Explaining Elastic Supply and Demand
Here’s the thing: I don’t take Uber or Lyft. I like yellow cabs. I don’t know why. It’s a little more expensive and a lot more unreliable, but it makes sense to me. That’s not to say that there aren’t things that frustrate me about yellow cabs. I just don’t care enough to stop using them.
For instance, the other week my wife and I saw a show in a music venue that was not normally a music venue located in a very residential area of Queens – zoning laws be damned! New York is still cool it’s just not as cool. So, anyways, the show ends and everyone leaves only to discover all the trains have shut down. Why? I have no idea. That’s just one of the joys of living in New York in the age of Cuomo. Then it suddenly occurs to me: I’m going to have to flag down a cab.
Now, normally, getting a taxi wouldn’t be a problem, but that night there were about 300 people on a remote corner of Roosevelt Avenue and 99th Street where normally there wouldn’t be much more than a few rats the size of small elk roaming about. But there is a finite number of taxis in New York, and they tend to go where they believe the highest amount of demand will be based on their experience. For instance, if they know there is a Knicks game that ends around 10pm, they might show up at 9pm to catch the hordes of frustrated Knicks fans leaving Madison Square Garden early. This situation, however, was one the taxi and limousine commission had no means of anticipating, meaning they missed out on a high-demand opportunity and any incremental revenue that might have resulted.
This is similar to a problem facing the traditional Publishing Brands we work with (think The New York Times) with regards to their relationship with their email inventory. They have a set number of ad units in each email newsletter and they use data they have available to them to project anticipated demand and maximize revenue. They rely on LiveIntent to help traffic and target their direct sold campaigns and fill any unsold inventory with the best possible advertiser via third-parties. Some even allow these different demand sources to compete so they can optimize the yield. Then they take the results, factor that into the next cycle, rinse and repeat.
But, just like the taxi commission, if there is a sudden unexpected source of increased demand, they do not have a means to dynamically adjust their supply to meet that demand and therefore, they miss out on new revenue opportunities.
As an example, and this example meanders: my wife hates technology. She doesn’t have any social media channels, barely uses Google, doesn’t really have any “intent” online. I, on the other hand, have a ton of intent. Instant Pots, stain removers, and yes, fine, “best ride-share” apps dot my search history. I have a long, detailed purchase history as well as subscriptions to email newsletters from music ticketing companies, furniture stores, and advice columnists that specialize in car-buying tips (one day!). So, while the demand might not be there for my wife, I am the online advertising equivalent of that isolated corner in Queens suddenly overrun with 300 trust-fund buoyed hipsters.
This is where the ride-share companies have innovated. They are able to recognize when there is a Hipstata (the technical term for a herd of aging hipsters) gathered in a corner of Queens and incentivize drivers to go that location by increasing the fare. It expands the supply to match demand and maximizes revenue potential; a shining example of innovation and modernity in the form of fleets of cars whisking annoying gentrifiers back to their enclaves in Williamsburg and Greenpoint while I try to flag down every remotely green or yellow car, yielding nothing but angry honks.
The concept of expanding the supply to match demand and maximize revenue potential is why we made recent changes to our LiveTag technology.
Now, instead of basic static ad units, these tags dynamically adapt to the size of the ad being served and will expand or collapse to meet increases or decreases in demand.
That means Publishers can still dedicate the standard 2 ad units (or whatever) to their direct sold or marketing campaigns and add any other number of units with the confidence that these will only appear when demand meets a defined premium. If the Publisher believes that $8 is what it’s worth it to increase the number of ads seen by a subscriber, the ad units will only expand when advertisers are willing to pay $8 or more.
So, let’s say my wife and I subscribe to the same email newsletter. I am a person, we have established, that has a lot on online intent, while my wife does not. That means there is a likelihood more advertisers would be willing to pay more to reach me. My wife… not so much. So, when my wife opens the newsletter, she will see the standard 2 ad units, while I will see 4 (or 6, or 8, or however many more exist in the template) – all of which are seamlessly integrated into the email newsletter so as not to detract from the content.
Just like there were cars sent to meet the demand of a concert that let out, so too are there ad units deployed to meet the demand of a sucker (me) opening an email. More advertisers reach a person they want to reach, while Publishers increase revenue without having to negatively impact my experience as a reader.
Essentially (God I hate myself for this line. I should be fired? Can anyone hear me?) LiveIntent is now the Uber of email newsletters! By the way, anytime you use the “is the Uber of” in startup world, an angel gets their MBA. But really, we’ve mimicked the marketplace innovations of the rideshare business. We’re bringing the supply to meet the demand, while not ruining the experience.