One Fast Way To Increase Your Online Sales

sasha uritsky

Jan 22, 2018

Chatbots and conversational AI solutions offer easy and reliable sales channel.

Chatbots are helpful because they not only engage with your customers, they also retain them. This means that unlike other forms of marketing, chatbots keep your customers entertained for longer. For example, when a user has a customer care inquiry, the chatbot can answer it accurately and take the conversation a step further by offering personalized shopping advice based on the customer's purchase history and preferences.

Chatbots make communication with your brand proactive, thus enhancing your brand's reputation. By increasing interactions, they make a positive effect on your sales numbers.

Chatbots allow your business to reach out to a wider audience. They can gather and analyze customer feedback and data. Send relevant notifications. Make communicating with your brand more fun.

Chatbots help with top of funnel conversions. Offering your online customers a highly personalized experience of your site with the addition of a chatbot can help guide consumers down the sales funnel, and ultimately influence their buying decisions.

To summarize, chatbots opens new opportunities for you to increase sales. Opportunities that are easy to use and are not costly. Better not to miss them!

Interested in reading more? Check out our other blogs:

Tech world came to Toronto

In May 2019, the Collision Conference took place in Toronto for the first time, and we couldn’t miss it! It was a great opportunity to meet amazing people, learn from great companies and showcase our own capabilities.

Attending the first day’s talks at the Collision center stage

AI solutions naturally attract attention

Lots of interest interest in our conversational AI

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.