3 ways AI will increase your sales

sasha uritsky

Nov 06, 2017

Many of us get the understanding of artificial intelligence from the film industry. It creates an image of smart, humanized machines that are helpful, efficient and omnipresent. It is true that AI has seen rapid advances in the past several years, to the point that it became an integral part of our everyday life. In real life, however, AI is far away from the level portrayed in sci-fi movies. And yet there are affordable AI tools and solutions that can make a significant impact on your business.

Here are three main reasons why a company, especially if it is a B2C company, should consider integrating AI into their business process.

AI makes your sales process scalable

AI solution dealing with your prospects and customers works 24/7 without sick days, holidays and breaks. It can handle any level of traffic, incoming inquiries and conversations. It does not need to be trained. It does not have personal issues or bad days. It is always polite and uses professional jargon. It is fast.

AI creates better user experience

Some might find it surprising but this is only because they have experienced low quality AI solutions. A professional AI solution makes customer experience better primarily because it delivers the results with a minimum of fuss and maximum efficiency. A good AI eliminates bureaucracy, makes customer experience speedy and seamless, and that’s what consumers are looking for today.

AI offers sustainability

Adding AI to your business model creates long-term sustainability for the business. It allows your business to grow while controlling, or even minimising the costs. More importantly, it ensures that the business remains competitive in providing the level of customer service consumers became accustomed to. Lastly, it creates platform for future technical improvements and integrations which, without a doubt, will be based on Artificial Intelligence components.

Interested in reading more? Check out our other blogs:

NMODES at Collision 2019

While Toronto is charged with hosting the Collision - "North America's fastest-growing tech conference" this year, nmodes is excited to make its first appearance among designated start-ups who have been selected to demo their products to conference visitors, potential investors, tech-enthusiasts and business executives.

nmodes, a year and a half in the market, offers a conversational product that uses AI to provide its customers with a scalable solution to execute 24/7/365 marketing acquisition and customer experience programs. While nmodes has already garnered its global presence with 40+ clients, North American market continues to be most enterprising for AI Chatbots and Voicebots. Collision Tech Event offers an exciting opportunity for nmodes team to take its networking game a notch higher and pitch it to businesses looking to catch-up with the AI space and be early adopters of hottest AI products available in the market.

How nmodes is different than other chatbots?

AI space is nothing new to the tech world as chatbots, virtual assistants and voice bots are finding their commercial contribution toward improving the customer experience of brands. nmodes continues to work closely with the businesses focusing on helping brands drive double digit growth in lead conversions and engagement rates.

Three key market differentiators for nmodes:

1. Interlacing marketing and customer experience

nmodes chatbots are custom built for the brands. nmodes solutions support full customer lifecycle from lead generation to marketing campaigns to scheduling demos, to gathering feedback and understanding engagement patterns of existing customers.

2. Lifetime AI training

nmodes solutions promise to work with progressive AI capabilities that are built to recognize old and new communication patterns and form a sensible response template that is malleable and fulfills the intent of desired conversation for the customers.

Nmodes solutions work on three principles while conversing with the customers.

A) Keep business context

nmodes solutions remember the customer’s history and their presence in the sales cycle and hence conversations are based upon the context of customer for the brand.

B) Data personalization

personalization of conversations focuses on collecting different data points from all internal and external data sources, helping brands deliver tailored and one-on-one predictive interactions.

C) Easy to use analytics

nmodes advanced dashboards uncover detailed analytics and insights on customer conversion rates, engagement rates and listen upon most common conversations to help brands better align their marketing communications and customer experience strategies.

Why Keywords Do Not Cut It on Social Search

Most of the online search is keywords-based. Same in social domain, a vast number of analytical tools, networking platforms and mobile apps use keyword-based technologies as well.

There is a difference, of course, between traditional internet search and social search. The former finds websites. The latter finds conversations, messages, posts. Keyword-based internet search is doing a decent job for us for over 20 years. Keyword-based social search is not doing a decent job at all.

Consider a basic example: finding on Twitter who is interested in buying jeans. We can start by typing ‘jeans’ but that brings up too much noise. Maybe ‘need jeans’? Less noise but then we people who use expressions like ‘looking for jeans’ or ‘want jeans’ or shopping for jeans’. Not to mention those who use ‘denim’, or brand names. So we have to run multiple searches or create a complex search string using logical AND and OR and hope it works. Neither option is simple, or convenient, and certainly not efficient.

The above example highlights the major flaw with keyword search - it does not capture the meaning of social conversations, and therefore cannot be a reliable source of information about conversations.

It does not provide too much of correct information. And it does provide lots of incorrect information. But the biggest problem is that it has extremely limited potential for improvement.

So as long as we stick with keyword-based social search the results are destined to be limited.

Why, then, we stick with keyword-based search in social search? Simply because there is no good alternative. Until recently, that is.

The advanced semantic technologies capable of capturing the meaning, or intent, of conversations are now offering an exciting alternative.

I will discuss these technologies on my next blog.