Working in association with organizations, US21 helps its customers create a predictive analytical ability utilizing a framework that distinguishes patterns in your historical information utilizing data mining techniques, while searching for new opportunities to decrease costs and increase profits.
The aim of predictive analytics is to predict future behavior or events utilizing the information you hold about things that have effectively happened. Predictive analytics has been around for quite a while, yet it is just now becoming standard and numerous organizations are unsure of what it is or where it fits into their organizations data strategy.
This is mostly in light of the fact that it depends on having admittance to quality information in a format suitable for business examination, for example, business analysis, such as that available from a well designed data warehouse. The procedures involved are more advanced than enterprise reporting & business analytics and the level of business comprehension is higher, requiring reliable and well-established data and information governance.
US21’s framework takes the best of the industry-standard CRISP-DM (Cross-Industry Standard Process for Data Mining) and applies an ‘agile’ overlay to make it more responsive for internet-paced market change. Our flexible approach ensures models remain current and effective, even for near real-time analytics. This avoids the trap of spending too long on building models in concrete only for them to quickly degrade as the business world around them changes.
Companies in a wide range of markets including energy, utilities and mining, telecoms, pharmaceuticals, retail, healthcare and financial services that fail to use their data proactively are missing out on a whole range of benefits. These include steady and incremental profitability improvements through promotion and pricing optimization; the quick creation of new data models to support a single view of the customer; and more successful up-sell, cross-sell and retention through personalised consumer engagement. Using predictive analytics, companies can grow revenues and reduce outbound marketing costs by improving response rates through refined targeting with offers tailored to specific customer needs.
Predictive Analytics Engagement
Predictive Analytics from the start, we work directly with your business people and your data. Particularly for predictive analytics, it is vitally important to develop a clear understanding of the business meaning of the data, because inferences will later be drawn from it and potentially far-reaching action taken as a result. Often US21 consultants bring fresh eyes to help client staff members clarify their own understanding and make sure the most valuable business questions are being tackled. This fundamentally helps the client company on its journey to becoming an analytical competitor.
After this initial review we apply our data mining expertise to produce predictive models, using our statistical knowledge to select the most appropriate modeling tools and techniques for your specific needs. As with all of our engagements, our focus is to deliver tangible business performance improvements quickly, with benefits seen by everyone in the business, not just the data team.
Businesses who have good data management in place and who want to benefit more from it, for example exploiting their ‘single view of the customer
Enterprises looking to create more refined customer segmentation with product portfolios tailored to them
Organizations looking to improve business performance and decrease costs through greater control of the customer relationship
Companies looking to increase profitability by improved up-selling, cross selling and customer retention