How to Implement AI-based Assistants in B2B Sales
You are considering implementing AI-based predictive analytics in your sales organisation. Are you convinced that this type of technology will give you a competitive advantage?
Then it is good to know what steps and what decisions you will have to make if you want to use an AI-based assistant in sales. AI enables you to make data-based decisions in sales. At the same time, AI-based assistants in sales do not replace sales staff. Instead, this type of technology supports and enhances the skills and capabilities of your team.
How to Improve your Pricing Policy with AI – Predicting Pricing
Most companies in the B2B sector have so far adjusted their prices based on factors such as production costs, competitive prices and supply and demand.
Especially in the current situation, both wholesalers and manufacturers are struggling with rising raw material prices. How can you pass on such a price increase without losing all your customers?
Dynamic pricing through AI-based predictive analytics, acts on a pricing strategy where companies can additionally adjust their prices for products and services based on the current customer and market situation. Thus, it is possible to make individual price adjustments per customer and product.
How does Artificial Intelligence help B2B Sales?
Artificial intelligence (AI) in sales: AI helps customers and is rapidly revolutionising the world of B2B sales.
With the ability of AI to analyse vast amounts of data and make complex predictions, AI has the potential to improve the efficiency and effectiveness of sales teams significantly.
In the coming years, advances in AI, machine learning and digitisation will replace many of the time-consuming tasks that sales teams are performing today. This game-changing trend will also affect sales management. AI will redefine sales management.
Read more
Types of machine learning (ML)
What is machine learning and what types of machine learning exist?
As part of artificial intelligence (AI), machine learning (ML) is a subcategory interested in processing and learning from vast amounts of data. It does this to make predictions that can help performance improve around a specific goal. These goals could be around forecasting, associations, clusters, regression and more.
Today, we’ll review the different kinds of ML that exist, what they are best used for and any downsides to the algorithms in this 7-minute read.
How to Realise Sales Potential with Cross- & Up-Selling in B2B Sales.
Cross-selling (also known as cross-selling) the sale of an additional product or service to an existing customer. Targeted and individually adapted to the needs of the customer, cross-selling increases customer satisfaction and is a service-oriented way to increase turnover.
"Cross-selling" offers a possibility to use internal synergy potentials and to open up rapid, attractive growth opportunities.
Read more
How to Define and Reduce Customer Churn in B2B Sales
Customer churn in B2B refers to a portion of subscribers or contract customers who change suppliers during a certain period of time. In B2B practice, some churn goes unnoticed for a long time or is only detected when it is already too late.
Have you ever wondered how you can reduce the likelihood of churn and target B2B loyalty programmes?
Read more
How to Define and Increase the Lifetime Value of your B2B Customers
Customer Lifetime Value Definition for B2B.
Sales and marketing B2B experts define customer lifetime value (CLV or often CLTV), lifetime value (LTV) or lifetime customer value (LCV) as the net profit attributed to the entire customer relationship. Sales practitioners usually referred to this value as predicted, yet it can also be a historical value.
For business-to-business sales managers and marketers alike, the ability to calculate what customers are worth is hugely appealing. That is the reason why customer lifetime value is prevalent in so many industries nowadays. CLV represents a quantitative metric and brings a long-term perspective to customer relationships.
Predictive Analytics in B2B Sales - What it is and how to get Started
Predictive analytics technologies are becoming increasingly popular and are already being used today, especially by wholesalers and manufacturers in business-to-business (B2B) sales.
Perhaps you have already made some elaborate attempts to implement predictive sales analytics with Excel or other spreadsheet programmes. Then you've come to the right place.
Predictive Sales Analytics is a modern technology to look into the future of your sales. Using machine learning methods, Predictive Sales Analytics allows you to make accurate sales forecasts: Customer churn forecasts, cross-selling forecasts and dynamic pricing.
Qymatix Academy celebrates its Relaunch
Learn online everything about AI in sales and the successful use of predictive sales analytics at the Qymatix Academy. Save 50 % on all courses with the code SELLSMART! (Courses only available in German language)
Karlsruhe, 27.04.2023. Qymatix Solutions GmbH is pleased to announce that its Qymatix Academy has been relaunched. The Academy now features an improved UX design with additional newly recorded videos. In each course, participants will also receive clear scripts that summarise the content. After the final quiz, participants acquire a certificate for each course!
Qymatix Solutions GmbH wants to share the knowledge and practical experience of AI in sales through the Qymatix Academy. The content combines the two specialist areas of "artificial intelligence & predictive analytics" and "B2B sales management or sales practice".
Read more
Five Mistakes Sales Managers Make when Dealing with AI and How to Fix them
Artificial intelligence in B2B sales and how to use it properly.
AI technologies are all the rage in sales and chances are you’re considering them for your own organisation. But what is AI really and how can you avoid the five mistakes sales managers make when dealing with AI?
We’ll help you uncover our top tips for successful AI in sales with this 7-minute read.
Read more