{"id":1041,"date":"2009-03-10T22:40:16","date_gmt":"2009-03-11T04:40:16","guid":{"rendered":"http:\/\/www.lucindah8.sg-host.com\/?p=1041"},"modified":"2019-04-02T01:10:25","modified_gmt":"2019-04-02T06:10:25","slug":"analytics","status":"publish","type":"post","link":"https:\/\/growmap.com\/analytics","title":{"rendered":"Don’t Make ANY Changes Based on Web Analytics Until You READ THIS FIRST"},"content":{"rendered":"

The importance of understanding analytics BEFORE making any changes to your business based on the data you see there can not be overstated.<\/strong><\/em> 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.<\/strong><\/em><\/p>\n

Mike Tekula touched on this yesterday in his post SEO & Analytics: Four Useful Ways to Assess Your Organic Traffic<\/a>:<\/p>\n

We often have a pretty simple and straightforward way of looking at a given metric.\u00a0 Example: \u201ca high bounce rate is bad.\u201d But a single metric by itself rarely tell us everything we need to know (see #1 above).\u00a0 A higher bounce rate can actually reflect a positive change.<\/p>\n

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.\u00a0 The traffic source (read: keyword) users arrive through plays an important role here.<\/p><\/blockquote>\n

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<\/a>.<\/p>\n

Even more dangerous is making assumptions about the true sources of your conversions<\/a>. 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:<\/p>\n

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:<\/p>\n