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Interpreting tests results in some cases will be very easy.  

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Simple observation can provide many clues about what website changes should be made.   

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Also, many users will tell you directly that something is wrong, bad,

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it's not working, or that they don't like something.

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These comments often relate to usability issues but it is important to separate facts from opinion.   

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When providing results, consider the experience each user had.  

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Did they successfully accomplished each task,

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and in each case, where they satisfied with the results?  

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It's very possible for a user to eventually find what they were looking for after a long period of time.  

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This doesn't necessarily mean the website is in good shape.  

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Other times, tests just don't yield clear results.  

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If you're unsure what some of your data means,

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make a note of it so you can review it later and then move on.

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When all is said and done, the key deliverable from your test should be

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a set of recommendations you deliver to the people responsible for your website.  

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It should be a clear list of directives based on your research,  

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the test you conducted, and personal observation.

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The data you collect will help stir you in certain directions  

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when generating recommendations for improvement.

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For instance, if every test user had trouble finding our return policy

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on the Shirts 4 Mike's site, there must be a problem. 

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Sometimes the fix is obvious like adding a link in an expected location but not always. 

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More testing can often reveal the best way to rule out different areas   

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and decide upon the best solution.

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Your recommendations don't have to be produced in the form of one long check list. 

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And in fact, a list like that can be misleading. 

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You should be able to provide background on each item and rank them in order of importance.

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Fixing typos on a page isn't as mission critical as fixing a shopping cart that crashes every time.  

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Therefore, you should organize these proposed fixes into a format that make sense     

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and that's easy to implement especially if you are the one that has to do it.  

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Lastly, understand that while findings can show areas for improvement,

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it can also confirm that something is working.   

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Neither case knowing something works or doesn't work can be equally important.   

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If you can run these tests with three to five people each month or two,

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you'll have plenty of data to keep yourself busy with changes and improvements

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especially if you end up implementing them immediately.    

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And if that's the case, you'll have something new to test the following month.