Social selling for businesses

sasha uritsky

Jan 03, 2015

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:

nmodes Is Helping Businesses to Succeed

With the launch of the new dashboard nmodes is helping businesses to drive traffic and grow sales.

For example, One of our clients needed to increase traffic to their website while at the same time improve the conversion rate. In other words, they wanted to see more quality traffic.

The client made a concentrated effort on social media, however they were having difficulties in finding the target audience - traditional keywords search resulted in too much noise and did not produce desired outcome.

nmodes dashboard simplified this client’s engagement process. We created a dedicated stream that accurately addressed their targeted audience. nmodes dashboard is actionable, so their engagement became easy. nmodes technology identifies potential customers accurately, and so their engagement became efficient.

As a result, the click thru rate rose up to 65%, traffic quality improved by 25%, and conversion increased to 6-8%

Another client relied heavily on mainstream dashboards (such as Hootsuite) These tools do not do a good job finding relevant conversations, in the process producing too much noise and forcing client’s community managers to spend long hours manually identifying these relevant conversations. The client manages multiple social account and this type of manual labour was impeding the business, both in terms of costs and efficiency.

nmodes produces highly accurate results in finding relevant conversations that do not require manual clean up. The client started using nmodes solution, and immediately freed a substantial amount of hours which enabled them to consecrate on servicing their customers and acquiring new ones.

Towards smarter data - accuracy and precision

There is a huge amount of information out there. And it is growing. To make it efficient and increase our competitive advantage we need to evolve and start using information in a smart way, by concentrating on data that drives business value because it is accurate, actionable, and agile. Accuracy is an important measure that determines the quality of data processing solutions.

How accuracy is calculated?

It is easy to do with structured data, because the requirements are formalizable. It is less obvious with unstructured data, e.g. a stream of social feeds, or any data set that involves natural language. Indeed, the sentences of natural language are subject to multiple interpretations, and therefore allow a degree of subjectivity. For example, should a sentence ‘I haven’t been on a sea cruise for a long time’ be qualified for a data set of people interested in going on a cruise? Both answers, yes and no, seem valid.

In these cases an argument was put forward endorsing a consensus approach which polls data providers is the best way to judge data accuracy. This approach essentially claims that attributes with the highest consensus across data providers is the most accurate.

At nmodes we deal with unstructured data all the time because we process natural language messages, primarily from social networks. We do not favor this simplistic approach, as it is considered biased, inviting people to make assumptions based on what they already believe to be true, and making no distinction between precision and accuracy. Obviously the difference is that precision measures what you got right, and accuracy measures both what you got right and what you got wrong. Accuracy is a more inclusive and therefore more valuable characteristic.

Our approach is

a) to validate data against third party independent sources (typically of academic origin) that contain trusted sets and reliable demography. Validating nmodes data against third party sources allows us to verify that our data achieves the greatest possible balance of scale and accuracy.

b) to enrich upon the existing test sets by purposefully including examples ambiguous in meaning and intent, and providing additional levels of categorization to cover these examples.

Accuracy is becoming important when businesses move from rudimentary data use, typical of the first Big Data years, to a more measured and careful approach of today. Understanding how it is calculated and the value it brings helps in achieving long-term sustainability and success.