Value Propositions… is there such a thing as too many?

First thing anyone asks after introducing the idea behind Challengr is ‘what makes you different?’ The technical translation of what they are really asking for is: ‘what are your value propositions?’

I always had a quick answer to this, but the answer was never really the same every time. Early on, I figured I should really nail this down and just write out what I thought were the concrete value props so I would be a little more consistent in my messaging.

So here they are, Challengr’s Value Propositions:

  • Personality first, Looks second — The largest items on the discover page are the Challenge cards, so you catch people’s attention with the creativity / interest / uniqueness of your challenge, not just your face. Yes you definitely still can see what the person looks like before responding, it just isn’t the leading trait for discovery.

  • Less anxiety to post — No need to come up with clever user profile text to stand out. “Talk about yourself” is actually a pretty difficult thing to do, especially when you only have a paragraph to do it in. Instead, you can search and browse through all the different Challenges until you find one that you relate to and your response can do the talking for you. It is pretty straightforward to respond to “What was the last podcast you listened to?”

  • No pick up lines — Your response to a Challenge is your pickup line, and better still, it is directly answering a call to action by the other person. After they like your Response and you start direct messaging, instead of ‘hey’ the opening is a conversation about the response… a lot more interesting and more likely to result in a date.

  • Less Ghosting, More dates— Since matching requires a little bit more effort than a simple swipe and revolves around a shared interest (Challenge), matches filter out people who simply want the ’ego boost’ that comes from a match.

  • Get exactly what your looking for — We don’t generate ‘matches’ for you, we empower you to do it yourself through presenting Challenges you can relate to from users who fit your preferences. Are you really into Dungeons and Dragons? Just search for it and find some Challenges that ask about your most dangerous quest!

  • Niche based dating in general dating app — Not every niche can be represented by a dating app usually due to lack of critical mass of users. When you search for Challenges by hashtag, you can turn Challengr into the niche dating app of your choice with the larger user base of a general interest dating app.

  • Filter out the noise — Since direct messaging is not allowed until a response to a Challenge is ‘liked’, women won’t be bombarded with inbox messages.

  • Total Privacy Control — On Challengr, you are invisible if you do not create a Challenge or Response. Feel free to browse for as long as you want until you find just the right Challenge to respond to. When you respond to a Challenge you are still invisible to everyone on the platform except for the person who you are responding to. The only time you are generally visible to other users are through your Challenges, so if you never create a Challenge, only people you decide to respond to will ever know you are on the app.

That’s a lot… and certainly longer than the attention span of a typical user. But how do you go about trimming the message? As the creator of this app, that is like asking a parent which of their children are they going to brag about? So I didn’t pick which one was more important, I just asked the world (or at least a hundred people in the world).

It turns out there are a couple services out there that will let you survey any demographic of person you want and give you the results in just a couple weeks. I settled on people fish for this project. I whipped up a quick google forms survey that asked questions that would help me rank these value propositions and sent it over to them. They converted my google form into their own little system and we were off to the races. 60 single women and 40 single men between 25–35 later and we have results!

So now when I talk about the value propositions I do so in the order the people indicated. That order so happens to be the order I listed them above (Personally I was surprised privacy control was at the bottom).

Hot Dog, or Not Hot Dog - using AI for what it was meant for, content moderation (Part I)

Ok, yes, we are building a dating app and yes it has everything you would expect to allow users to report content and users to our admins in the event they are being harassed, spammed, or just generally done talking to a particular person. But we decided very early on that would not be enough. 

The dating market is pretty full and each app out there has it’s own well deserved reputation. The last thing we want when we launch is to open the door for a small number of trolls to make Challengr’s reputation ‘the app with all the dick pics’.

So we took action. As a tiny company, there is no way we would be able to manually look at every picture or video that gets uploaded to the app. More importantly, if we were getting a lot of nudity, we would not want to sear our eyes with what the general public would be submitting. So here comes the first step of Machine Learning into our platform, the dick detector AKA booby bounty.

