Jan

MAKING AI MAINSTREAM



We are experiencing a strong demand for conversational AI solutions. It is coming from every corner of the B2C market. It is growing by the day.

Conversational AI is becoming increasingly popular among the consumer facing business community. It is easy to see why - AI offers sales and customer service scalability and therefore is critical for the long-term success of a business.

Conversational AI solutions such as chatbots, voice bots, and virtual assistants provide much needed speed and efficiency, in an age where the rapid advancement of technology makes them virtually the only sustainable customer service solution.

Bu there is a catch - AI is complicated. Mainstream businesses do not have in house AI expertise. And it is not part of their business model to develop such expertise.

Today’s market offer several good conversational AI solutions, such as IBM Watson or Google DialogFlow. However, getting a business value out of them requires the very AI expertise that mainstream companies do not possess.

So what can be done?

Any AI solution should follow these three steps in order for the mainstream business community to fully benefit from it:

  1. Conversational AI should come as a service,
  2. The service should be available in natural language,
  3. The service should be fully personalized.  
 In the next several posts we will explore how the AI industry, including nmodes, is moving towards achieving these goals.
Interested in reading more? Check out our other blogs:

Send Us Your Travel/Hospitality Business Pitch

                                                           

nmodes is a data analytics company. We analyse data based on consumer intent. We’re pretty good at it.

We spend a significant portion of our processing resources on analysing travel data. And so we are fast to know when somebody is planning a trip, or looking for a place to stay, or visiting your city and searching for activities, restaurants, entertainment.

In addition to data processing we help businesses in monetizing the data we deliver them. We create and implement the marketing strategy to convert intent-driven consumer data into your sales. Typically the majority of the data comes from social web, and consequently a successful marketing strategy has an important benefit of establishing long-term social presence for your business.

We also offer free end user services. Knowing consumer intent gives us capability to identify in real-time social users in need of travel help. Our data is actionable, allowing to respond momentarily to individuals with timely recommendations and advice.

Knowing consumer intent in real-time gives business power to control the sales process. Your customer satisfaction will improve, and your sales will grow significantly.

And if you are not ready to start using our full service, you can always send us a short description of your business, its value, and how it is better from competition. We will be happy to connect consumers with your product when appropriate. No commitment on your part is required.

Intent-driven data offers instant value, start enjoying it.

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Towards smarter data - accuracy and precision

                                                   

There is a huge amount of information out there. And it is growing. To make it efficient and increase our competitive advantage we need to evolve and start using information in a smart way, by concentrating on data that drives business value because it is accurate, actionable, and agile. Accuracy is an important measure that determines the quality of data processing solutions.

How accuracy is calculated?

It is easy to do with structured data, because the requirements are formalizable. It is less obvious with unstructured data, e.g. a stream of social feeds, or any data set that involves natural language. Indeed, the sentences of natural language are subject to multiple interpretations, and therefore allow a degree of subjectivity. For example, should a sentence ‘I haven’t been on a sea cruise for a long time’ be qualified for a data set of people interested in going on a cruise? Both answers, yes and no, seem valid.

In these cases an argument was put forward endorsing a consensus approach which polls data providers is the best way to judge data accuracy. This approach essentially claims that attributes with the highest consensus across data providers is the most accurate.

At nmodes we deal with unstructured data all the time because we process natural language messages, primarily from social networks. We do not favor this simplistic approach, as it is considered biased, inviting people to make assumptions based on what they already believe to be true, and making no distinction between precision and accuracy. Obviously the difference is that precision measures what you got right, and accuracy measures both what you got right and what you got wrong. Accuracy is a more inclusive and therefore more valuable characteristic.

Our approach is

a) to validate data against third party independent sources (typically of academic origin) that contain trusted sets and reliable demography. Validating nmodes data against third party sources allows us to verify that our data achieves the greatest possible balance of scale and accuracy.

b) to enrich upon the existing test sets by purposefully including examples ambiguous in meaning and intent, and providing additional levels of categorization to cover these examples.

Accuracy is becoming important when businesses move from rudimentary data use, typical of the first Big Data years, to a more measured and careful approach of today. Understanding how it is calculated and the value it brings helps in achieving long-term sustainability and success.

 

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