Big Data

All About ERP Data Mining for Sales

All About ERP Data Mining for Sales

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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KI Systeme Vertrieb

Will Artificial Intelligence be Picasso of Tomorrow?

Can Artificial Intelligence be creative?

The cover picture shows the faces of four people. One person does not exist – artificial intelligence (AI) created it. Can you guess who? Number 1, 2, 3 or 4? Read the article to the end and we will tell you.

Today we stray a bit from our usual focus on modern data analysis with predictive analytics and B2B sales. We dedicate ourselves to the question of whether artificial intelligence can be creative.

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predictive sales software

Forecasting individual Customer Lifetime: Why you should not use external data

There are two types of historical data to use for predictive analytics and sales forecasting: internal and external data. How to know which one to choose?

Making a forecast always requires planning under conditions of uncertainty. Successful sales executives plan and execute an accurate sales forecast using data. For an aggregated, precise sales plan, it is necessary to consider forecasting the individual customer lifetime of the client base.

There are different data sources that executives can use to forecast sales. Some of them count for internal, some for external factors.

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Predictive Analytics in B2B: 3 Ideen für Vertriebsleiter

Are you a sales manager with Big Data? Here are three Predictive Analytics examples for B2B

With predictive analytics, big data becomes a big opportunity for B2B sales managers. This significant opportunity requires, however, a profound understanding of the sales situation, coupled with an understanding of big data mining models available.

 

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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.

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