Problem regarding calculating correlation approach?
Most probably, you are using Pearson's correlation method. This method is used for two Continuous features.
Here, both the price_drop and the OHE features are Binary Categorical features.
So, you can use these methods -
Phi - Phi is a measure of the degree of association between two binary variables      (two categorical variables, each of which can have only one of two values)
Crammer's V - Cramer’s V is an extension of phi for tables larger than 2×2.
Both are extensions of the Chi-square test of Independence.
Since both the Features have 2 values, both of the above methods will output the same result.
# dataset is your DataFrame
s1 = dataset['Status']
s2 = dataset[product_type_OHE_01]

import pandas as pd
from scipy.stats import chi2_contingency
n = len(s1)
r,c = s1.nunique(), s2.nunique()
matrix = pd.crosstab(s1,s2).values
chi_sq = chi2_contingency(matrix)

phi = np.sqrt(chi_sq[0]/n)
cramm_V = np.sqrt(chi_sq[0]/(n*min(r-1,c-1)))

print(phi, cramm_V)