In order to get more specific with our audience, we set up our targeting to focus on those people that Facebook says are interested in moving. We narrow our age range slightly to exclude those too young to (probably) be looking to sell their home, and also include some demographic and behavioral targeting traits. We target those who are “likely to move” and those within a range of incomes and net worths that we like:
Then how can someone afford to pay $54.20 per click if it does not generate profit? The answer is simple: they are spending that money to build a brand and they are not focused on the profitability on that individual click; they are focused on profitability over time and they most likely have a budget assigned to building that brand. Not having to focus on achieving profit for individual click puts a company at a tremendous advantage for displaying their brand prominently in search results. It also makes it harder for profitability based marketers to compete.
For example, say you have a clinic in Des Moines, Iowa. Someone looking at your social media advertising in California isn’t likely to come to your clinic. A geotargeted campaign would help you find social media users that need your clinic and live in your area. And if you have multiple locations, you can run geotargeted social media ads in each area where you want to increase your customer base.
Exhaustive – Your keyword research should include not only the most popular and frequently searched terms in your niche, but also extend to the long tail of search. Long-tail keywords are more specific and less common, but they add up to account for the majority of search-driven traffic. In addition, they are less competitive, and therefore less expensive.
CTAs match user intent inferred from content. Here is where you’ll evaluate whether the CTAs match the user intent from the content as well as the CTA language. For instance, if a CTA prompts a user to click “for more information,” and takes them to a subscription page, the visitor will most likely be confused or irritated (and, in reality, will probably leave the site).
As UX designers, we should go out there and collect as much data as possible before building a real product. This data will help us to create a solid product that users will want to use, rather than a product we want or imagine. These kinds of products are more likely to succeed in the market. Competitive analysis is one of the ways to get this data and to create a user-friendly product.
The Java program is fairly intuitive, with easy-to-navigate tabs. Additionally, you can export any or all of the data into Excel for further analysis. So say you're using Optify, Moz, or RavenSEO to monitor your links or rankings for specific keywords -- you could simply create a .csv file from your spreadsheet, make a few adjustments for the proper formatting, and upload it to those tools.