The Dawn of Machine Learning in the Enterprise

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Here at AMPP Group we strive to change the way businesses connect. By centering our platforms around our propriety business matching algorithm, we open up new business opportunities for our customers.

Read about Machine Learning’s growing role in enterprise via @apttus

Enterprises are struggling to find value in the massive amounts of data they generate and save every day. Machine learning, the field of computational science centered on pattern recognition, is providing the needed insights that bring greater understanding, predictive accuracy, and prescriptive intelligence to enterprises’ data sets, as well as contribute to diverse strategic outcomes.

Machine Learning’s Strategic Role in the Enterprise

Unlike advanced analytic techniques that seek out causality first, machine learning techniques are designed to seek out opportunities to optimize decisions based on the predictive value of large-scale data sets. Data sets are comprised of both structured, i.e. highly organized data like that in databases, and unstructured data, i.e. less organized data like text in a sales contract or web traffic. The global proliferation of social networks is fuelling the growth in the latter type of data, making it increasingly important for companies to effectively leverage their unstructured data.

In enterprise businesses, machine learning is proving to be effective at handling predictive and prescriptive tasks, allowing these companies to define which behaviours have the highest propensity to drive desired outcomes. Enterprises eager to compete and win more customers are applying machine learning to both sales and marketing challenges.

Machine Learning Role in Enterprise

  1. At least 40% of UK companies are already using machine learning to improve sales and marketing performance. Two out of five companies have already implemented machine learning based intelligence in sales and marketing.
  2. 76% of companies say they are targeting higher sales growth with machine learning. Gaining greater predictive accuracy by creating and optimizing propensity models to guide up-sell and cross-sell is where machine learning is making contributions to omni-channel selling strategies today.
  3. Several European banks are increasing new product sales by 10% while reducing churn 20% using machine learning intelligence.

Machine Learning Acceleration

For enterprise businesses, machine learning has the ability to scale across a broad spectrum of business processes. Those directly related to revenue-making, often called Quote-to-Cash, are among the highest value applications and include sales, contract management, customer service, finance, legal, quality, pricing and order fulfilment.

The economics of cloud computing, cloud storage, the proliferation of sensors driving the Internet of Things (IoT) connected devices growth, and pervasive use of mobile devices that consume gigabytes of data in minutes are a few of the numerous factors accelerating machine learning adoption today. Add to this list the many challenges of creating context inside of search engines, as well as the complex problems companies face optimizing operations while predicting most likely outcomes, and the perfect environment is set for machine learning to proliferate dramatically.

Where Machine Learning is Delivering Business Outcomes Today

The good news for enterprises is that all the data they have been saving for years can now be turned into a competitive advantage and lead to the accomplishment of strategic goals. Revenue and senior management teams are concentrating on how they can capitalize on machine learnings’ core strengths to transform the strategic vision of their businesses into a reality. These teams are focusing on business outcomes first and are looking for machine learning to accelerate and simplify, determining which factors most influence buying behaviour and lead to goals being accomplished.

Sales, marketing, and channel management teams are using machine learning to optimize promotions, while compensation and rebates drive the desired behaviour across selling channels. Predicting propensity to buy across channels, making personalized recommendations to customers, forecasting long-term customer loyalty, and anticipating potential revenue and credit risks of buyers are some specific applications of machine learning right now.

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AMPP’s Latest Project

Working in partnership with the Commonwealth Enterprise and Investment Council (CWEIC) AMPP Group have successfully rolled out their proprietary business matching technology to bring companies from across the Commonwealth together on a members-only digital platform, in order to showcase their products and services across international markets. (www.tradecommonwealth.com)

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