When it comes to loyalty and referrals, good customer service that exceeds expectations rules. Most of you probably think you know that, but how many of you really implement it in your business? Top-notch customer service is not just something that you hope makes your company superior to your competitors. It’s truly a table stake for success.
Nowhere is this more true than when you have made a mistake or inconvenienced a customer, and how you handle that. Maybe you shipped to the wrong address or delivered the wrong product. Perhaps there was a bug in your system that prevented a customer from being able to log in. Maybe it wasn’t even your fault, but if you can’t turn that negative experience into a positive one, the customer probably won’t be coming back.
Your web analytics are important. It’s critical that you are able to measure the activity on your website accurately. I’ve said it from the very beginning: your analytics package is your most valuable marketing tool. That’s one reason I’ve been urging people to upgrade to Universal Analytics from their old Google Analytics implementation. There is a great deal of added functionality with UA.
But there’s an unexpected issue that comes along with Universal Analytics: Referral Spam. This isn’t a reason not to upgrade to Universal Analytics (I’ll talk about how to eliminate most referral spam in a minute), but referral spam can seriously affect the usefulness of your analytics—especially for small and medium sized sites.
For seemingly straightforward tasks, such as signing up for a company’s loyalty program, many lay people probably think an effective User Experience (UX) just takes common sense. But designing a good UX usually requires much more thought. Many facets of a good UX, such as maintaining a consistent message from ad to landing page, ensuring that you have sufficient offline resources to support the added interest from the website, and performing the right testing, are often forgotten in many new implementations.
Let’s look at an example of a registration process that is experiencing some issues, and how it can be improved.
For the most part, people think of Google Analytics as a quantitative tool that only tells you what has happened on your site, but not why. And that’s mostly true. Google Analytics can give you clues to things like why visitors are not converting by looking at things like landing pages with high Bounce Rates or creating segments that might lead to a group of similar visitors who are not converting.
But for the most part, you still have to make hypotheses about what is going wrong. If you want to find out why those things are happening, if you want to gain insight into why your users are behaving the way they are, you generally have to turn to more expensive tools, such as usability studies or session recording tools.
However, one component of Google Analytics actually can provide some clues into what your users are thinking while on your site. That’s the Site Search section of reports. If your website has a Search function, you’ll want to set up GA to track its usage. It’s easy, and will provide you plenty of helpful information.
We are often asked by potential clients for more information and examples on just how we go about optimizing a landing page for conversions. Each project is obviously very different, but examples do go a long way toward illustrating some methods of improving certain kinds of landing pages. Here is an example of a project we just finished recently to help a small ecommerce website increase sales.