How To Accelerate B2B Sales Growth With One Proven Strategy
Revenue stagnation is a nightmare most managers are scared to dream. If a market is growing in line with the economy and income stagnates, then market share is approximately contracting, and a company is becoming irrelevant. No manager wants that.
Data Mining ERP in B2B Wholesale & Distribution
B2B sales managers and managing directors of specialised wholesalers in Germany face many challenges in today's competitive business environment.
The rise of e-commerce has made it necessary for wholesale distributors to leverage data mining in ERP to stay ahead of the competition.
By analysing wholesale customer data and implementing artificial intelligence in their ERP, B2B wholesale distributors can gain valuable insights into customer behaviour, identify the most profitable products, and find the optimal final price for each customer. They can also retain customers before they lose them.
Read more
Predictive Sales Analytics: Can you anticipate your customers’ journey?
Nowadays, new technologies enable a highly detailed understanding of the way customers buy, fancily known as “digital customer journey”. They also allow a cost-effective application of predictive analytics in Business-to-Business (B2B) sales.
The Art of Artificial Intelligence in B2B Sales
AI in B2B sales: How exactly can B2B companies use Artificial Intelligence to support their sales?
The applications of artificial intelligence (AI) are very diverse. It is not without reason that big players such as Apple, Facebook, Google or Samsung pour billions in the development of new AI technologies.
The management consultancy KPMG estimates that global AI investments will increase from twelve billion US dollars (2018) to 232 billion by 2025.
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.
Market Basket Analysis in Excel - Example for Cross-Selling in B2B
One Useful Example of Predictive Sales Analytics Using Excel
Cross-selling is the practice of selling an additional product or service to an existing customer. Indeed, B2B companies define cross-selling in general and cross-selling analytics in particular, in many ways and with many names. One common naming used in retail or distribution is “market-basket-analytics”.
Most of us are familiar with cross-selling from our experience as online consumers. “Customers that bought X also bought Y” or “related products”. E-commerce websites make product suggestions based on a market basket analysis. The list of the possible suggestions is also known as “associating rules”. Marketing practitioners talk about “Buying Propensity”.
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.
What type of B2B sales will still exist in 50 years?
Will sales jobs still exist in fifty years from now? Will robots take over all sales jobs? How will artificial intelligence redefine sales management? What long-term influence does digitisation have on B2B sales?
To discuss the future of sales, let's first present how companies made Business-to-Business sales 50 years ago and how it works today. Let’s then peep inside the crystal ball to see what sales (and marketing) can look like in the future.
Data Mining in ERP for Sales - All About It!
ERP Data Mining: what we learnt from analysing 100 million of B2B sales transactions.
Data mining is the application of a varied assortment of statistical techniques to ERP datasets. Companies nowadays use data mining to predict outcomes, identify sales trends, prevent customer churn, and dynamically adjust pricing strategies.
Mining enterprise resource planning (ERP) sales data is critical in Business-To-Business, where small improvements in sales efficiency can have a significant impact on results. Mining ERP sales data helps customers to unlock a significant amount of value, discover quick-wins, and to prioritise their sales activities. Automatizing this process is possible today with the help of artificial intelligence (AI).
How to define customer churn in B2B?
B2B Churn Rate: Definition and Calculation.
Business-to-Business (B2B) companies depend on building and developing long-term relationships with their customers to be financially successful.
However, over time, some customers will stop buying or will defect to the competition. Sales managers define this situation as “churn” or “customer attrition”. Managing and reducing customer churn is one of the most important, yet sometimes overlooked job of the sales leader.
Read more