Senior Account Manager
Posted on January 22, 2018
You’ve invested a lot of time and money into the implementation of a management information system that tracks impressive data such as marketing interactions and sales activity. All of this data is great, but what should you really be doing with it all?
Most of us are too busy to delve into the data ourselves and even if we had skilled team members to help analyse and understand the information, many companies are now facing the issue of big data – a data set so large and complex that humans and traditional analysis methods are unable to deal with the information. As a result, business decisions are often made without adequate material.
Machine learning is an application of artificial intelligence that gives computer systems the ability to automatically learn and develop without being programmed to do so. Consumer sales and marketing are already benefiting from this technology, using programmatic buying and audience signals to reach specific audiences, using the data generated to improve marketing effectiveness.
Digital marketers have started to explore the benefits of machine learning and the opportunities it presents for B2B marketing.
When faced with big data, machine learning can process the vast volume of data, comparing thousands of variables quickly and efficiently. This information is then correlated into an unbiased outcome, enabling the machine to forecast and predict future conclusions with a high degree of accuracy.
Typically the buying cycle for a B2B product or service is significantly longer and more complex when compared to B2C purchases. The speed of machine learning can help marketers to quickly get to know their customers and respond to findings with the objective of closing the sale as efficiently as possible.
It can take a huge sales team to source and qualify new business leads, searching social media platforms, company websites and more. Machines can help to gather this information and analyse qualitative data such as emails, phone calls and interactions to determine who is a good prospect.
Fortunately, not everything can be completed by machines and the execution of decisions is still very much a human process, requiring creative and emotional intelligence.
It’s inevitable that machines will soon take over many human functions in the workplace as it becomes more and more difficult to keep up with the pace of the world through human processes. The question is, will machines one day have the capability to also make creative and emotional decisions?
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