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:

WHAT IS AI TRAINING

AI training is a critical part of conversational AI solutions, a part that makes AI software different from any kind of software previously created.
AI training is not coding.
Unlike all other existing software which is fully coded.

Let us consider a simple example:
We create chatbots for two companies, one company is selling shoes, another is selling cars. From the software standpoint it is one chatbot solution running as an online service accessed remotely or a program available locally. In both cases they are two identical instances of the same software (one instance for the shoes company, another for the cars company).
Yet, for the first company the chatbot is supposed to talk about flip-flops, summer shoes, high heels and so on. For the second company, however, the chatbot is not expected to know any of that. Instead, the chatbot should be able to support conversations about car brands, car models, should know how to tell Toyota Camry from Toyota Corolla, etc. This shoes and cars knowledge is not programmable. It is trainable. It is not coded, instead it is a part of language processing capability that AI solutions like chatbots have. And herein lies the major differentiation and advantage of the AI solutions compared to traditional software.

How to train AI?
There are several ways to do it. Sometimes AI system can train itself, improve its linguistic ability over time. It also can be trained by professional linguists. And in some cases, by the users. The latter is the desirable scenario because businesses know better than anybody else what they want their chatbot to talk about.
It is not easy, given the existing state of AI technology, and usually requires a high level of technical knowledge. You may have heard mentions of intents and entities in chatbot discussions. These are examples of linguistic elements AI training is currently based on.
Without proper understanding of what these linguistic elements are and how language acquisition process works in existing AI systems it is better to leave AI training to professional linguists.

Lessons for Businesses from Brazil’s World Cup Disaster

1. Mental, or psychological, state of your team is important: you can put so much pressure on people before they crack. Brazil players didn’t become unqualified professionals overnight. They failed because they were overwhelmed by their country’s expectations, distorted sense of history, and the right to win considered divine. They were too emotionally charged, not in the proper state of mind to compete. So better keep calm, relaxed atmosphere in your team even before launch, or important deadline.

2. Manage customer expectations. Brazil were ramping them up unreasonably. Aggressive messages like the 6^th[title] is coming, statements by their coach about two more steps to heaven massively backfired by creating an unhealthy emotional frenzy in the society, which in return influenced the players (see 1.)

3. Logic, organization is the key to successful execution. Germany are not a great team. But they are very well organized. They had a detailed game-plan where every team member knew his task and several different scenarios where prepared. They were able to adjust when the situation on the field changed to squeeze maximum advantage. Sounds simple? That’s because it is.