Optimizing my query

Here’s my query:

DECLARE @monthStartDate date;
DECLARE @monthEndDate date;
    
SET @monthStartDate = DATEFROMPARTS(2020,6,1);
SET @monthEndDate = EOMONTH(@monthStartDate);
     
SELECT @monthStartDate, MIN([Date]), @monthEndDate, GroupId, TypeId,
    COUNT(UserID) as 'CountTotal',
    SUM(CASE WHEN [IsA] = 1 THEN 1 ELSE 0 END) as 'CountA',
    SUM(CASE WHEN [IsB] = 1 THEN 1 ELSE 0 END) as 'CountB',
    SUM(CASE WHEN [IsC] = 1 THEN 1 ELSE 0 END) as 'CountC',
    SUM(CASE WHEN [IsEven] = 1 THEN 1 ELSE 0 END) as 'CountEven',
    SUM(CASE WHEN [IsOdd] = 1 THEN 1 ELSE 0 END) as 'CountOdd',
    SUM(CASE WHEN [IsEven] = 1 AND [IsA] = 1 THEN 1 ELSE 0 END) as 'CountAEven',
    SUM(CASE WHEN [IsOdd] = 1 AND [IsA] = 1 THEN 1 ELSE 0 END) as 'CountAOdd',
    SUM(CASE WHEN [IsEven] = 1 AND [IsC] = 1 THEN 1 ELSE 0 END) as 'CountCEven',
    SUM(CASE WHEN [IsOdd] = 1 AND [IsC] = 1 THEN 1 ELSE 0 END) as 'CountCOdd',
    SUM(CASE WHEN [IsEven] = 1 AND [IsB] = 1 THEN 1 ELSE 0 END) as 'CountBEven',
    SUM(CASE WHEN [IsOdd] = 1 AND [IsB] = 1 THEN 1 ELSE 0 END) as 'CountBOdd'
FROM MyTable
WHERE [Date] >= @monthStartDate AND [Date] <= @monthEndDate
GROUP BY [Date], GroupId, TypeId
ORDER BY Date, GroupId, TypeId

which selects from this table:

SET ANSI_NULLS ON
GO

SET QUOTED_IDENTIFIER ON
GO

CREATE TABLE [MyTable](
    [UserID] [varchar](32) NOT NULL,
    [Date] [date] NOT NULL,
    [GroupId] [varchar](16) NOT NULL,
    [IsEven] [bit] NOT NULL,
    [IsOdd] [bit] NOT NULL,
    [TypeId] [int] NOT NULL,
    [IsA] [bit] NOT NULL,
    [IsB] [bit] NOT NULL,
    [IsC] [bit] NOT NULL,
 CONSTRAINT [PK_Http_Uniques] PRIMARY KEY CLUSTERED 
(
    [Date] DESC,
    [GroupId] ASC,
    [UserID] ASC
)WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY]
) ON [PRIMARY]
GO

ALTER TABLE [MyTable]  WITH CHECK ADD  CONSTRAINT [CK_MyTable_Period] CHECK  (([IsIn]<>(0) OR [IsOut]<>(0)))
GO

ALTER TABLE [MyTable] CHECK CONSTRAINT [CK_MyTable_Period]
GO

It works, but the table is going to have millions of rows eventually, and I’m obviously cautious about performances.

Do you see a way to optimize this query? Thanks.