If you keep up to date with new technologies, you have undoubtedly come across several professional articles about Predictive Analytics (PA).

According to the Harvard Business Review, experts agree that predictive analytics delivers a significant gain from your data: actionable information. Precise forecasts are the holy grail for sales decisions in the B2B sector.

But anyone who wants to use predictive analytics profitably should also understand it. For this reason, we have compiled four facts about PA that are often underestimated or ignored in practice.

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Do you know the following situation? You work for a B2B manufacturer or wholesaler, and you have some bright minds in your IT department. Data projects are a dime a dozen: in individual departments, across departments (maybe a new CRM?) and some IT people even try to create “THE ONE data analysis”.

Nevertheless, nothing works. The efforts do not pay off measurably, and the analyses wither away in archives.
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Everybody knows, B2B pricing analytics represents one of the most critical levers to boost earnings. Still, this reality is a sometimes-overlooked fact in Business-to-Business (B2B).

However, getting B2B pricing right can represent both financial success and substantial competitive advantage. Pricing is not only a driving factor in for-profits, but it also impacts how customers and markets perceive brands.
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ERP Data Mining: what we learnt from analysing 100 million of B2B sales transactions.

Data mining is the application of a varied assortment of statistical techniques to ERP datasets. Companies nowadays use data mining to predict outcomes, identify sales trends, prevent customer churn, and dynamically adjust pricing strategies.

Mining enterprise resource planning (ERP) sales data is critical in Business-To-Business, where small improvements in sales efficiency can have a significant impact on results. Mining ERP sales data helps customers to unlock a significant amount of value, discover quick-wins, and to prioritise their sales activities. Automatizing this process is possible today with the help of artificial intelligence (AI).

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Artificial intelligence in sales: our top five tips!

Sales processes, salespeople and sales management should adapt to the brave new world of artificial intelligence. Artificial intelligence is taking over the administrative tasks that consume much of the managers’ time. It is doing it faster, better, and at a lower cost. It has pros and contras. AI will redefine management.

In B2B Sales, artificial intelligence (AI) refers to Enterprise Resource Planning (ERP) and Customer Relationships Management (CRM) systems equipped with machine learning and automatized data mining features.

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