Machine learning: does personalised marketing sound the death knell for PR?

Netflix. Google maps. Spotify. Predictive text. Machine learning is all around us and getting more and more sophisticated with every piece of data we reveal about our preferences and likes.

I’d be lost without Google Maps (literally). I’m uncomfortable about all the data it is capturing about me, but the gain is worth whatever privacy I am giving up … even though I’m not entirely sure what that is. That’s how I’ve been seeing machine learning – a risk-benefit trade off.

I had my eyes opened to the world of possibility of machine learning by the brilliant Marie Davies, Head of Customer Solutions at Google this week. In her mind-blowing talk at the Network Ireland event, Marie told us that, today, there is 7x more data created daily than was created in the whole of 2010 … it is way too much for humans to process and almost impossible for marketers to cut through. Enter machine learning, it can serve consumers information tailored for them and allow marketers find their ideal customer and identify what message to show them.

But where do reputation and trust fit in a world of such personalised sales and marketing? Will we be served tailor made solutions that mean we drop all checks and balances on the integrity of the product and the company/people behind it?

Of course not. Mobile has transformed consumer behaviour … we are more impatient, demanding and curious. But we still buy from people and brands we trust, and increasingly ones with a greater purpose than simply making a financial return.

As the physical and digital worlds merge, good storytelling remains critical to bring brands to life. Machine learning won’t be eating PR for breakfast, but it might help us serve it in a better way.

I now understand machine learning a little better, thanks to a presentation from the brilliant Marie Davis from Google at a Network Ireland event this week. But it got me thinking … where do reputation and trust fit in a world of totally personalised sales and marketing? See where I netted out in this short article.