3 Reasons Why Knowing Intent is Essential for Your Business

sasha uritsky

Jun 18, 2014

What is intent? It is the reason behind the sentences we say. Behind posts and messages, as they appear on social networks. For instance, the intent of the tweet ‘I am going to buy a new car soon, my old car is entirely broken’ is buying a new car. The intent of this one however ‘ Need to buy me a car, got things to do lol’ could be anything from killing time by posting randomly to impressing friends, but not buying a car.

During the time when most customer activities online happened on search engines (e.g. Google) understanding of intent was predominantly the task of these search engines. So when I type ‘typical menu of Chinese restaurant’ and the search engine displays the list of local Chinese restaurants clearly in this case it did not understand my intent.

Nowadays, when an ever growing part of the consumer related activities is happening on social networks the task of understanding the customer intent becomes responsibility of a business.

Here are three reasons why this task is essential:

1. Marketing is personalized. Email blasts are a thing from the past. Today to stay completive your business should be able to target individually. And that means knowing what each of your potential customers needs in real time. The best way to know this is to understand customer intent. The numerous analytical and measurement tools available today exist only because until recently we didn’t know how to capture customer intent properly.

2. Knowing intent allows efficient and timely service across your company’s departments: those interested in the product belong to marketing department, purchase intent goes to sales, unhappy customers go to customer service, and so on.

3. Knowing intent offers long-term sustainability to your business because it reduces the noise. Unlike the previous generations, when the problem was a lack of information, today’s problem is the abundance of information. Business can function efficiently and be sustainable only when a competent model of finding the right information is in place. Understanding of intent is the best model available

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.