The quality of your study has nothing to do with the p-value; it cannot tell you that you need to "improve" your results.
You may be underpowered and need more participants to get the effect that you are looking for. You can try replicating the study again, with a larger sample size, and then doing a small-scale meta-analysis between the two studies. Your effect size, in Cohen's d terms, is 0.25. If the actual effect size is 0.25, you would need 253 people per group to get a significant result, p < .05, 80% of the time.
As I'm typing this out, @Qroid has already pointed out the p-hacking nature of this question. So in addition to what I'm saying, I also agree that it sounds like p-hacking. If you are unfamiliar with the term, here is a first paper and a second paper that I enjoy on the topic. And a third on small-scale meta-analyses and underpowered studies.
Do not decide something needs to be done based on a p-value.
EDIT: I didn't fully understand what you meant by mean classification, (I'm a psychologist by training, so I assumed you were talking about results to some type of cognitive task), so the Cohen's d bit above might be a little off.