We wont get too technical for Part I. If you want to see how we developed this bit, check out the follow on posts (Tech: Image Moderation and Tech: Video Moderation). But what we will get into here is how our rules should apply in this world. 

The first question we asked was, how much is this all going to cost us and is it worth it? The answer to that comes pretty easy thanks to Amazon’s pay-as-you-go pricing sheet. It will cost us 10 cents a minute for each video we process and another 10 cents for every 100 images. That’s pretty reasonable, and as a brand new startup, essentially makes it free until we are pulling in some real usage.

The next question to answer: What does this AI actually tell us anyway? How ‘smart’ is it? It turns out it wont give us a name, address, social security number, nor the deepest and darkest secrets of the person being processed, but it does give us what we need, ‘this is nudity’ and ‘this is not nudity’. More specifically, these are the available results:

  • Explicit Nudity

  • Nudity

  • Graphic Male Nudity

  • Graphic Female Nudity

  • Sexual Activity

  • Partial Nudity

  • Suggestive

  • Female Swimwear or Underwear

  • Male Swimwear or Underwear

  • Revealing Clothes

Now after reading this list you may asking, ‘Hmm… should we be filtering out Female Nudity?’ You don’t really hear too many complaints about boob pics being sent over the net. In fact, if we think guys don’t mind seeing some naked women, perhaps we can even save a couple bucks and not even bother processing any photos or videos uploaded by women at all! 

Here at Challengr we try not to put our users in gender buckets like that and in the interest of equality and not making assumptions on what kind of experience our users want, we decided against that approach. But, you were on to something about saving a couple bucks, so we put a setting on everyone’s profile and just ask them: do you want us to filter your content for you? We default that setting to ‘yes’ and leave it at that. After we launch we’ll let you know what percentage of people open the door to some private pics.

Now the next big question. How do we deal with the people sending these graphic images. The answer to this one took a little bit of thinking

Option 1: Stop the upload in its tracks and just mark the post as a failure.

On its face, this seems like it would be an attractive option. There is no mistaking what happened, we show a little ‘Oops!’ message to the user uploading letting them know that kind of content isn’t allowed on the platform, and the person being sent the image never sees it. 

So what’s the catch? Well, this is a person who clearly has a need to send some untoward content and if we tell them we blocked it, will start trying to get around it. For whatever reason, they will have a need to get their privates through the door and no matter how good our computer is, they will probably find a way. The next drawback to this approach is a false positive. What if they upload a totally innocent picture and we tell them its porn? That would rub our users the wrong way.

Already this option is looking pretty rough but the one that knocks this one out of contention is: That’s way too much work! We would have to build out an entire error flow for users to be notified that their penis was blocked, allow for an interface for them to dispute the block or allow them to accept it and delete it from their profile. And if they dispute, would need to have to have a real person review and then have a pipeline to restore override the block, and then notify the uploader that ‘sorry our bad, we sent it through ok’.

Option 2: Shadow Moderate

In this scenario, we are going to make the content moderation completely invisible to our users, both the one sending the nudity and the one potentially receiving it. When a private picture gets sent up, we create the post as normal but with a special status of ‘processing’. When looking at your own posts, we simply ignore the ‘processing’ state and return it as normal, so you think it went through just fine. For everyone else, if the state is not ‘complete’ it gets filtered from their feeds. 

After we check for nudity, we change the state to either ‘moderated’ or ‘complete’. If we mark it complete, we send a quick notification to the receiving user that a safe piece of content was sent to them and they should check it out. If we mark it ‘moderated’ we don’t have to do anything, it just exists on the platform and the only one who can see it is the creator of the post. 

So now, any piece of inappropriate content uploaded looks like it works and the uploader never knows if we caught it or not and therefore wont try to game the system. If we mess up and it is a false positive, no one will ever know! It will be as though the post was just not good enough for the receiver to mark it as a match.

So naturally, we went with option 2.