Intent-driven Data Critical for Sales Growth

sasha uritsky

Dec 10, 2015

One of the most central causes of missed growth opportunities and overspending is a failure on the part of businesses to create strategies that are tailored to the intent of the consumer. Recognizing and harnessing visitor intent brings increased engagement with relevant messages and calls to action.

Once a business identifies purchase intenders it can create content that aligns with their needs and desires in order to increase the likelihood of conversion. Consequently it can pick up on pre-sale signals from visitors in the research phase and drive lead-nurturing initiatives accordingly. The ability to identify this spectrum of visitor intent is key to creating relevant engagement campaigns that drive sales.

nmodes has been at the forefront of delivering consumer intent to businesses.

We sort the intents based on conversation topics, called ‘streams’.

Here is a stream of people looking for a hotel:

A stream of people who are getting married:

A stream of people thinking of going on a cruise:

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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.

Volunteering during social distancing

nmodes is making an effort to assist you during this challenging time. Our team created this online community resource https://nmodes-coronavirus.web.app resource to help during COVID-19 self-isolation. It is powered by nmodes conversational AI.

In case you or your close ones are experiencing symptoms of COVID-19, our self-assessment tool could help to determine if further medical care is needed.

With the self-isolation assessment, you could measure whether your self-isolation procedures are appropriate or not. It is important to maintain self-isolation to protect yourself from getting infected.

If you wish to volunteer and contribute to the community our chatbot will connect you with people who need help. You can contribute either virtually and in-person.

Most importantly if you would like to get help the chatbot will connect you with a volunteer who could assist with your needs.

It is fast and easy - answer quick questions and you are all set. We have volunteers ready to help with all kinds of requests , from grocery shopping and home chores to online tutoring and sharing game time.