Artificial Intelligence in a Construction Machinery Company
Artificial intelligence technology can be used in a wide variety of areas. In this article, you will learn how AI was used in a mechanical engineering company.
I've already written a few posts on this blog about Artificial Intelligence (AI) in sales. Simply a fascinating topic for an old sales hand like me who has worked with several different CRM systems as well as sold AI systems.
For someone in sales, the area of predictive analytics is particularly interesting - an AI is able to predict sales opportunities. That's why I report on a specific case study below.
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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.
How to use Predictive Analytics in your CRM for Truly Data-Driven Decisions?
Successfully implementing Predictive Analytics for data-driven decisions in your CRM requires more than just software.
Every successful sales team wants to become data-driven. Companies that successfully execute predictive analytics in their CRM are easy to identify.
They take care of their salespeople and successfully utilise their current data and processes. They employ the standard software and adapt them to their situation. Finally, they introduce Predictive Sales to CRM step by step and learn from their experience.
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.
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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Why is Predictive Sales Analytics a “Must-Have” to Increase Sales Productivity in Business-to-Business?
Predictive Sales Analytics is a Game-Changer in B2B.
Productivity in business-to-business (B2B) sales is simply defined as the output rate of a sales team, considering all direct costs and performance. Two trends that are drastically affecting sales productivity are sales analytics in general and predictive sales analytics in particular.
Sales analytics is since long an efficient method to measure what is working and what is not working in sales. This is then used to compare performances in order to increase revenues.
How Predictive Sales is Transforming the KPIs You Must Be Measuring
A straightforward question: is your sales team using the same sales performance KPI they did five years ago? If your answer is yes, you better watch out, you might not be using the right KPIs.
Of course, sales per quarter and sales quota attainment are still sensible KPIs to measure. However, total revenues or sales vs quota are lagging indicators. They are “slow KPIs” in the nowadays dynamics B2B sales world. They come way too late.
B2B Predictive Analytics - Successful Data Management
How to make data work for your B2B sales team while avoiding common pitfalls in data management
We can associate power with strength, force and influence, but also with destruction and violence - the typical two sides of a coin.
Sayings like “data is the new oil” or “data is a valuable asset” are on everyone’s lips in the age of Big Data. These statements might hide a profound truth, nevertheless. If used rightly, data is worth its weight in gold for a company.
Why Projects using AI in B2B Sales fail and yours will too
Successful organizations do not underestimate the complexity and hidden costs of artificial intelligence (AI) projects.
Artificial intelligence (AI) for sales has become an arms race. Correctly employing it will separate the winners from the losers in Business-to-Business (B2B). There are, however, very high chances that your AI project will not deliver the promised ROI or will ultimately fail.
How B2B Data Analytics is Changing Sales
How Big Data and Advanced Analytics Are Revolutionizing Sales in B2B, and What Managers Should Know About It.
B2B customer buying experience is radically changing. This trend has led to dramatic changes in the sales profession over the past decade.
“Nothing is so painful to the human mind as a great and sudden change”, wrote Mary Wollstonecraft Shelley in Frankenstein. Sales management in B2B is experiencing an abrupt and rapid transformation.