Assuming that this is human poly+ve RNA-seq (Illumina), first up see the number of reads you have. 40-50million reads is min. number if you are aiming to do differential expression.
2) Look at the box plot of qual. distrib. in FastQC. A good data would have the majority of plots well above phred score 30 (green region). Depending on read length, boxes for few bases at the end falling below 30 is normal.
3) Then check the plot for "Sequence dupli. level". Don't worry if its shown to be failed as per FastQC. RNA-seq is bound to have duplicates because mRNAs are present in multiple copies. A peak/ hump for x-axis value ">10" or more is good. It means you have sampled the transcriptome well.
4) Check the "Per seq. GC content". Ideally it should be unimodal: a single hump in the centre with the theoretical and observed more or less overlapping. I would be worried if I see two humps.
5) Check "Adapter content" plot
If you have adapter content warning, remove them using any suitable tool (Cutadapt, Trimmomatic etc.). Use a base quality-based filter to clip reads when quality falls below a level. Like "SLIDINGWINDOW" in Trimmomatic.
After quality filtering if you still have good number of reads left, box plots look OK for most of the read length, no mean looking 2nd hump in GC content (a shoulder is OK) and majority of read lengths are towards the higher end (like if you have trimmed 5 bases, then the peak in Seq. len. distrib plot is over 95/96), then your data is good to go (for algn.)
Post algn. a >70% algn. rate is decent. Though I routinely get >85-90% using STAR.
All the above is theory, ultimately it would depend how much you value a particular sample. If you have many and there is one low quality sample you could remove it. If its clinical sample on other hand, you try to salvage what you have.
Check the sample with 5% algn. rate for its FastQC. How many reads it had to start with? Use bedtools to overlap the BAM with exons to find where reads aligned.
Also if you want to dig deep for that sample, check the diagnostic metrics of the sequencing machine.