I am looking at customer data, and created frequency tables (+histograms) for customers with different professional statuses and what the best time is to reach them. Status ranges here from employed, retired, self-employed, unemployed, blank.
For each of these statuses, I expected some variation in terms of when the best time is to reach each type of customer. Intuitively and from experience e.g. employed people, on average, should be available early in the morning or early evening, while unemployed are expected to show a more even distribution. However, the distributions look very similar and the peak hours for all statuses are between 8-11, I am pretty sure that the agents drive this peak. There are more agents working early than in the afternoon.
How can I extract this effect to be able to focus on what the best times to reach are for these different group of customers?