The importance of understanding analytics BEFORE making any changes to your business based on the data you see there can not be overstated. Online businesses could seriously damage their sales and wrongly assume they were down due to the economy if they don’t realize Web Analytics data is NOT black and white. What it APPEARS to show and what is REALLY true are rarely the same.
Mike Tekula touched on this yesterday in his post SEO & Analytics: Four Useful Ways to Assess Your Organic Traffic:
We often have a pretty simple and straightforward way of looking at a given metric. Example: “a high bounce rate is bad.” But a single metric by itself rarely tell us everything we need to know (see #1 above). A higher bounce rate can actually reflect a positive change.
If your aim is to bring in users who are more likely to be engaged by your content, then an increasing bounce rate combined with an increasing number of pages viewed per visit may be positive. The traffic source (read: keyword) users arrive through plays an important role here.
We MUST stop viewing any metric as “good” or “bad” because in almost every case “it depends”. If traffic goes up – but it all immediately bounces because it comes from a source too general and the visitors simply aren’t interested in your site, more traffic can be bad.
Even more dangerous is making assumptions about the true sources of your conversions. Most Web Analytics programs including Google Analytics attribute sales to the LAST CLICK. Even if you already knew that do you know what it means when applied to actions you may take based on analytics data? Here are some examples:
You never see any sales generated by your most general keywords. ASSUMPTION: They don’t generate sales so they aren’t important or you want to eliminate ppc spending on them. This action could seriously impact your sales because:
- Conversions generated by returning buyers may be attributed to Direct if they type in your Web site URL
- The buyer may have FOUND YOU using the general keyword, found what they wanted, and then returned to your site by searching on a specific keyword phrase. Without the original general keyword they may never have found you but the specific search phrase will be credited with the sale!
- Buyers searching on one PC and then buying using a different PC will not be tracked to the original visit
- Buyers may leave to read reviews or check price comparison sites before buying. If you have links from those other sites the sale will be attributed to them instead of the original visit.
Hopefully you’re still with me. (If this isn’t clear do please comment below and ask any questions you may have.) If that isn’t confusing enough, there are real life examples that explain why some merchants believe their affiliate commissions are too high because affiliate statistics don’t match Google Analytics.
When you start driving traffic from Social Networking sites you may see greatly increased traffic, much higher bounce rates, and a decline in overall conversion rates. One way to determine whether a particular metric is a “good” or “bad” indicator is to segment the traffic (i.e., look at traffic from different sources separately). All traffic does not convert equally so you want to look at conversion rates for each source.
Even then there is a serious problem with making decisions based on last click only analytics data. There is really no way to know what is driving your sales unless you track every click – and that is something that most commonly used analytics programs including Google Analytics – simply do not do.
The real solution is to find a way to track every click. In the meantime be VERY CAUTIOUS about making ANY change – whether that is to your advertising, affiliate programs, shipping costs, traffic generation methods, or anything else!
You should record every change you make in a simple change management plan. This can be a spreadsheet, a notebook or any other method of recording data. Write down the day you make each change and specifically what you changed. Whenever possible only change ONE THING at a time.
One other point: changes you make today do not immediately affect your sales. There is a residual effect due to return visitors. Do NOT make the mistake of assuming that if you stop advertising today and sales are fine tomorrow that you made a good decision. Your marketing efforts from last week will still be bringing in sales.
The residual time is generally 10-14 days for low to medium cost products and services. Even if what you sell is VERY inexpensive and you would think most buyers would make immediate decisions there is STILL a delay of 10-14 days before changes you make today start generating sales and a similar time before what you do today stops generating sales.
Products and services that are more expensive and require complex decisions or configuring will have a longer residual time. When you start making changes if at all possible wait until this residual time has passed and you can evaluate the true effects of your last change before you make another.
Applying Web Analytics is a complex skill. Don’t expect to be an expert immediately; it take time to increase what you know. If you haven’t already signed up we recommend the free ten part Mastering Web Analytics ecourse. If you’re new to analytics start there. If you already have some experience you may find the resources below useful.
Questions and comments are ALWAYS encouraged. We want to hear from YOU!
WEB ANALYTICS EXPERTS on TWITTER:
- KISSmetrics – KISSmetrics Blog – Follow KISSmetrics at Twitter
- Author of Mastering Google Analytics – Follow ValueGuardian at Twitter
- Web Analytics Demystified Blog – Follow Eric T. Peterson at Twitter
- Occam’s Razor by Avinash Kaushik – Follow Avinash Kaushik at Twitter (Occam’s Razor is probably the best known of all Analytics blogs. Not easily understood by beginners; best for more advanced users or very serious students.)
- FutureNow Blog – Follow The Grok at Twitter – Advanced marketing and analytics blog.
- Web Analytics World – Follow WAWorld at Twitter
- WebTrends Blog – Follow WebTrends CEO Alex Yoder at Twitter (WebTrends is a major analytics program more suitable for large to Fortune 500 businesses.)
- Ben Gaines, blog author at Omniture – Follow OmnitureCare at Twitter (Omniture is the other major analytics program used primarily by very large to Fortune 500 businesses.)
UPCOMING WEB ANALYTICS EVENTS:
- SearchFest 2009 Site Analytics Session with Eric C. Peterson
WEB ANALYTICS BLOGS:
The following list starts with those who write for the general public and gets progressively more challenging to understand. The first three are the easiest to follow. Those at the end are more relevant for very large companies (Fortune 500 and major corporations). The comments below may save you some unnecessary clicks.
- KISSmetrics Blog – suitable for those new to analytics
- ROI Revolution – from basics to advanced
- Web Analytics Demystified – basics to advanced concepts – probably understandable for most
- Occam’s Razor by Avinash Kaushik – Very advanced – not suitable for beginners
- Read the latest posts from other best Web Analytics blogs at AllTop
WEB ANALYTICS ARTICLES:
- REVIEW: Free Mastering Google Analytics ecourse (highly recommended)
- DoshDosh: How to Analyze and Improve Your Bounce Rate
- FutureNow: What Your Bounce Rate is Trying to Tell You
- SEO and Analytics: Four Useful Ways to Access Your Organic Traffic
- Start Using Google Analytics with their Getting Started Guide
- Don’t Get Stuck: 5 Ways to Simplify Analytics and Avoid Analysis Paralysis (from KISSmetrics – suitable for all expertise levels)
- Recession Busting Analytics (Occam’s Razor blog – better for advanced users)
- The 8 Most Important Conversion Metrics You Should Be Tracking – Excellent basic information
- 50 Resources for Getting the Most out of Google Analytics
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