Vendo provides billing services with a heavy use of artificial intelligence.

Our platform uses artificial intelligence to choose the best price for each shopper. That is the price that makes the most money with that shopper. If a price is too high the shopper won’t buy and you lose the sale. That’s obvious.

If, however, the price is too low (ex. $30 when the shopper would have happily paid $40) then you also lose money. $10 in that example.

No human can pick the right price for each shopper. There are just too many shoppers. An average client of Vendo’s will have over 100,000 shoppers a day to his site. That’s more than one per second!

Only artificial intelligence can pick the best price for every shopper at every moment.

The AI works by gathering information about the product and the shopper. t learns through experience what the optimal price is for each particular shopper at each moment..

Dynamic pricing, nowadays is being used across countless industries for both products and services. Some notable examples of companies using dynamic pricing actively are:

  • Amazon
  • British Airways
  • Hilton Hotels

After analyzing their logs on consumer behavior they realized that different consumers would be willing to pay different prices for the same item or service. They choose not to make assumptions on how much the product is worth for each user, but let the data of past sales speak for itself.

They have implemented this concept years ago and are still using it today because the positive results they’re seeing from dynamic pricing are real.

Despite its gains and proven results, dynamic pricing is a complex topic. I can tell you by experience, it’s not an easy concept to get across to your prospects or customers. It’s hard to teach sitting face to face in a meeting room, let alone during a phone or skype conversation.

Countless times we’ve walked out of a meeting room, took looking at the face of our customers and it was clear that they did not fully grasp it. That’s a frustrating experience for everyone.

We realized that we were in need of a visual tool to make it easier for our clients to see the benefits of dynamic pricing.

So we created a Dynamic Pricing demo. It’s an application built on over a gigabyte of real transaction data from our historical database.

You can manually create a user, based on variables like country, device, day of the week or time of the day of the purchase. They are just a few of the variables we look at when deciding on price. We then plot the revenue curve specific to this shopper. It shows the effect on revenue of each price you could show to that shopper. It’s the first time anyone has seen industry wide data showing the actual effect of prices on revenues.

The goal for our clients and prospects is to guess the best price for each specific user. He will then see within the curve where his price stands against the optimal revenue price.

The result looks something like this:

Screen Shot 2016-07-29 at 1.02.55 PM

If you haven’t yet had the chance to play with this tool, or simply if you are curious and want to give it a spin. Don’t hesitate to get in touch with me, and I’ll walk you through it.