How does one investigate the performance of a BULK INSERT statement?
As far as I can tell you can optimize a bulk insert in a very similar way that you'd optimize a regular insert. Typically, a query plan for a simple insert isn't very informative so don't worry about not having the plan. I'll go over a few ways of optimizing an insert but most of them probably don't apply for the insert you specified in the question. However, they could be helpful if in the future you need to load larger amounts of data.
1. Insert data in clustering key order
SQL Server will often sort data before inserting it into a table with a clustered index. For some tables and applications you can improve performance by sorting the data in the flat file and letting SQL Server know that the data is sorted through the ORDER argument of BULK INSERT:

ORDER ( { column [ ASC | DESC ] } [ ,... n ] )
Specifies how the data in the data file is sorted. Bulk import performance is improved if the data being imported is sorted according to the clustered index on the table, if any.

Since you are using an IDENTITY column as the clustered key you don't need to worry about this.
2. Use TABLOCK if possible
If you are guaranteed to have only one session inserting data into your table you can specify the TABLOCK argument for BULK INSERT. This can reduce lock contention and can lead to minimal logging in some scenarios. However, you are inserting into a table with a clustered index that already contains data so you will not get minimal logging without trace flag 610 which is mentioned later in this answer.
If TABLOCK is not possible, because you can't change the code, not all hope is lost.  Consider using sp_table_option:
EXEC [sys].[sp_tableoption]
    @TableNamePattern = N'dbo.BulkLoadTable' ,
    @OptionName = 'table lock on bulk load' , 
    @OptionValue = 'ON'

Another option is to enable trace flag 715.
3. Use an appropriate batch size
Sometimes you will be able to tune inserts by changing the batch size.

ROWS_PER_BATCH = rows_per_batch
Indicates the approximate number of rows of data in the data file.
By default, all the data in the data file is sent to the server as a single transaction, and the number of rows in the batch is unknown to the query optimizer. If you specify ROWS_PER_BATCH (with a value &gt; 0) the server uses this value to optimize the bulk-import operation. The value specified for ROWS_PER_BATCH should approximately the same as the actual number of rows. For information about performance considerations, see &quot;Remarks,&quot; later in this topic.

Here is the quote from later in the article:

If the number of pages to be flushed in a single batch exceeds an internal threshold, a full scan of the buffer pool might occur to identify which pages to flush when the batch commits. This full scan can hurt bulk-import performance. A likely case of exceeding the internal threshold occurs when a large buffer pool is combined with a slow I/O subsystem. To avoid buffer overflows on large machines, either do not use the TABLOCK hint (which will remove the bulk optimizations) or use a smaller batch size (which preserves the bulk optimizations).
Because computers vary, we recommend that you test various batch sizes with your data load to find out what works best for you.

Personally I would just insert all 695 rows in a single batch. Tuning the batch size can make a big difference when inserting lots of data though.
4. Make sure that you need the IDENTITY column
I don't know anything about your data model or requirements, but don't fall into the trap of adding an IDENTITY column to every table. Aaron Bertrand has an article about this called Bad habits to kick : putting an IDENTITY column on every table. To be clear, I'm not saying that you should remove the IDENTITY column from this table. However, if you determine that the IDENTITY column is not necessary and remove it that could improve insert performance.
5. Disable indexes or constraints
If you're loading a large amount of data into a table compared to what you already have then it may be faster to disable indexes or constraints before the load and to enable them after the load. For large amounts of data it is usually more inefficient for SQL Server to build an index all at once instead of as data is loaded into the table. It looks like you inserted 695 rows into a table with 11500 rows, so I would not recommend this technique.
6. Consider TF 610
Trace Flag 610 allows minimal logging in some additional scenarios. For your table with an IDENTITY clustered key, you would get minimal logging for any new data pages as long as your recovery model is simple or bulk-logged. I believe this feature is not on by default because it may degrade performance on some systems. You would need to test carefully before enabling this trace flag. The recommended Microsoft reference still appears to be The Data Loading Performance Guide

I/O Impact of Minimal Logging Under Trace Flag 610
When you commit a bulk load transaction that was minimally logged, all of the loaded pages must be flushed to disk before the commit completes. Any flushed pages not caught by an earlier checkpoint operation can create a great deal of random I/O. Contrast this with a fully logged operation, which creates sequential I/O on the log writes instead and does not require loaded pages to be flushed to disk at commit time.
If your load scenario is small insert operations on btrees that do not cross checkpoint boundaries, and you have a slow I/O system, using minimal logging can actually slow down insert speeds.

As far as I can tell this doesn't have anything to do with trace flag 610, but rather with minimal logging itself. I believe the earlier quote about ROWS_PER_BATCH tuning was getting at this same concept.
In conclusion, there probably isn't much that you can do to tune your BULK INSERT. I wouldn't be concerned about the read count that you observed with your insert. SQL Server will report reads any time you insert data. Consider the following very simple INSERT:
DROP TABLE IF EXISTS X_TABLE;

CREATE TABLE X_TABLE (
VAL VARCHAR(1000) NOT NULL
);

SET STATISTICS IO, TIME ON;

INSERT INTO X_TABLE WITH (TABLOCK)
SELECT REPLICATE('Z', 1000)
FROM dbo.GetNums(10000); -- generate 10000 rows

Output from SET STATISTICS IO, TIME ON:

Table 'X_TABLE'. Scan count 0, logical reads 11428

I have 11428 reported reads but that is not actionable information. Sometimes the number of reported reads can be reduced by minimal logging, but of course the difference cannot be directly translated into a performance gain.