chirrp vs. chat: how chirrp’s rich conversation is different from the rest

Our team has been giving demos to a wide audience, including investors, potential partners, and customers. One question that comes up over and over is “Why chirrp?” What makes chirrp different, in a market that growing by the minute? Let’s take a look.

When working with most chatbots, you must identify each question that your bot can handle. This format is inherently limited to a fixed number and to a fixed question sequence. If a customer engages in a way that your bot wasn’t programmed to handle, it has little ability to respond correctly. A chatbot built in this way has a limited amount of scenarios it understands, and is powerless to address any variance in those use cases. Even if a customer asks a question that’s in a programmed scenario, if the question is asked out of sequence, the system can’t adjust. This inflexibility is why most available bots are limited, and often not sufficient to significantly cover your customer service needs.

One of chirrp’s most powerful capabilities comes from its patented analytical model which recognizes questions and commands that it wasn’t explicitly coded to know. Every customer response is first analyzed by a robust natural language processor (NLP), which identifies the sentence structure, breaks down word phrasing, and determines intention.

Once the system has located the customer’s basic intention, the system will route the conversation to the appropriate branch point. It may be that the user has asked a question that the system has a direct answer to. In that case, a list of possible answers is pulled, and the answer with the highest certainty (best likelihood of being correct) is the response from chirrp. An example of this scenario involves a potential customer chatting with a doctor’s office chirrpbot. They may ask “what types of injuries do you treat?” To such a question, chirrp might provide a list of services and types of doctors in the practice.

Alternatively, the customer may ask a question that warrants another question from the system, in order to proceed. Often times this type of question may lead to a back and forth dialog that helps the user reach an end destination. A customer may ask a doctor’s office, “Do you accept Aetna insurance?” This could trigger a dialog around insurance and becoming a new patient. Chirrp might respond, “We accept certain types, what type of Aetna plan do you have?” or “Yes, we do. Would you like to schedule an appointment with one of our doctors?” or some question that proceeds with the new patient registration process. At each interaction, the system re-analyzes intent, to determine the next response from chirrp.

By applying a robust natural language processor to every customer response, chirrp’s AI can flexibly route the conversation to the correct next step. If a user asks a question that goes outside of a sequential dialog, the NLP will identify the intent, and route the question to the correct answer (which may be under a new topic altogether), or to a new dialog, or to a later point in the same dialog. Because the NLP is applied at every point, chirrp’s platform allows for fixed answer sets AND free text answers.

Chirrp’s flexibility in user input also makes system more user friendly and conversational. Customers aren’t forced to pick from a short list of answers; they can ask and respond using free text. This also allows the customer to have more control over the conversation. They can jump to a new topic, skip ahead if they don’t need info, and ask questions out of sequence.

As AI continues to mature, customers are expecting their interactions with bots to become more intelligent and capable. Due to its patent methodology, chirrp delivers flexible, responsive interactions to users across industries and channels. Using artificial intelligence, chirrp promises to push chatbot technology into our everyday lives.

– Rosanne Lush [VP of Product]

Event: You’re Invited to Digital Demo Day

Are you interested in chatbots, but not sure how they can be useful in everyday life and business?

Have you heard about chirrp, but don’t really know what it does?

If so, join Mallesh Murugesan, the Co-Founder and CEO of chirrp.ai, today, as he demos the robust capabilities the chirrp, a chatbot enterprise platform. He’ll be presenting as part of a Digital Demo Day, presented by SeedInvest. Come armed with curiosity and questions to this short demonstration.

Chirrp will be presented Thursday, July 20th at 1:30-1:45PM Eastern Daylight Time.

To join, please fill out this short form. SeedInvest will email you the attendee info shortly before the meeting.

Chirrp.ai Takes Home eMerge Americas Award

Mallesh and I traveled to eMerge Americas’ annual conference where we demoed our AI-powered conversational platform chirrp. In competition with over 100 other startups, chirrp took home the top prize in Early Stage Venture! We’re so proud of our team for their vision, hard work and dedication. We’re very grateful to all our friends, partners and clients who directly and indirectly have supported and encouraged us along the way.

Here’s a quick excerpt from our press release:

Chirrp is a multichannel conversational platform that uses the power of artificial intelligence and machine learning to deliver engaging interactions to customers. Chirrp provides solutions to key challenges for enterprises such as building stronger brand loyalty, driving additional revenue through upselling, and capitalizing on predictive and prescriptive data. The platform reduces the costs of delivering customer service, support and communications, while increasing customer satisfaction and loyalty.

For more info on the conference and a list of winners in the University and Late Stage categories, check out this article release by eMerge Americas.

Thanks again to all our friends, partners and family who’ve support us along the way.  If you’re just learning of  chirrp, we’d love to explore new opportunities with you, as we continue to grow.

Rosanne

2016 Year of Dumb Bots

2016 is being called the “Year of the Bots” by technology experts primarily because 2016 is seeing the culmination of artificial intelligence and conversation model, thereby paving the way for enterprises to reach out to their customers in a whole new way. Some of the world’s largest technology companies are banking on this technology and is investing heavily into this space both in R&D and in acquisitions.

But are we there yet. Bots that are being created in 2016 are pretty dumb, rightfully so because of the below reasons…

One: When a technology is exciting and new, lots of developers want to play in that space and will create basic applications hoping to get some traction. Not a lot of thought goes into it except for the hope of having the first movers advantage. We have seen this time and time again, remember websites in early 2000’s, mobile apps in 2008 etc. Chatbots today are fairly basis and rudimentary in functions. When it doesn’t understand a phrase, it goes into a dead end. Some chatbots are handling this scenario by providing menu’s for the users. But is that really a human-like conversation.

Two: The technology itself is not very mature. It is very much a beginning of a new foundation and requires time for it to have all the right pieces to become a global phenomenon. Artificial Intelligence though has been around a many years, without significant amount of work, it is hard for it be a robust conversational platform.

Three: Large enterprises are not ready to move into this space yet. Large enterprises are risk averse when it comes to a complex new technology disruption, especially when it is customer facing that could affect their brand. There has been several internal pilots at the enterprise level but it hasn’t gone mainstream yet and until that point, we will continue to see dumb bots being released. The chatbot idea is still a bit of mystery.

Chatbots have ways to go before they can replace apps for enterprises but its evolving and only time will tell if chatbots will become as ubiquitous as the apps have.