All successful businesses begin with an idea of filling a perceived need that has not been addressed. That’s what happened in 1995 when two guys decided that single people looking for love and romance were limited to their small physical environments.
The result of addressing this need was Match.com. Singles could join this online dating service, give some information about themselves, state what they were looking for, let the website do its magic and find them matches to connect with and date.
The matching system was primitive by today’s standards. Everyone was entered into a large database, and matches were made using common keywords in profiles and preferences. But singles were able to meet prospects that they would not have met in traditional ways.
Moving Forward
Once Match proved to be a successful dating service, this industry exploded. Along came plenty of other online dating services, some appealing to the general public and others appealing to specific demographics. Today there are online dating apps for nerds, farmers, so-called elites, seniors, women who want to meet divorced man , fitness buffs, and even clowns, to name just a few.
Still, the matching process remained pretty primitive, there were fraudsters with fake profiles, and there were breaches that lifted personal information of users. All of these issues caused a hesitancy on the part of many.
Enter AI and ML
The transformative power of artificial intelligence and machine learning was not lost to consumer-driven enterprises. Once someone conducts a search on Amazon, for example, they are immediately provided with a host of other related products based upon the preferences and purchases of others who searched for the same product. And then, of course, similar product offers show up on their social media feeds too.
Once dating service entrepreneurs understood the power of artificial intelligence and machine learning, they were anxious to incorporate it into their systems for three purposes:
- Making “more perfect” matches
- Personalizing the dating experience
- Detecting fraudulent activity
- Boosting user engagement
Truly, these technologies have vastly transformed the dating landscape. With over 8,000 (and counting) online dating apps and over 450 million users worldwide, anyone with a smartphone can take advantage of these sophisticated algorithms. Indeed, dating apps are today’s matchmakers.
It’s time to take a look at exactly how AI and ML are used to meet the purposes listed above.
The Roles that AI and ML Play in the Dating Game
In general, these two technologies allow computers to analyze and learn from data they are fed, to identify patterns, and then to “spit out” decisions in four areas, with not a lot of human intervention.
Boosting Matching Algorithms
The primary function of a dating app is to match potential prospects. Traditional methods of matching fed user-provided info – age, interests, location, and preferences into a rather primitive matching algorithm, AI and ML have moved that process to a much higher level by adding much more complex data and analysis of user behaviors on the app. Here’s how:
- AI analyzes user behaviors such as patterns of swiping, methods of communication, time spent on the app, and more.
- Natural Language Processing (NLP) analyzes the content in user profiles and messages, to generate data profiles on personality, communication styles, and interests. The system then can create closer matches to other users who are similar.
- Image recognition and memory: ML algorithms analyze profile pictures to determine compatibility. For example, if a user continually swipes right on profiles with specific physical features, those with similar features will be presented from then on.
Personalization of User Experiences
It’s important that dating apps keep their users satisfied and engaged with the app. Here, AI and ML tailor both the interface and content to individual user preferences.
- Recommendations for Content: Just like Amazon makes recommendations for other products, dating app recommend potential matches, of course, but also recommends articles, in-app events, and such to individual users based upon their preferences and past behaviors
- User Interfaces: AI customizes individual interfaces, showing features that are used often and suggesting new features they might be interested in. It keeps users engaged and coming back.
- Profile Recommendations and Suggestions: If AI sees that a user profile is not getting a lot of play, it will recommend changes to the content and photos based on what it knows will work better.
- Additional Recommendations: When two users connect and begin to communicate, AI can make suggestions for icebreakers based on both users’ profile and behavior. And it may also present recommendations for that first IRL date.
Detecting Fraud
Scammers and catfishers have traditionally loved online dating apps. They create fake profiles and then use them to connect with users for nefarious purposes.
Dating apps have upgraded their security systems over the years, but AI and ML have added a much more sophisticated level of detection to provide a safer dating environment.
- Detection of anomalies: ML can identify patterns of behavior that are indicative of fraud, and that alerts administrators to require additional identity information or to suspend accounts until identities have been verified
- Verification of Images: AI-powered image recognition can detect if photos exist elsewhere on the Internet and expel those using such images.
- Monitoring user behavior. Most apps depend on users to report any violations of their standards of behavior. But AI also monitors user interactions and flags suspicious behaviors such as requests for money or confidential personal information. Those accounts are suspended or expelled pending investigation.
Boosting Engagement of Users
A dating app’s success depends on keeping users satisfied and using that app regularly. To do this, AI and ML do the following:
- Use of AI-powered chatbots to help conversations – suggesting icebreakers or even responding to messages when users are busy and cannot be on the app.
- Analysis of emotions: AI can detect when a user is unhappy or frustrated by the tone of their messages and then intervene with suggestions and support.
- ML can suggest gaming experiences based on user behavior patterns, keeping them engaged and coming back.
Online Dating is Here to Stay
It’s a part of our current consumer culture and behavior. As AI and ML continue to refine the whole process, smartphones continue to be the method to find love and romance from anywhere, at any time. It’s the “now” of dating.