There are a lot of ways to see how well a recommender works and I think it really depends on your final goal. A list of evaluation metrics are here that might be useful to looks through. Although a measure like Accuracy/Precision/RMSE might suit your needs.
For simplicity, lets say you have a year worth of historical sales. You can build your system on the first 8 months of sales, then for each following month you can see what products would be recommended in that month and what products were actually purchased in that month. So within that you can get an idea of how well it is performing (of the 5 products someone bought, we had all 5 in the in the spots 1,2,6,8,9 of the top-10 list). You would want the product purchases to be closer to the top, which is why ranking metrics could be useful for you.
Of course there is a lot more to consider, but I think this is a good place to start. Are you trying to increase the pure number of sales or the revenue? Do certain products sell more depending on seasons/holidays? Are you using ratings or just associated sales (how do you recommend new products?). Factors like these can change your recommender and how you would want to evaluate it.