate data but that doesn’t matter. You can still make informed decisions with the data that your analytics solution provides. It is a really great post and I highly recommend giving it a read. [...]

By: Justin Cutroni

Justin Cutroni — Mon, 05 Jun 2006 14:56:19 +0000

I couldn’t agree more. I can’t tell you how many times our clients ask us to compare statistics from Analytics Package A to Analytics Package B. It’s a time consuming process that usually ends in failure. We try to stress two things to people:

1. Look at the trends in your data
2. Make one change at a time so you can accurately measure the results.

Measuring change to your website is a scientific, controlled experiment. If you start with a baseline statistic and implement controlled change then there will be little doubt as to the results of that change. It doesn’t matter if your baseline is off by 2, 5 or 10 percent from the actual numbers. If you implement a single change then there will be little doubt of its effect when you’re looking at the trends in your data.

I think Caleb touched on this in his comment a couple of weeks ago:

Start with benchmarks, make a report that can be easily shared throughout the organization. Host a meeting to talk about it, then pick one area to take action on that will show some real results and give the credit to the people who actually made the changes (the IT, developers, designers, etc…)

By: Laurent Flores

Laurent Flores — Mon, 05 Jun 2006 09:33:13 +0000

Hi Avinash -

Not sure I have the ability to comment on the technical apsects of your post, but as you said the key is to recognise that data quality is never optimal…once, you know this, what I say to clients, and as decision maker myself, I’d rather know NOW 70 or 80% of the truth rather than 100% (knowing that truth is a “relative” concept of course), to take a decision… Too many “technically oriented people” forget this (I was probaly too much like this in the past, my intial training is in computer science as well), and at the end, the key is to decide and learn over time…specifically from mistakes…At a time where marketers finally recognize that a a lot consumer decisions are “irrational”, data is good but so is Intuition…data dive helps shape the right intuition…to make the right decision…

Cheers
Laurent