I have data regarding the performances of shops on a certain time period: in this data some shops had an active marketing promotion, and some didn't. I would like to understand whether the shops with the promotion improved their performances more than the other group.

I have formulated the problem in the following terms: how many shops improved their performances (wrt the previous time period) among the two groups?
 In this case, my results are

| Group      	| Total # Shops 	| # Shops with improved performances 	|
|------------	|---------------	|------------------------------------	|
| No Promo   	|  37907            | 23762                                	|
| With Promo 	|  1007             | 801                                	|

Running a significance test, data suggests that the difference is significant (p-value < 0.05), so I would have concluded that shops with active promo are more likely to improve their performances.

I would like now to estimate how much the improvement is, so if there's a difference in the mean growth between the two groups. In this case, data are:

| Group      	| Total # Shops 	| Mean Growth % 	|
|------------	|---------------	|---------------	|
| No Promo   	|    37907          |    45%           	|
| With Promo 	|     1007          |    83%           	|



At this point, do I have to run a test on the difference in growth mean to understand if they are significant? If so, which kind of test should be used?