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Sales and Marketing Reloaded—Deep Learning Facilitates New Ways of Winning Customers and Markets

 Sales and Marketing 2017

“Data is the new oil” is a saying that is readily quoted today. Although this

sentence still describes the current development well, it ides not get down

to the real core of the matter; more suitable would be “artificial intelligence

empowers a new economy”. The autonomous automation of ever larger

fields of tasks in the business world will trigger fundamental economic and

social changes. Based on a future world in which unlimited information is

available on unlimited computers, ultimate decisions will be generated in

real time and processes will be controlled objectively. These decisions are not

liable to any subjectivity, information or delays.

In many sectors of the economy, e.g. the public health sector or the

autonomous control of vehicles, techniques of artificial intelligence (AI)

are applied and increase the quality, availability and integrity of the services

offered. The same development can be observed in the field of sales and marketing. Today, companies no longer allow themselves to be recorded by turnover, commercial sector and other company master data. Presence and active


communication on the Internet, be it the website or in social networks,

today belong to a company’s everyday routine. The efficiency of a sales or

PR campaign heavily depends on the choice of companies and people to be

addressed. Are they interested in the subject? Is this a well-chosen point in

time? Has the company just concluded a contract with an innovative CMS

provider, or is an outdated stack still being used? Classical sales and marketing approaches define target groups by way of simple selections or segmentations. Companies are selected on the basis of commercial sectors and sales

margins and transferred into the sales process.

Prior to the first call by the sales team, little can be said about the prob-

ability of the conversion with this approach. There is neither data nor

a method available to make a forecast about whether the prospective customers can really be won over as a customer in the sales funnel. Yet, for an

efficient and agile sales process, having extensive and up-to-date data is crucial. The establishment and development of individual leads in issues of the

topics they focus on, their sales forecasts and their digitality are crucial for

successful communication. Accordingly, an ideal system should make a sure

prediction as to which prospective customer will be the next to sign a con-

tract. This way, the sales team can achieve the maximum conversion rate.

The high complexity of the data and the high dynamics this data underlies are a typical field o application for deep and machine learning algorithms. In the following, I will illustrate how these are applied to the field of

automated lead prediction.

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