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:

How nmodes Intent API Improves Social Intelligence

Social media generates a vast amount of data. There are 500 million daily messages on Twitter alone. Still more data on Facebook, Google+, LinkedIn and other social networks. Some of this data is useful to businesses, in fact, it is extremely useful.

A business can use social data to generate actionable insights about customers, competitors and their company strategy. Social information empowers departments and teams, and when used correctly, creates a strong sustainable bond between businesses and their customers.

nmodes Intent API helps businesses to execute their social strategy efficiently. Here are the major elements of social strategy Intent API contributes to:

1. Listening. Intent API finds customer intent with any level of granularity. You might want to know who is looking to buy shoes in general, or looking to buy flip-flops in particular, or interested in buying only Nike footware, or interested in buying sneakers in New York region.

2. Sales and marketing. Intent API understands what stage in the purchase process your customer is in. Intent API tells if a customer is ready to buy, or is in the awareness stage, or considering the purchase but not ready yet, and so on.

3. Social intelligence. Intent API delivers meaningful intents and behavioral information on a large scale and for all verticals. Any insights and topics, as long as somebody is conversing on this topic, are available.

4. Teams and projects. Intent API channels information to the relevant departments within the company. Sales prospects should go to sales department, complaints to customer service, brand conversations to the marketers, and technical issues to tech support.

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.