Author: David Wolf

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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Correlation does not equal causality – KPIs in Sales

Watch your step! Sales managers and managing directors in B2B confuse correlation and causality.

Data-based decisions in sales are not always ad-hoc better than intuition. The reason for this is the frequent confusion between the terms causality and correlation.

How nice it would be if managing directors or sales executives regularly knew why something happened. Why individual customers churn; why one product does not sell well or sells more than others; why in the end a promising sales lead does not become a customer, regardless of how good our salespeople are.

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b2b-distribution-kpi

The Most Important KPIs in Distribution and the Influence of AI

Key Performance Indicators (KPIs) are also used to manage companies in the retail and wholesale sectors.

AI in the form of predictive analytics can establish correlations between individual KPIs and thus provide recommendations for action.

Numerical parameters are necessary to understand the current situation of a business. Key Performance Indicators (KPIs) are indicators that can be used to measure and determine the performance or degree of fulfilment of pre-defined objectives within a company.

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