Web analytics is an integral part of any business intelligence portfolio and cannot be avoided in any decision-making phase. But it is perhaps most discussed among online marketers, who require it in order to make the best sales and marketing decisions.
These are often the same users who face a decision between paying for Web analytics tools and using free ones.
Since the time long ago when the release of the free Google Analytics tool created immense noise, significant differences between paid and free tools have emerged.
The biggest advantage of paid Web analytics solutions is the extensive support offered in terms of training, consultancy, and expert advice in measuring every aspect of your Website. Also, free tools normally just show trends and a summary-based view of the data. With paid analytics, it is possible to have much more graphical information, including a summary of data by date presented in dashboards.
Free tools like these may well be sufficient for small and medium-sized businesses. And even for a large enterprise, free tools can act as prototypes to showcase the power and importance of eventually opting for paid Web analytics.
Paid-for Website analytics from suppliers like these will help firms answer queries like the following:
Which keyword(s) or referral source is giving me the best sales activity?
Which geography is giving the best clicks and sales?
Is organic search working well for me? Or is it the inorganic search giving more leads? (Note: Organic search refers results that appear automatically for free; inorganic search results are linked directly to ads or sponsored links.)
Which is my best online marketing campaign?
Who are my visitors in terms of geography, age, browsers, etc.?
What areas of my Website are visitors most interested in?
These reports aren’t the end of what can be done with Website analytics. All the Web intelligence and insights drawn from these tools fall into the area of business intelligence. To be specific, I would call it Website business intelligence.
Users can create spreadsheets and presentations to showcase Website business intelligence. But suppliers offer help here, too. IBM Corp. (NYSE: IBM), for example, has partnered with WebTrends to deliver Web analytics through IBM’s WebSphere Portal Software, a corporate BI management and reporting system.
The growing popularity of Web analytics tools is a clear indication of how important it is for any businesses to extract Web intelligence to optimize the user experience on corporate sites. Only Web analytics can help optimize online marketing campaigns while contributing valuable detail to business intelligence.
— Meer Irfan Ali is a search business analyst and strategist in business intelligence and decision support at Fidelity Business Services India Pvt. Ltd.
Thanks for the overview. There are many factors to consider with web analytics free versus paid
- Timeliness of delivery. Many of the free services are not real time.
- Cost of Switching. The metrics from one vendor will never match the metrics of another vendor (many many reasons). Switching vendors means losing mch if not all of your historical data. Being able to compare August of last year to August of this year.
- Data Quality - If you are lucky enough to have data analysts and actively use the data you will most certainly find data issues. With the free service you are unlikely to get any support/assistance to address this.
There are many issues to consider. As you noted, small site, personal site - why pay?
A business site - much to consider. Free may cost you more in the long run when you factor in data issues and staff time to analyze and address issues.
However, whereever the data is spooled from (either free or paid tools) unless accurate; its just matter how we dig the information of it & derive intelligence of it for optimization of ongoing campaigns/projects or build new/future strategies & plans.
Appreciate your comment. "Hammer" or "Hammering" really makes sense. Good way of relating to humor. In fact, you rightly said wherever the data comes from or which ever tool we use to gather the data "Unless the data used from tool is accurate there is nothing to worry about". ; its all about hammering it & furnishing & using the intelligence we draw from it Also, i completely support your say on google analytics; its indeed excellent.
You are absolutely right. Google analytics is very powerful. In fact, when you are doing immense campaigns using Google AdWords & certainly linking it with Google Analytics, you'd certainly feel very comfortable in devicing dashboards & furnishing intelligence out of it for optimization of your campaigsn, landing pages & not to forget "spending money wisely on campaigns" ;)
Clearly everyone should have a hammer. Whether it should be a very simple one that can only drive small tacks or whether it should be a finely crafted steel headed claw hammer that can withdraw nails is a matter for discussion.
That's how I felt about some of the discussion so far. We really should not be talking about the tools but rather about the job to be done.
I see two main purposes of Web Analytics. You can only manage what you can measure so that is one purpose. You wish to evaluate the performance of your website, hopefully in ways that make business sense. That probably means sales conversions and all the steps that lead up to that.
