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.
BI
The difference between Business Intelligence (BI) and Self-Service BI and why Qymatix is not a traditional Self-Service BI solution.
2018 said Carlie J. Idoine, Research Director at Gartner:
“The trend of digitalization is driving the demand for analysis in all areas of modern business and administration.”
That’s right. Not only large companies and big players, but also more and more SMEs have recognised the value of data analysis: Data-supported decisions to achieve corporate goals.
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.
How can your B2B sales team take fact-based decisions faster using your CRM and ERP data?
B2b companies are investing in modern lead management. The focus is on the online channel.
Modern lead management with a well-thought-out lead strategy, consistent lead evaluation and prioritisation and powerful tools ensures that marketing resources are used efficiently and effectively in marketing.
What happens once leads have become customers?
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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.