They reduce the apparent entropy inherent in the structure of the original message.

One simple example would be replacing the name in the end tags of xml with a special symbol. You can perfectly recreate the original xml from that but the compressor doesn't have to include the full name again in that place.

A more real-world example is png compression. Each row is assigned a filter which turn the original pixel values into a differential encoding. Most adjacent pixels tend to be similar colors so the values that end up encoded by DEFLATE, the entropy compressor, are mostly close to 0. In the extreme case this will turn a smooth gradient from all different values into a single value throughout the row which the LZ portion or DEFLATE makes very quick work of.

They reduce the apparent entropy inherent in the structure of the original message. Or in other words they tune the message to make use of the strengths of the next stages of compression.

One simple example would be replacing the name in the end tags of xml with a special symbol. You can perfectly recreate the original xml from that but the compressor doesn't have to include the full name again in that place.

A more real-world example is png compression. It's entropy compressor is DEFLATE, which is a combination of Lempel-Ziff and Huffman. This means that it works best with values and patterns that repeat often. Most adjacent pixels tend to be similar colors. So each row is assigned a filter which turn the original pixel values into a differential encoding. This way the values that end up encoded by DEFLATE are mostly close to 0. In the extreme case this will turn a smooth gradient from all different values into a single value throughout the row which the LZ portion or DEFLATE makes very quick work of.