The other purpose is to help you spot when something unexpectedly is going off track. It may not be something you watch routinely but when you have the time to do a more in-depth review of performance, something comes to light. In practice this is more likely to be highlighted by whatever Google shows you through its Google Webmaster Tools website. However analytics can sometimes expose the unexpected.
Once you have defined the tasks to be done, it then becomes very much easier to define which hammer you should use. That goes for analytics too. I find Google Analytics is excellent for the performance measurement tasks I want to accomplish. It is so easy to get data overload with Web Analytics so think carefully before you commit to high-priced data that you will never really use.
From my experience working on websites owned and operated by large corporations, I've noticed an interesting thing pertaining to the idea of free analytics vs. paid, having worked with both.
Free analytics often provide just as credible information as their paid counterparts. Usually, when companies spring for paid analytics, their employees still have to analyze the data anyway and draw conclusions from it in order to employ the data towards accomplishing goals and hitting targets. Paid analytics will be packaged it in a nicer way, in a pretty folder instead of pdf's and printouts and presented by composed executives in conference rooms. Most often, nothing that in-house employees couldn't have come to. And of course, I am generalizing, I do respect the craft of data analyzing- to do it properly it takes artful research methods and processes attained by education and experience and insight (when done right).
I think it all comes down to accountability- something most people in corporations don't want. This way, when major decisions lead to disaster, they can say "this is what the paid analytics company told us, and we acted on that knowledge" rather than internalizing blame. I like to see these organizations as paid scapegoats. On the other hand, when major decisions lead to positive results, all the corporate sharks are eager to take credit...
The google analytics are quite good and I've even seen enterprises using them, no names please. While some paid analytics offer more services, eg, who's clicking on what links, the free ones are quite robust depending on your uses.
Your comment post was real interesting & informative, thanks for it.
Allthough, i do agree with you that the analytics has yet have a clear cut definiation. Precisely it would mean very diffferent to each industries & segments. However, in general i would refer analytics to be " dig data > warehouse information > dig insights > present valuable intelligence & strategy ". However, to help do this is the "data" as you said could cause in accuracy if is spontaneous & thats the lone reason that most of the web anlaytics solution carry a 1 to 2 days lag data.
Ultimately, requirements change > technologies are rebuilt > technologies are connecting ( like the web to mobile & vice versa with the addon on cloud computing & web3.0 in making ; things would be real interesting) lets wait & watch who wins the race of the best web analytics cum web intelligence provider solution.
I completely agree with you. Probably, Michael's simple 3 points could make the selection more easire too. Also, i am wonderng how mobile analytics would take pace now :) , i guess it could be the next big thing in the anlaytics bandwagon as mobile marketing merged with web is gaining huge momentum.
I support!! i buy in all your 3 points of the web analytics solution being solid(1) with robust support(2) & the availibity of in-house analytics team(3).
Trust me, a smart & business acumen based in-house analytics teams makes job so much easier for the in-house marketing folks to purely focus on marketing to the right set of customers invariably optimizing campaigns & saving monies leading to wise spending.
Allthough, i should mention this which i happened to read in a business article in leading news paprt that today most of the companies (the big ones) have realized the worth of a in-house business anlaytics teams & the recent to join the bandwagon of business analytics are IBM, Accenture etc
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M2M: Rise of the Machines? Not Yet David Weldon In the 1970 science fiction thriller Colossus: The Forbin Project, two giant supercomputers from the United States and Soviet Union secretly join forces to take control of the collective nuclear might of the two countries. In the film, the two machines discover each other's existence, communicate back-and-forth, share their collective data, and cut their human creators out of the process. It is the ultimate example of machine-to-machine communications, or M2M. CLICK FOR MORE
M2M: Rise of the Machines? Not Yet David Weldon In the 1970 science fiction thriller Colossus: The Forbin Project, two giant supercomputers from the United States and Soviet Union secretly join forces to take control of the collective nuclear might of the two countries. In the film, the two machines discover each other's existence, communicate back-and-forth, share their collective data, and cut their human creators out of the process. It is the ultimate example of machine-to-machine communications, or M2M. CLICK FOR MORE
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