Preiskorridor mir Excell

How to make a price corridor analysis in excel in three simple steps

This article describes a step-by-step introduction to price corridor analysis with Excel.

You will learn the meaning of a price corridor and how to create a price corridor from a list of sales transactions in your ERP system.

Let us disclosure that our software uses AI-based data mining methods to present a B2B pricing strategy to Key Account Managers. Based on these data mining algorithms and techniques, we would like to discuss how any sales representative can create a price corridor for predictive analysis using Excel.

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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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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.

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Predictive Sales

Simply explained: Why internal data is better for predictive analytics

Many companies are sitting on a treasure: their own sales data. This is an enormous advantage for the application of predictive analytics.

Companies use sales forecast to make business decisions. They also employ them to predict future developments better than their competitors. However, reliable predictions are rare, and sales teams try to play a safe card by applying external forecasts. Companies are nevertheless better off using their in-house data – with predictive analytics.

“There are three types of lies: lies, damn lies, and statistics.” This quote from Benjamin Disraeli, a British statesman and 19th-century novelist, fits the situation in companies very well.
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Kundenbindung statt Kundenabwanderung mit Qymatix

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.

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