Why a CRM System with Predictive Sales Analytics and AI?
CRM and Sales Analytics: In this article, you will learn what you can expect from a CRM system with artificial intelligence.
Using CRM systems have long been a common practice in large companies today, even if not always successfully implemented. Small and medium-sized enterprises (SMEs) often still have some catching up to do.
Meanwhile, the next expansion stage has long been underway. Predictive sales analytics/artificial intelligence (AI) is being added to the CRM systems.
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.
Why is internal data considered more reliable and easier to collect than external data?
Simply explained: Why internal data is better for predictive analytics in B2B.
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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What is a Predictive Score Model in B2B Sales? How Can You Create Yours?
A predictive score model is a formula to calculate a probability.
There is a 70% chance that you will read this entire article. How do I know this? Because I used a predictive score model. The score is the probability of you reading to the end of the article (or one minus the likelihood that you will not – the exact opposite).
My example in the paragraph above is a well-known application of predictive analytics in marketing. The most common examples in business-to-business (B2B) sales are lead scoring, churn (or customer attrition), cross-selling, and pricing.
How Predictive Sales Analytics Works and Why It Matters
AI-based programs help your sales team to sell products are services more efficiently. The programs make predictions about your customers' behaviour: who will churn? Who might pay a different price or buy an additional product?
The technology behind this is called "predictive analytics" or, in sales terms, "predictive sales analytics".
Study: Automated, Artificial Intelligence (AI)-based pricing versus Human-based pricing in B2B
To further explore the potential of automating the B2B salesperson’s pricing decisions.
You'll learn the results of a field experiment conducted by Yael Karlinsky-Shichor (School of Business at Northeastern) and Oded Netzer (Columbia University) to explore "Who makes better pricing decisions in B2B settings - humans or machines?"
We now know that algorithms and artificial intelligence are part of our daily lives. The general trust in systems like Google Maps is relatively high when looking at the number of users utilizing the platform.
Nevertheless, it often happens that we see a route suggestion that causes us to frown and think, "That seems weird to me. I don't think that's right."
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.
How to measure sales success correctly
That is a topic that is on the table repeatedly in almost every company and every sales organization and often leads to considerable disputes. It is also a topic that can frequently lead to the demotivation or churn of sales staff.
Predictive Analytics: Questions and Answers
This article answers the most asked questions about predictive analytics (PA), according to Google. Predictive analytics is a technology that allows you to look into the future.
Especially in the last two to three years, we have noticed a significant increase in interest in predictive analytics technologies, their possibilities, and their functionalities.
In 2015, we tried to find out what was frequently searched in the area ofpredictive analytics. Other than the question “What is predictive analytics?” no beneficial results came up.
Pricing in B2B: will AI replace salespeople?
When will AI replace Sales Jobs in Pricing, and what can you do about it.
Will AI replace sales jobs? Short answer: no. Long answer: it depends.
Artificial intelligence replaces skills and tasks, not people. While AI for sales might be overhyped now, it still follows known rules of innovation. If some technology takes decades to change the way we work, it cannot be considered disruptive. Advances in AI are slowly eroding the bulk of manual pricing processes.