Need to delete consecutive, unchanged records
For this table:

mysql&gt; SELECT * FROM tracking;
+----+-----+---------------------+-------+
| id | sku | date                | price |
+----+---------------------------+-------+
|  1 |   1 | 2014-08-11 20:31:40 | 10.00 |
|  2 |   1 | 2014-08-11 20:32:05 | 11.00 |
|  3 |   2 | 2014-08-11 20:32:18 |  1.00 |
|  4 |   1 | 2014-08-11 20:32:22 | 11.00 |
|  5 |   2 | 2014-08-11 20:32:26 |  1.00 |
|  6 |   2 | 2014-08-11 20:32:32 |  1.00 |
|  7 |   1 | 2014-08-11 20:33:00 | 12.00 |
|  8 |   1 | 2014-08-11 20:33:03 | 11.00 |
|  9 |   1 | 2014-08-11 20:33:06 | 12.00 |
| 10 |   1 | 2014-08-11 20:33:10 | 12.00 |
| 11 |   2 | 2014-08-11 20:33:17 |  2.00 |
| 12 |   2 | 2014-08-11 20:33:17 |  2.00 |
+----+-----+---------------------+-------+
12 rows in set (0.01 sec)


You can run the following query to search for unchanged prices on consecutive records for the same sku:

mysql&gt; SELECT t1.id, t1.sku, t1.date, t1.price
       FROM tracking t1
       WHERE t1.price = 
          (SELECT t2.price 
           FROM tracking t2 
           WHERE t2.sku = t1.sku 
                 and 
                 t1.date &gt;= t2.date 
                 and 
                 t1.id &gt; t2.id 
           ORDER BY t2.date 
           DESC LIMIT 1 
          );
+----+-----+---------------------+-------+
| id | sku | inserted            | price |
+----+-----+---------------------+-------+
|  4 |   1 | 2014-08-11 20:32:22 | 11.00 |
|  5 |   2 | 2014-08-11 20:32:26 |  1.00 |
|  6 |   2 | 2014-08-11 20:32:32 |  1.00 |
| 10 |   1 | 2014-08-11 20:33:10 | 12.00 |
| 12 |   2 | 2014-08-11 20:33:17 |  2.00 |
+----+-----+---------------------+-------+
5 rows in set (0.00 sec)


Those are the records to be deleted. So:

DELETE FROM tracking t1
WHERE ...


If you have duplicated records (same sku, price and date), it deletes the ones with higher id. This assumes that a record with a higher id will always have the same or higher date (it normally happens due to the auto_increment with no updates).

Please note that this is a correlated subquery, with an efficiency of O(n^2) row operations, where n is the number of records. You can solve this in O(n) programmatically if you can afford O(n) memory in a single table scan. 

EDIT: Changed query for the structure proposed, handling duplicated values.