In-Scope: Is love just an algorithm away?

Courtney Doddridge is a Social Insights Executive for OMD Insights, using social intelligence to identify consumer behaviour to inform a range of data-lead solutions.


Picture this – it’s a warm, balmy Saturday evening and you’re at a rooftop bar with your girlfriends that you’ve wanted to try for ages. You’ve got a nice dress on and you’re wearing your new heels for the first time. You’ve had one prosecco so you’re feeling a little flirty. You see a tall, dark and handsome man at the other end of the bar. The liquid courage encourages you to go over and say hi. He buys you a drink, you tell a joke, he laughs – you’re getting along like a house on fire. Before he leaves to meet his friends, he asks to catch-up for another drink sometime. You put your number in his phone with a wink-emoji.

But wait! With the likes of Tinder and Bumble people don’t meet in bars anymore, they meet online. Would you put your future in the hands of a computer? Is love really just an algorithm?

Artificial Intelligence (AI) used to sound like “technology of the future”, but now it’s a part of everyday life as brands adopt this technology to meet consumer expectation. Interestingly, we are beginning to see dating apps like Tinder using AI to take the guesswork out of dating, basing your perfect match on numbers instead of butterflies.

Although online dating isn’t a new concept, with Match.com launching in 1995, using AI and algorithms is. It’s changed the dating game forever. We’ve seen the landscape change as technology and social media becomes engrained into our lifestyles. We are shortening our attention span and becoming less tolerant of poor online experiences.

Dating apps, like Bumble, Happn, Hinge and The Inner Circle, are coming onto the market to incorporate technology seamlessly into consumer’s quest for a partner. Happn accesses your location to personalise your feed with users you’ve physically crossed paths with, whilst Hinge uses connections on Facebook to match you with friends of friends. These dating apps have been building momentum since Tinder’s launch in 2012 which changed dating into a hookup game, having been referred to as the “king of the dating hill”. These apps continue to generate a significant volume of social mentions, with over 60K in the last year.

As technology becomes more of a life assistant, we are putting more trust into it making important life decisions on our behalf, like finding a partner. Tinder’s ‘Super Like’ feature has undergone an upgrade with AI predicting which people a user will want to ‘Super Like’ using historical data and algorithms. Whilst Hinge has been testing a new machine learning feature, ‘Most Compatible’, to help find the perfect match.

AI is revolutionising the dating app space by improving it in four main ways:

  1. Improving the quality of matches
  2. Moderation of users’ online experience
  3. Improving security
  4. Helping users improve the quality of content by giving feedback on their profile

This trust in AI has also been key to making US dating apps, like Raya, The League and BELONG, more premium and exclusive. Professionals are putting faith into these apps to set them up with successful, educated and wealthy partners. BELONG was the first dating app to use AI and machine learning to give users a curated experience, with personalised matches and social experiences for accomplished individuals.

But is it really working? Are computers better at matching us with our soulmate than we are? Are we really that predictable when it comes to love? We’ll have to wait and see. Being a very new concept, we don’t know if AI is the perfect matchmaker… yet. Maybe we’ll see an increase of Tinder success stories and less divorce. Only time will tell.

But it’s not just dating apps who are using AI, other brands and services are adopting algorithms and machine learning techniques to improve the consumer’s experiences in all aspects of their lives.

  • Sephora has a chatbot that shares beauty advice, content and product suggestions on Kik using data from its quiz.
  • Spotify uses AI and machine learning to provide personalised recommendations for similar music based on users’ previous listening experience.
  • Amazon’s Alexa and Echo smart speakers get smarter over time and enables human-like interaction and problem-solving.
  • ANZ employs a “digital assistant” called Jamie to help on 30 banking topics.
  • The Hilton Hotel has a “robot concierge”, called Connie, who gives guests quick access to personalised information about the hotel and surrounding areas.
  • Netflix uses AI to provide bespoke recommendations based on what users like rather than what they watch, as well as personalising the video frame to a still-image which appeals to the viewer.
  • Barcelona-based start-up, Badi, uses AI to connect compatible roommates and available rooms in Spain using personal data and living preferences.

So now you can use Tinder to set up your perfect date, ask Sephora’s chatbot what makeup to wear to show your best angles, listen to a personalised playlist on Spotify on your Amazon Alexa while getting ready and check your bank balance with Jamie. If the date goes well, you can talk to Connie about a hotel room, or you can always “Netflix and chill” where you might need to introduce the roommate to Badi. It seems AI really has all aspects of the modern dating game down to a fine art!

But what are the implications of AI for brands and marketers? AI is the future.

If you’re not thinking about it, you should be. Forbes claims that “AI will transform marketing in the future”.

Consumers’ attitudes towards brands are changing. We want brands to facilitate meaningful experiences as we shy away from traditional advertising and use adblocking technology to filter out the noise. There is a demand for brands to offer personalisation at scale. However, this has moved far beyond human capacity with an increasing amount of data points and sensor networks. This is where AI comes in as brands shift their behaviour to meet evolving expectations.

AI uses algorithms and machine learning to understand the consumer better than they do themselves. It understands how consumers think, feel and behave, while it simultaneously identifies patterns, trends and predicts how consumers will respond. It speaks to consumers’ emotional drivers and is extremely predictive and persuasive. This data feeds into AI techniques and assists in meeting consumer expectations by creating experiences, like chatbots, digital assistants and personalised content. Brands and marketers who are slow to integrate AI need to take this into account as competitors inevitability enter the “AI arms race”.

AI has well and truly entered our day-to-day life, like what we watch on Netflix or what we listen to on Spotify, however with apps like Tinder and Hinge, it’s clear that it has entered our lives in the most intimate way. We have put an increasing amount of trust into technology that we trust its judgement better than our own. If this doesn’t sound like an episode of Black Mirror, then I don’t know what does.

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