He also emphasises that the AI doesn’t make choices about language without any human input or oversight. “Every week or every two weeks, Phrasee will come back to us and say, “Hey, why don’t we try these ones out?”
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“And it isn’t Phrasee introducing brand-new language without any human oversight or control – I know that that can sound a little bit scary for many. It’s Phrasee coming to us and saying, “We’ve looked at your language, and we’ve looked at your algorithms; we think we should put these new ten subject lines within the pot and test”. Of course, we have to go through business standards, we have to see if everything is above-board; then we input them into the pot, and we optimise. And then you’ll see, three or four weeks later, three or four have left the pot and are no longer important, and we start seeing the winning subject line on the top.
“It’s something that we’re constantly changing and reviewing. There’s always that element of human review of this language.”
The Phrasee tool also learns based on the language that a brand is already using in their communications, in order to closely replicate the brand’s voice. In other words, it’s following a path laid down by human copywriters, and then optimising the language of each subject line based on performance, and using this to learn about what works.
“The way that the performance optimisation system works is that it learns from past behaviour to project onto the future, while bringing in things that it’s not sure about,” says Malm. “By bringing in all this uncertainty in conjunction with past actions, you can actually create a very strong, highly accurate model, which can take on ambiguity that happens in marketplaces and react very, very quickly. That’s what makes it inherently powerful.