Skip to main content

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provider, or is an outdated stack still being used?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.

Comments

Post a Comment

Popular posts from this blog

Customer Engagement with Chatbots and Collaboration Bots: Methods, Chances and Risks of the Use of Bots in Service and Marketing

 Relevance and Potential of Bots for Customer  Obtaining information, flight check-ins or keeping a diary of one’s own diet—all of this is possible in dialogue today. Customers can ask questions via Messenger or WhatsApp or initiate processes. This service is comfortable for the customer, available at all times via mobile and promises fast answers or smooth problem-solving. A meanwhile strongly increasing number of companies is already relying on this means of contact and the figures on chat usage speak in favour of this means supplementing or even replacing many apps and web offers in the future. The reasons for this are manifold. Figures of the online magazine Business Insider 1 reveal a clear develop- ment away from the public post to the use of private messaging services such as Facebook Messenger or WhatsApp. Facebook meanwhile has a user base of around 1.7 billion people worldwide; 1.1 billion people use WhatsApp, and Twitter can nevertheless still record 310 million us...
Post a Comment
Read more

Robot Journalism Is Becoming Creative

 Algorithms are able to automatically search the Web for information, pool it and create a readable piece of writing. In addition, data-based reports in the area of sport, the weather or finances are already frequently created automat- ically today. Recently, for example, merely a few minutes after Apple had announced their latest quarterly figures, there was a report by the news agency Associated Press (AP): “Apple tops Street 1Q forecasts”. The financial report deals solely with the mere financial figures, without any human assistance whatsoever. Yet, AP was able to publish their report entirely via AI in line with the AP guidelines. For this purpose, AP launched their corresponding platform Wordsmith at the beginning of 2016, which automatically creates more than 3000 of such financial reports every quarter, and which are pub- lished fast and accurately. It is no longer that easy to distinguish between whether an algorithm or a human has written a text. Another exception of rece...
Post a Comment
Read more