You may remember IBM's Watson AI compete on Jeopardy. It was given a question in English (Well, an answer, this is Jeopardy after all) which it then parsed into a format it could understand, found a solution, and then presented that solution in an English phrase that Alex Trebek and the Jeopardy judges could understand. Let's take a look at the process that Watson used and see how you can leverage our Deeploop technology in a similar way to improve your sales.
Computers have been interacting with human language for a very long time. As early as the 70s there were text adventure games that allowed the player to enter commands in English. These early programs were not very good at understanding English as we speak it. Players had to enter their commands in very simple structures such as, "look left", "go north", or "take weapon." Enter the something outside of those allowable combinations and the computer would tell you that it could not understand you. The onus was on the user to properly understand the computer's needs.
Put another way, these old programs were not good at what we call natural language understanding. You had to enter your commands the way a robot from an old movie would speak, rather the way you would naturally speak. In the many years since those games first appeared, computers have gotten much better at natural language processing. They are now able to identify parts of speech, recognize many more words and their misspellings, and as a result, parse much more complex grammatical constructs that they could before.
These advances in natural language processing are what allowed Watson to understand the same questions that were asked of its human competitors.
Seeking The Answer
Watson had a supercomputer and the knowledge of the internet to get its answers. Not all AI systems need to be that advanced. Most are fine working within their own databases. Amazon, for example, will look at items that you have purchased and compare that to a list of purchases from other users who have purchased the same things. If a large number of them have purchased something that you haven't, Amazon may recommend it to you. The more things you purchase, the bigger a profile the AI can get of your interests, and the more likely it is to recommend things that you like.
An AI can also train itself to be more successful by tracking which attempts it makes that succeed, and which ones do not. If a shopping site's AI is constantly recommending you items from a certain category that you never purchase from, but you do purchase frequently from another category, it will know to prioritize the more successful product types in its future recommendations. This is a basic form of the much more complex field of machine learning.
Forming The Answer
We've examined how Watson uses natural language understanding to process the question. This is part of a larger subfield known as natural language processing. Another aspect of this subfield is the generation of natural language. That is to say, the computer takes the data that it has in raw form and outputs it in a sentence or set of sentences that sound the way an actual human would phrase them. Natural language generation technology is just now getting to the point that it can be useful for interacting with humans. You likely use it on a regular basis through the use of virtual assistants such as Apple's Siri, Amazon's Alexa, Microsoft's Cortana, or similar products.
How Can This Technology Benefit You?
Deeploop has developed an AI that will serve as a virtual sales representative for your company, interacting with sales leads via email typically. The customer will believe that they are talking to an actual human being, who answers their questions and figures out their unique needs. Once the AI knows what the customer wants and has convinced them to move on to the next step, it passed the lead off to your human salesforce.
Deeploop doesn't replace your salesforce. Instead, it prescreens and works the leads for them so they only spend time on leads that are ready to buy. This increases their productivity, work enjoyment, and your bottom line.