Jun

3 Reasons Why Knowing Intent is Essential for Your Business

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:

Abundance of Information Often is a Liability

A massive change has occurred in the world during the last ten to twenty years. Until recently and throughout the history of mankind information was hard to access. Obtaining and sharing information was either a laborious process or impossible, and the underlying assumption was that information can never be enough.

Today, of course, we have the opposite picture. Not only information is easily available, it keeps pouring in from a growing number of sources, and we continuously find ourselves in situations when there is more information than we want or able to process.

A major task we, as species, are facing is therefore how to reduce or filter out relevant information. It is, to repeat, in direct opposition to the task we’ve been accustomed to during all previous centuries, which was how to obtain information.

Since this change took place only recently, within a lifetime of one generation, we didn’t have time to develop efficient set of procedures to address the new problem. But the work has started and will only accelerate with time.

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nmodes Technology - Overview

                                                       

nmodes ability to accurately deliver relevant messages and conversations to businesses is based on its ability to understand these messages and conversations. Once a system understands a sentence or text, it can easily perform a necessary action, i.e. bring a sentence about buying a car to the car dealership, or a complaint about purchased furniture to the customer service department of the furniture company.

Understanding sentences is called semantics. nmodes has developed a strong semantic technology that stand out in a number of ways.

Here is how nmodes technology is different:

1. Low computational power. We don’t use methods and algorithms deployed by almost everyone else in this space. The algorithms we are using allow us to achieve high level of accuracy while significantly reducing the computational power. Most accurate semantic systems, e.g. Google’s, or IBM’s, rely on supercomputers. By comparison our computational requirements are modest to the extreme, yet we successfully compete with these powerhouses in terms accuracy and quality of results.

2. Private data sources. We work extensively with Twitter and other social networks, yet at the same time we process enterprise data.  Working with private data sources means system should know details specific only to this particular data source. For example, when if a system handles web self-service solution for online electronics store it learns the names, prices, and other details of all products available at this store.  

3. User driven solution. Our system learns from user’s input. Which makes it extremely flexible and as granular as needed. It supports both generic topics, for example car purchasing, and conversations concentrating on specific type of car, or a model.

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