Enterprises are entering a new era, an era that is ruled by data. Back in the day, artificial intelligence (AI) was a realm of science fiction. But, now it is being used in business intelligence. The key AI technologies such as machine learning (ML), deep learning, natural language processing (NLP), and computer vision enable organizations to establish a significant lead over their competitors.

It is never a simple process for organizations to incorporate AI technologies into their business intelligence setup. In the first few years, they had difficulties in organizing and analyzing the collection of big data. Intelligent behaviour needs substantial knowledge. Therefore, most AI work now involves machine learning because “learning” is the easiest way to obtain that knowledge.

When AI gains momentum, the prominent software development companies able to go beyond building traditional software to bring more holistic solutions.  Software development companies simplify AI technologies for organizations to aid in their intelligent enterprise transformation. These amazing platforms are capable of automating analytics processes and other business intelligence in a better way.


What Machine Learning Can Do to Improve Sales?

Well, to understand what potentials machine learning can bring to improve sales, let’s look into the core concept of machine learning. 

Machine learning is a branch of artificial intelligence that replaces traditional statistical techniques. Machine learning gives the computer systems the ability to automatically learn from the data without being programmed explicitly. In the simplest form, machine learning uses past experiences (collected as data) to understand the patterns to forecast future outcomes.


What is machine learning and what it does


Likewise, artificial intelligence utilizes the sales data particularly the won/lost opportunities history reports to predict the chances of winning for new sales opportunities. With the help of machine learning – machines are getting trained to read, see, listen, interact and understand their environments for better analytics. Even more, these can help people to automate and scale their routine tasks with ease. We can get benefit from the large volume of data and can take advantage of this data like never before. And this has become possible because of massive improvements in data processing software and hardware.


Why Companies are Investing in AI and Machine Learning Implementation?

AI technologies adopters are harnessing machine learning algorithms to determine insights and trends in vast reams of data. Those data are used to generate accurate predictions. They use these actionable insights to make real-time decisions to defend their market position and build a competitive advantage. Machine learning capabilities can be leveraged to magnify workflows between humans and automation.


Value chain with machine learning


SAP AI and Machine Learning

SAP is one of the biggest software providers has announced enhancements to its Next-Generation Support concept.  AI and Machine Learning integration into SAP business management system provide better opportunities for organizations to get more targeted results.

” The Intelligent Enterprise requires speed and precision, and the continued integration of machine learning and AI into the Next-Generation Support concept has enabled us to provide just that. These intelligent technologies enable our support tools and support specialists to learn from the past and deliver accurate solutions for inquiries in real-time as well as customized, proactive recommendations before an incident shows up.”

Andreas Heckmann, global senior vice president and head of customer success services, SAP Digital Business Services.


Machine Learning and SAP Sales Cloud

Business organizations implement SAP Sales Cloud to manage information databases that they have collected throughout their journey. In short, it can ingest and replicate structured data such as customer information and sales transactions from applications, relational database, and other sources. This solution can be run on-premise via the servers of the company or through cloud hosting.

The most outstanding feature of the latest version of SAP Sales Cloud is the “opportunity of scoring” or “opportunity intelligence”. An artificial intelligence-based system in this version can build an effective scoring criterion on its own. It goes through the data and begins the process of patterns identification. Whereby, it can identify the data linked with the won deals. Subsequently, it works to make calculations based on certain criteria and score them on the chances of a win.

Moreover, the opportunity scoring collects entire closed opportunities and removes the sales reports which contain zero transaction history. Thereby ensuring only the balanced data is being scored. The scoring model uses the data of at least one historic year depending on the size of the organization. Furthermore, the data is refreshed every quarter. And these data will be applied to predict new opportunities accurately.


Are you keen on reading more about how SAP Sales Cloud works?  Check out our Machine Learning for SAP Sales cloud blog. 


How SAP’s Lead Intelligence and Account Intelligence Support the Sales Team?

Lead Intelligence

Almost 70 per cent of leads generated for business to business (B2B) are not ready for sales. Thus, the sales team is wasting so much of its time on targeting the customers who are wrong-fit. This is the reason why you must think about having a sanity check on your pipeline. However, AI-based lead scoring can help the marketing and sales team to work more upon the leads which are sales-ready in a more effective way.

SAP’s artificial intelligence can help business organizations to make faster decisions as the machine learning algorithms are prioritizing automatic decision making. It can flag better opportunities to take immediate options too.

Artificial intelligence in SAP


Account Intelligence

Most of the sales organizations are struggling with the accounts data that is siloed across various applications. There are no engagement metrics and no real-time intent at an account level. The lead contact scoring alone can’t give a complete picture of the sales process. Therefore, account insights will also help the organizations to target B2B accounts with the highest chances to buy or close while maximizing the value of a lifetime. Besides that, it helps the sales teams to understand accounts health. Also, they can use the insights into account-based nurturing and selling processes.



With smart and intelligent machine algorithms you can get a better opportunity to complete the business processes more efficiently. Moreover, triggering intelligent actions can help organizations to bring newer opportunities or reduce risks in the best possible way.


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