Jan

Social selling for businesses

Social selling is one of the hottest buzzwords in the technology market. The popularity of social networks made the customer interaction and buyers hunting easier than before. More and more consumers are using social media to find deals, research products and make recommendations.

From the seller’s perspective the efficient use of social media is based on the mastery of following two major steps:

1. Finding the relevant audience,

2. Engaging with that audience.

The first step should be automated. This is exactly where the promise of Big Data, or Smart Data, as they now begin to call it, is supposed to come into fruition. Finding relevant information in the ocean of social data is the poster example of how Smart data can help businesses in the new world defined by computerized systems and networks. The companies should be able to use programs and solutions that accurately and efficiently deliver relevant data. If the company is spending time to sift through the ever increasing informational stream without automating the process, it is wasting precious time thus compromising its business growth and eventually losing competitive edge.

 The second step however is inherently manual. it is not a good idea to automate the engagement process. Social networks are designed to build trust, and trust cannot be won automatically. So it requires time and effort and knowledge. It also requires patience - trust cannot be built in minutes.

It is important that businesses looking to add social media into their arsenal of revenue channels, and we believe that all businesses should do just that, grasp this two-steps process. A clear understanding of the nature and requirements for each of the steps helps to plan strategically, manage the resources properly and avoid costly mistakes.

 

                               

Interested in reading more? Check out our other blogs:

Integrated Real-Time Data Boosts Content Delivery

How to make content more relevant and appealing to the content consumer?

This is a problem that has been on the mind of content creators for some time now. In our age of information abundance it is not easy to stand out and make your voice heard. The competition for the consumer’s attention is escalating, and with the number of information sources ever increasing, it will only get tougher.

Traditionally, a content delivery does not change across the target audience. A commercial, or a blog, looks and is experienced in the same way by all viewers and readers. We are entrenched in this paradigm, and can hardly imagine it being otherwise.

It turns out, the advancement of new technologies capable of capturing individual intents in real time brings up new opportunities in creating personalized experiences within the framework of content delivery.  

This is how content can become more relevant - by becoming more personalized.

In a rudimentary form, we are already familiar with this approach as seen in online advertising. Some web and social resources aim at personalizing their promotional campaigns based on whatever drops of behavioural patterns and interests they can squeeze out of our web searches.  The problem, of course, is that the technologies used to power these campaigns understand human behaviour poorly and results, therefore, more often than not leave a great deal to be desired. To put it mildly.

nmodes has been working on semantic processing of intent for several years. We now can capture intent from unstructured data (human conversations) with accuracy of 99%. (Interestingly, many businesses do not require this level of accuracy, being satisfied with 90%-92%, but we know how to deliver it anyway).

We recently started to experiment with personalizing content by using available consumer intent.

We used Twitter because of its real-time appeal.

We started by publishing a story, dividing it into several episodes:

 

And we kept the constant stream of data flowing, concentrating on intent to dine in Paris:

We then merged the content of the story with consumer intent to dine in Paris as captured by our semantic software. Like this:

This merging approach shows promising results - the engagement rate jumped above 90%.

Overall we are only at the beginning of a tremendous journey. We know that other companies are beginning to experiment, and the opportunities from introducing artificial intelligence related technologies into content delivery are plentiful.

There is a long road ahead, and we've made a one small step.  But it is a step in a very exciting direction.

 

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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.

 

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