Feb

Social selling. Difference between Facebook and Twitter

                                                         

There are obviously some key differences between Facebook and Twitter that make them appealing to different people as well as businesses. If possible, businesses should try to leverage both networks in their marketing and sales efforts.

But marketing approaches for each network differ.  Consequently social selling approaches differ as well. Here are some major differences of the two networks that impact sales strategy:

- Twitter lets all the accounts commingle, Facebook makes a definite distinction between business and personal. This can be an issue because a business page cannot proactively connect with individuals with personal profiles. Individuals have to first like a business page and still the business can’t reach out to them directly unless they message first. This is not the case with Twitter, as anyone can follow pretty much anyone.

- Facebook preferred way to market products and promote online sales can be compared to a showroom. The prospects can see the product and purchase it through some other channel, however engagement (with prospects) is limited to friends and followers. Hence growing the number of friends and followers becomes a critical task on Facebook.  Twitter does not offer promotional capabilities but engagement activity is not limited to followers. The engagement on Twitter is therefore more straightforward and can lead to direct sales.

- Facebook user data is typically open to friends or followers. Twitter data is typically open to the entire world.

- Twitter is fast (minutes). Facebook is slower (hours and days).

- Twitter is more about building a brand identity. Facebook is more about business relationships.

To summarize, a direct timely engagement could be a good strategy on Twitter. In a typical scenario a user tweets that she needs a taxi or asks where to dine tonight. A taxi company or a relevant restaurant engages in a conversation and secures a customer. It is an efficient approach with immediate ROI.

On Facebook a good strategy is to grow and educate a community of followers. Facebook is excellent for promotional campaigns. This is a longer-term strategy with effects not visible until after several months.

 

Interested in reading more? Check out our other blogs:

Meet Eliza, the Mother of AI

                                                             

Meet Eliza, the Mother of AI..

Today, Artificial Intelligence seems to be the buzz of every major enterprise. Salesforce is formally announcing Einstein this fall, IBM has worked on Watson for years now, and after 20 years of working with AI, Microsoft has made a few attempts to bring the technology to the market. With all this activity, you may be asking yourself what kind of impact AI will have on you and your business, and where you might want to look to investigate the possibilities Artificial Intelligence represents.

Before we discuss how AI will impact customer support and consumer experience, and how you may leverage it in your contact center, I thought it would be fun to take a look where AI got its start.

The term AI was coined by computer scientist John McCarthyin 1956 who subsequently went on to create the Dartmouth Conference to advance the ideas and technologies associated with machine intelligence. While this collective of thought leaders and scientists made huge advancements through programs at MIT and others, most of their work was only circulated in academic fields.

Not many people were aware of Artificial Intelligence, how it worked or its potential uses, until around 1964 when MIT computer Scientist Joseph Weizenbaumwrote Eliza, a program based on Natural Language Processingthat was able to successfully question and respond to human interactions in such a way as to almost sound like a real human being. Eliza, with almost no information about human responses was able to use scripts and pattern  matching to simulate responses that might occur between two people.

The most famous of these simulations, highlighting  AI ability to intersect with modern needs and technology, was DOCTOR. DOCTOR was able to question and respond to a human in such a way so as to almost sound like an actual psychotherapist. As the human subject made statements, DOCTOR asked questions and made statements relevant to the conversation as if it were a present and conscious being… almost.

Over the years  computer scientists, whether academics or industry professionals,  have worked tirelessly to improve upon these developments with the hope of delivering a computer program capable not only to ask and respond, but to understand the context of a conversation. A program that can relate relevant data to responses, thus providing value to the human it’s conversing with, while helping to chart the course of the conversation, just as if you and I were talking over a cup of coffee or across a conference room table.

Why is this important, you may ask? With the introduction of Chatbots, we began to see some of the potential in Artificial Intelligence. Companies could now front-end customer chat interactions that allowed the company to be more responsive to its customers while shortening wait times and deflecting inquiries from the call center, which as we all know are hugely expensive.

The one problem with Chatbots? Customers hated dealing with limited technology that was cold, often incorrect, and frustrating. People are accustomed to dealing with the cold, sterile nature of technology when they type numbers in a phone to be routed but expected a human to be chatting with them. These negative experiences have made a number of companies a little gun shy about implementing true Artificial Intelligence. The last thing a business wants is a customer complaining, especially on Social Media, about a poor customer experience due to a bad interaction with technology.

There is a significant difference between Chatbot technology and true AI, consequently the outcomes and customer experience are proving to be very different. Where a Chatbot is more like an IVR, answering simple questions and routing customers to the correct agent, Artificial Intelligence is aware of the conversation and able to present relevant responses, thereby providing a faster response and shorter customer interaction times and better customer service. I mean, if Eliza’s DOCTOR could simulate a psychotherapist in 1964, what can AI do for your contact center in 2016?

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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. 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.

  1. 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.




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