Predictive Sales Analytics in Excel? Yes, you could!
How to do predictive analysis in Excel: One Useful Example of Predictive Sales Analytics & Predictive Modeling in Excel
One of the critical tasks of a sales manager is to timely identify which opportunities have better chances of closing and what makes a “good” sales opportunity. Getting this job right is the essence of successful sales planning.
Key Account Managers in B2B typically serve hundreds of customers and oversee dozens of new and existing sales opportunities. They have limited time and represent one of the most valuable resources any company can have.
Four Situations Where you Should Not use Machine Learning
Machine learning (ML) is a great technology. But does it really have to be used all the time? This post is about four situations where you shouldn't use machine learning.
There is (rightfully) a lot of hype around artificial intelligence and machine learning (ML). As we said, great technologies and use cases are emerging from it. You can also find many examples that use machine learning in our blog articles. But in which situations is machine learning not necessary?
Remember, there are always exceptions to the examples to come. However, your AI project will probably be five times more difficult if these examples apply.
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Forecasting Individual Customer Lifetime Value: 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 factors while others count for external factors.
Applications of Machine Learning in the Real World
Learn about four real-world applications of machine learning here.
When you travel to a new country, have you ever had to translate a word quickly? Or how about when you are sending a reply to an email using the Gmail application? Do you notice that there are recommendations of what to reply? The examples above make use of machine learning.
From computerized translators, to email recommendations, as well as movie suggestions on Netflix, to autonomous cars. All of this is possible due to machine learning. But what is machine learning?
Machine learning is a concept that falls under the category of artificial intelligence. It is the process by which computers change the way they perform tasks by learning from new data sets. In this process, algorithms mimic the way humans learn to gradually improve their accuracy.
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Predictive Sales Forecasting: Answers to 5 Questions of Salespeople
Why should we use predictive sales forecasts in sales? This article is aimed at anyone thinking of using AI for more efficient sales planning and sales management.
Every Saturday morning, Mr. Meier visits the magazine store around the corner to buy the weekend edition of his favourite newspaper. This has been going on for half a year now. The saleswoman knows Mr. Meier by now, and because he stops by every Saturday, she always addresses him with the same question as soon as he enters her store: "Good afternoon, Mr. Meier! The weekend edition, as usual?"
For Mr. Meier, buying his newspaper on the weekend has become a ritual. It's a pattern that repeats itself every week. The saleswoman has recognized this pattern and addresses Mr. Meier about it, almost automatically.
