Does this sound familiar? You're in a store, armed with cash and ready to buy something but, after searching for several minutes can't find the item anywhere. You could look around for something else to buy or you could travel to another store. But that would require some hassles - walking out to the parking lot, fighting traffic, burning expensive gas and finding another parking spot.
Now picture this scenario online where, in a fraction of second, a click of a finger will take you to a different store where you're likely to find exactly what you want - a dream for a shopper and a nightmare for a website owner.
As a general rule, the longer it takes your visitors to find their desired products and get to your checkout page, the less likely they will stick around and buy.
There are a number of reasons why your "distance to sale" may be too long: Complex navigation, incomplete information or loads of products with no search feature are just a few.
The Answers are in Your Web Analytics The information in your Web analytics can make it easier to determine the complexity of your website - an important factor in understanding how visitors interact with and move through your site. In some analytics packages there is a report called "clicks to pages" that shows the number of pages visited prior to visiting a specific page.
Suppose you have experienced a decline in online sales from your PPC campaign for a particular product from the same period 12 months ago. It's likely your analytics package will show, on average, how many clicks (or pages) it takes for your prospects to arrive at the shopping cart page. Your report from 12 months ago shows that the average clicks-to-pages metric was five pages. In running the same report for the most recent month, you notice that the average has increased to eight pages.
Depending on the Web analytics package you're using, your clicks-to-pages report may look similar to the one below.
In this report, there are two data columns - Number of Visits and Average Clicks. For our example, we're interested in studying the average clicks to our shopping cart page so we'll want to locate the URL of that page - on this report, https://store.yahoo.com/cart.asp.
We can see that, for the time period reported, that it took an average of eight clicks for site visitors to reach the shopping cart page. Let's get a little more information that will help us determine why.
In some analytics packages, you will find a Conversion Analyst. Here, we can drill down and view the "path to here" option. This will show a path analysis chart similar to the one above that graphically lists the pages visited prior to arriving at our shopping cart page. In this sample, 77.43 percent of visitors who end at the checkout page are coming from /products/coffeemugs.html, while 4.85 percent of visitors are coming from products/knife.html and 1.79 percent come from shippinginfo.html.
If we also run this path analysis report for the same period 12 months ago, we can look for any additional branches of activity between our primary entry page and the checkout page. These added branches could be an indication that our customers are confused or not getting the information they expect. Also, note how many visitors exited your site from one of those new branches of activity.
Once new branches have been identified, take a look at the primary entry page and those new branches for any changes that might have been made in content or navigation. Also consider visitors' expectations prior to their visit. If driving traffic to this primary page from a PPC campaign, check for a strong degree of continuity between your ad creative and the content on the page. A change in PPC ad copy could influence a visitor's navigation behavior.
Note that depending on the size of your site, a path analysis chart may become difficult to manage due to the numerous possible navigation paths. So, it's important to focus on the path navigation for specific products or pages, one at a time.
1. Web analytics should help determine what product and service attributes are important to your visitors. While details for some products seem trivial, those same details could be vital to the visitor's decision- making process.
For example, if we're selling wine gift baskets, the dimensions of the basket may not be important to our visitor, and we could benefit from a cleaner product page by placing that information on a drill down page.
However, if we're selling wine racks, the dimensions are most likely very important and should be listed on the product's main page.
2. Wherever you list a privacy policy link, test displaying text similar to "We value your privacy, and will never sell or share your information" next to the link. Most of the time, that one sentence is all your visitor wants to know. By allaying their fears and avoiding a visit to a privacy policy page, you've removed another distraction that could increase the distance to a sale.
3. Test your modifications to product pages on less-traveled areas of your site. You don't want to risk losing significant amounts of sales on your most popular items while you fine-tune your site.
Think of your Web analytics as a democratically elected reflection of how visitors really get around your site.
When it comes to closing the distance to a sale, remember that not only are you testing your visitor's level of patience, but also competing with any offline distractions. The longer it takes for the sale to be completed, the better the chance that any interruption, even a phone call, can foil a sale.
And keep the big picture in mind. Any minor change in your pages, navigation or ad copy could result in a different experience for the user than originally intended.
One less click for every potential purchase could improve your conversion rate, resulting in more profits and revenue from your existing traffic without any further ad investment.