Post by account_disabled on Mar 4, 2024 8:24:29 GMT
The take. So I want to make sure that youre all set and prepared to have really good user interviews. All it takes is a little practice and preparation. Its helpful to think of it like this. So the data is kind of telling us what happened. It can tell us about online behaviors things like keywords keyword volume search intent. We can use tools like KeywordTool.io or Ubersuggest or even Mozs Keyword Explorer to start to understand that. We can look at our analytics entry and exit pages bounces pages that get a lot of views all of that stuff really important and we can learn a lot from it. But with our interviews what were learning about is the why. This is the stuff that online data just cant tell us.
This is about those offline behaviors the emotions beliefs attitudes that Greece Mobile Number List drive the behaviors and ultimately the purchase decisions. So these two things working together can help us get a really great picture of the whole story and make smarter decisions. So say for example you have an online retailer. They sell mainly chocolatedipped berries. Theyve done their homework. Theyve seen that most of the keywords people are using tend to be something like chocolate dipped strawberries gifts or chocolate dipped strawberries delivered.
And theyve done the work to make sure that theyve done their onpage optimization and doing a lot of other smart things too using that. But then they also noticed that their Mothers Day packages and their graduation gifts are not doing so well. dropoffs around that product description page and a higher cart abandonment rate than usual. Now given the data they had they might make decisions like Well lets see if we can do a little more onpage keyword optimization to reflect whats special about the graduation and Mothers Day gifts or maybe we can refine the user experience of the checkout.
This is about those offline behaviors the emotions beliefs attitudes that Greece Mobile Number List drive the behaviors and ultimately the purchase decisions. So these two things working together can help us get a really great picture of the whole story and make smarter decisions. So say for example you have an online retailer. They sell mainly chocolatedipped berries. Theyve done their homework. Theyve seen that most of the keywords people are using tend to be something like chocolate dipped strawberries gifts or chocolate dipped strawberries delivered.
And theyve done the work to make sure that theyve done their onpage optimization and doing a lot of other smart things too using that. But then they also noticed that their Mothers Day packages and their graduation gifts are not doing so well. dropoffs around that product description page and a higher cart abandonment rate than usual. Now given the data they had they might make decisions like Well lets see if we can do a little more onpage keyword optimization to reflect whats special about the graduation and Mothers Day gifts or maybe we can refine the user experience of the checkout.