Social Strategy for B2B Companies

sasha uritsky

Sep 20, 2014

I am regularly approached by businesses that sell to other businesses to help them market and promote their brand on social networks.

And so I noticed that some of them have a vague idea of how social media works and the sustainability it offers. They often see social marketing as yet another way to advertise and sell their products, in the same manner they are accustomed to do on traditional marketing mediums. Not surprisingly it usually results in frustration.

While I saw companies successfully sell on social, they are typically limited to mass consumer oriented B2C verticals, such as fashion and apparel, travel and hospitality. There is a segment of online shoppers, sometimes called ‘impulse shoppers’, that makes purchases straight off the Twitter timeline, yet the majority of us go to social networks for different reasons. Certainly no one is buying an insurance policy, or a house, or a CRM solution there.

The success of social media and its importance for business is in its unique ability to build trust.

For B2B, as well as for the majority of consumer-oriented businesses, this is where the real value of social marketing lies. A more detailed discussion here

And so that means approaching social media strategically. First know precisely why you want to engage, understand clearly how it will help you grow the business. Then, if you are convinced of social media’s importance for the success of your business, start taking practical steps. Obviously very company is different, but here are some observations that are pretty generic:

- Plan long-term. Don’t expect results after one month. Not even after two months.

- Do not do social media just because ‘everybody’ is doing it. When people have strategy their choice is between social tools X or Y or Z. It typically comes early in the conversation. And when people say ‘I’ll try it for a month and see if it brings results’ or ‘I want to see how my friend/my competitor is making out before deciding’ it usually indicates a lack of strategy, because it implies a choice between tool X and doing nothing. In that case, better do nothing.

- Social media does not substitute sales. It is however one of the most efficient ways to grow sales Here is a good explaination

Social media’s importance for B2B business is increasing. More and more owners and executives are inquiring how they can succeed in the new environment. As usual, the earlier you start the better are the chances.

Interested in reading more? Check out our other blogs:

CHATBOT PLATFORMS. How to choose the right one?

Chatbot platforms are essential tools if you need to build and run a chatbot.
There are many available on the market, big and small, popular and not so much.

Here are some useful thoughts that should help you navigate the complex world of chatbots and conversational AI solutions.

All chatbot platforms can be split into two categories: those that let you create chatbots without any programming, and those that require programming. Now, the idea that you don’t need to possess technical knowledge to build a chatbot seems appealing but the reality is not so rosy. In fact, I have yet to see a professional chatbot created without coding.
Chatbots rely on sophisticated algorithms and advanced knowledge of linguistics. These technologies are so complex that at the moment there are no plug-and-play solutions available. The companies like Chatfuel, Manychat, Flow XO and many others are attempting to fill that void and offer chatbot platforms that are simple in use. The best way to make the chatbot creation simpler is by dropping the need to code them. However this simplicity comes at a price: chatbots made without coding are limited, rigid and in general, primitive.
So to summarize: if you want to impress your girlfriend use Chatfuel. If you need a professional chatbot that delivers on your business goals and provides customer satisfaction use advanced chatbot platforms with programming capabilities.

One of the main, if not the main, tasks of the chatbot platforms is to connect your chatbot to the user interfaces. There are many ways for your chatbot to interface with the world: on Facebook messenger, on the website, on the mobile app, via SMS, on Twitter , on Skype, on Slack, on Telegram, and more. A good chatbot platform should seamlessly connect the chatbot to most of these channels. Chatbot platforms do not make your chatbot smarter. For this you need AI Engines (brief disucssion on AI Engines: http://nmodes.com/entry/2018/03/29/what-are-ai-engines-and-how-choose-one/).

For best results create your chatbot on a chatbot platform, then connect it to AI engine.

One of the top chatbot platforms on the market is Microsoft Bot Framework. It is robust, powerful, with a wide variety of useful functionality built-in. Another good chatbot platform is DialogFlow. DialogFlow has a slightly different architecture in the sense that it is a chatbot platform and an AI Engine all in one interface.

Chatbot platforms can be used to create conversation flow for your chatbot. There are several schools of thought here: some prefer to delegate conversation flow to AI engines. Chatfuel and other tools with the emphasis on simplicity (build your chatbot in minutes, no coding necessary) offer easy graphical interfaces for conversation flow creation. And there is always a reliable option to create conversation flow in an old-fashioned way, programmatically.

Which option to choose? Depends on your chatbot requirements and the business needs the chatbot is expected to address.And if you have questions feel free to ask: http://http://nmodes.com/contact-us/

The Curious Case of AI Technology

The notion of Artificial Intelligence has been around for a while.

Yet, unlike other prominent technological innovations such as electric cars or the processor speed, its progress has not been linear.

In fact, as far as industrial impact is concerned, there were times when allegedly there was no progress at all.

The widespread fascination with AI started several generations ago, in 80-s of the last century. This is when a pioneering work of Noam Chomsky on computational grammar led to a belief that human language capabilities in particular, and human intelligence in general, can be straightforwardly algorithmized. The expectation was that the AI-based programs will have a significant and lasting industrial impact.

But despite unabridged enthusiasm and significant amount of effort the practical results were minuscule. The main outcome was disappointment and AI become somewhat of a dirty word for the next 20 years. The research became mostly confined to scientific labs, and although some notable results have been achieved, such as development of neural networks and Deep Blue machine beating acting world champion in chess, the general community was largely unaffected.

The situation started to change about 5-10 years ago with a new wave of industrial research and development.

We now experience somewhat of a renaissance of AI with bots, semantic search, self-service systems, intelligent assistant programs like Siri are taking over. In addition, optimists of science are bragging confidently about reaching singularity during our lifetime.

The progress this time seems to be genuine indeed. There are indisputable breakthroughs, but even more impressive is the width of industries adopting AI solutions, from social networks to government services to robotics to consumer apps.

For the first time AI is expected to have a huge impact on the community in general.

There is this vibe around AI which hasn’t been felt in years. And with power comes responsibility, as they say, - prominent thinkers such as Stephen Hawking raised their voice against the dangers of powerful AI for humanity. Still, as far as current topic is concerned, this is all part of the vibe.

Despite all the plethora of upcoming opportunities, it is important to observe that we are yet to advance from anticipation stage. AI has not became a major industrial asset, an AI firm has not reached a unicorn status, and despite the fact that major industrial players such as IBM are pivoting towards fully-fledged AI-based model it has not manifested itself in business results.

We are still waiting for AI-based technology to disrupt the global community.

The overall expectation is that it is about to happen. But it hasn’t happened yet.