# Adding Seasonality vs including Day of the Week in Time Series

I'm dealing with time series data about sales in a supermarket.

When I fit the model using auto.arima(data), I don't get any seasonal component (weekly) and if I impose a seasonal component I get 'no arima suitable model was found'.

Then I fitted a new model, ARIMAX, using 6 day of week regressors( I omitted one to avoid collinearity) and I found them significative by calculating the p value (being the coefficients MLE estimates they are asimptotically normal).

Am I missing a conceptual difference between these 2 models??