Translating a business problem into a machine learning solution: job-adds website
With this kind of general problem there are many possible approaches, and I can't list them all.  In general, you want to go with the simplest model that creates value over a more naive approach.  So we can look at the different approaches, ranked by complexity, and see what you need for each.  This is the order I would try for this analysis:

(1) The simplest approach is just contact a flat 20%, drawn randomly.  This is very easy to do, but hopefully it can be improved upon.

(2) Next, you can try an approach based on the basic statistics of the problem at hand.  For example, you can calculate for those employers which previously placed ads, how many applications* did they get.  And then start with the ones that got the most, and work your way down.

(3) Now that you have baselines sets from doing a blind and then a basic descriptive analytics approach, you can try something a bit more complicated.  Assuming you have the text from the past ads, you can mine that text for features which might be descriptive of what they are looking for.  If the employers placed multiple ads, you can combine those and look for features in the aggregate.  Once you do the same with the resume data, you can create a recommendation engine to match potential employers with employees.  You can then use that data to determine which possible employer is most likely to have potential matches in your client pool.  As a side effect, this engine can also guide your clients to which jobs might be the best matches.  There are many variations which you can use here.  For example, for the recommendation engine, you may want to weight your client sample towards clients which have logged in the most recently, or most frequently, so or you can just filter out the "stale" clients who haven't really been looking recently.

*An alarm bell went off when you said you know who applied.  Are you sure?  Or do you just have clickthrough statistics to know whether they started an application?  How do you know that they applied?  The first rule of real world data analytics is that you need to be skeptical of your data and especially of what you think your data represents.