What type of B2B sales will still exist in 50 years?
Will sales jobs still exist in fifty years from now? Will robots take over all sales jobs? How will artificial intelligence redefine sales management? What long-term influence does digitisation have on B2B sales?
To discuss the future of sales, let's first present how companies made Business-to-Business sales 50 years ago and how it works today. Let’s then peep inside the crystal ball to see what sales (and marketing) can look like in the future.
Five Facts from our Predictive Sales Software that you probably don't know
Here are five interesting facts we discovered while analyzing sales transactions of B2B companies.
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How did we get to these interesting facts? Using our Predictive Sales-AI software. Our AI-based predictive sales software analyzes sales transaction data and generates accurate customer behaviour predictions (cross-selling potential, pricing, and churn risks).
Predictive Customer Analytics: From customer analysis to customer value
Customer analytics with predictive analytics can provide valuable information for sales activities.
Do you really know your customers - and not only the large-scale customers? Successful Customer Analytics should provide you with all the critical information about your customers. What are their preferences? How do they shop?
Using customer data, predictive analytics can determine individual opportunities for offers and subsequently determine the value of a customer.
B2B-Trends 2020/21: The Top 6 in Sales
Whether digital platforms, AI or chatbots. In the future, B2B sales must deal with these six critical trends.
Experts guess every year what the next hot B2B trends will be. Artificial intelligence is on the main scenario now, for B2B sales and its future development potential.
We have looked at several studies and sources and have summarized the top six you should know now.
How to improve your B2B Customer Journey with Predictive Analytics
About the b2b Customer Journey Management and how Predictive Analytics can help.
Predictive analytics, customer-centric selling, and optimization of the customer journey (CJ) have long been part of everyday life in the B2C sector. In the B2B industry, things look somewhat different. First projects are starting, the theory has already been heard and understood - but there is still a lot of uncertainty regarding the concrete implementation.
That is no wonder. There are some fundamental differences between the B2C and B2B sector. For example, business customers often have higher expectations of the business relationship. It is more important for salespeople to build a personal relationship with their customers and to know their customers.
Artificial Intelligence in Sales: B2B Algorithmic Management
Modern data-driven management in B2B sales is where Big Data meets Artificial Intelligence. Using AI for sales efficiency.
Although algorithmic management boasts a fancy, new name, managing a workforce using data is not necessarily a new postulate. Just remember that “The Principles of Scientific Management” were published by Frederick Taylor in 1911 and soon became a culprit of the data-driven management.
Algorithmic management is Taylorism in times of big data and artificial intelligence. It uses machine learning to manage and control workforces. Millions of people employ algorithmic management when ordering food, buying online or taking a cab. Millions of workers respond to algorithms. For some, the future of management, for others a depressing picture.
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B2B E-commerce Analytics: Why Predictive Analytics is now critical
Predictive Analytics in B2B e-commerce has become decisive.
The sale of products and services via B2B platforms is on the rise. However, precisely because of the intense competition for comparable offers there, companies should automatically analyze their customer data to enable a personalized customer experience and identify churn risks.
For private consumers, buying online is ubiquitous. The Business-to-Consumer (B2C) sector is dominated by e-commerce platforms such as
Industrial distribution: Identify potential for cross-selling with predictive analytics
How wholesalers and distributors recognize cross-selling potentials with predictive analytics.
Many manufacturers now sell their products directly to end consumers via web marketplaces. Unfortunately, wholesale trade and industrial distribution are coming under increasing pressure as a result.
Calculating cross-selling potentials using modern data mining can be a suitable strategy for keeping pace with the competition.
A glance at the analyses of the Federal Statistical Office shows that almost 90 % of Germans make online purchases at least once a year.
How can a classic salesforce get started with predictive analytics?
In the future, it will be all about reading customer data correctly and drawing the right conclusions for customer strategy. That means a paradigm shift for the classic, contract-trimmed salesforce.
Is the classic field salesforce as known to companies and customers - slowly but surely - dying out? The digital transformation, currently the most critical driver of change, suggests this, and it has significant implications for B2B business and for internal processes.
How to use Big Data to stop customer churn in B2B | Predicting Customer Churn
Sales leaders in business-to-business (B2B) organisations are under constant pressure to spot new business opportunities.
It is, however, a too often neglected fact, that some of their current customers will churn and recurring revenues will not return.
Besides attracting new customers, succesful B2B firms also direct their efforts into retaining existing ones.