- ACCOUNTING AND FINANCE
- RESEARCH AND DEVELOPMENT
Measurement of the number of impressions on websites and social media is readily accessible via most online platforms today. However, unifying this into a single view across all online channels, where measurement of the return on investment per campaign and against a range of online engagement, conversion and cost-effectiveness targets is out of the reach of most Marketing departments.
Many organisations need to meet statutory requirements of handling cases within a particular timeframe and quality framework. Communicating this to regulatory bodies and external stakeholders is often a difficult task, involving complicated manual compilation of data across multiple systems. Automation of data processing allows organisations to better manage cases on a near-real time basis, and provide on-demand visibility to stakeholders easing the internal administrative burden of compliance.
To truly understand the success of a business requires a view of their share of a market. This introduces the need to quantify the market potential by geographic area using market demographics and existing customer and sales data. This helps businesses prioritise their field sales activity, direct marketing initiatives and investment in extending a branch network.
Proactive management of health is proven to be more cost effective than treatment after the fact. In the Sports Sector, predicting and intercepting an injury is critical to ensuring an athlete meets their performance objectives and has the best chance of successfully competing. Machine Learning allows organisations to identify patterns in the drivers of injury drawing on a range of performance and wellness factors, allowing near sighted intervention and medium term planning of a training regime.
Accurately predicting sales volumes every month helps to better manage cash flow and capacity planning to make sure that a business can keep up with customer demand. Consolidating these forecasts from a large workforce is a key challenge that prevents most businesses from providing a regularly updated view. Leveraging machine learning also provides the opportunity to detect patterns that more objectively estimate sales revenue by taking into account seasonality, environmental and market factors and location.
Management and Board Reporting is a regular rhythm of most businesses which often requires weeks of preparation each month. Stakeholders now demand information that is easier to consume than traditional static reports, such as mobile device capabilities, concise consolidated executive dashboards, and drill through capability, available on an on-demand basis through a central portal.
Customer touchpoints are commonly spread across multiple, disparate systems throughout the entire sales cycle. To gain a 360 degree, single view of a customer is either impossible or requires extensive manual intervention. Implementing a Single Customer View Solution can provide the necessary foundation for marketers to exploit up-sell and cross-sell opportunities, and optimise their channel investments.
Using insight from customer buying behaviour to drive instore and online communications can significantly uplift conversions and cross-sales. Using the Cortana Intelligence Suite, businesses can decipher instore movement and customer reactions, and use Machine Learning models to tailor real-time offers and recommendations that are relevant to a customer's specific needs.
Detecting a customer at risk of leaving is a time-critical activity that often requires drawing on indicators of a customer's satisfaction level that are not formally captured in systems. Modern data processing techniques allow businesses in real-time to detect the mood of a customer by the tone of their voice or their correspondence, rate the risk of customer churn and produce timely alerts to operational staff.
Effective scheduling of timetables, staff and resources can be a complex and effort demanding task. Businesses seek not only a consolidated view of availability but real-time feedback and alerts of job status and staff location to optimise the allocation of jobs across their workforce.
For many businesses, staff salaries represent one of the largest operational costs yet managers do not have a single view of Finance and HR data to gain meaningful insight into staff performance and utilisation. Quickly highlighting areas of concern and correlating drivers of long term success can help to drive the right investments in staff.
Companies often struggle with several aspects of the pricing process, including accurately forecasting the financial impact of potential tactics, taking reasonable consideration of core business constraints, and fairly validating the executed pricing decisions. Expanding product offerings add further computational requirements to make real-time pricing decisions, compounding the difficulty of this already overwhelming task.
This solution addresses the challenges raised above by utilizing historical transaction data to train a demand forecasting model. Pricing of products in a competing group is also incorporated to predict cross-product impacts such as cannibalization.
In today's highly competitive and connected environment, modern businesses can no longer survive with generic, static online content. Furthermore, marketing strategies using traditional tools are often expensive, hard to implement, and do not produce the desired return on investment. These systems often fail to take full advantage of the data collected to create a more personalized experience for the user. Surfacing offers that are customized for the user has become essential to building customer loyalty and remaining profitable.
Today's digital marketing teams can build this intelligence using the data generated from all types of user interactions. The Cortana Intelligence Suite provides advanced analytics tools through Microsoft Azure - data ingestion, data storage, data processing and advanced analytics components - all of the essential elements for building a personalized offer solution.
Quality assurance systems allow businesses to prevent defects throughout their processes of delivering goods or services to customers. Building such a system that collects data and identifies potential problems along a pipeline can provide enormous advantages. For example, in digital manufacturing, quality assurance across the assembly line is imperative. Identifying slowdowns and potential failures before they occur rather than after they are detected can help companies reduce costs for scrap and rework while improving productivity.
This solution shows how to predict failures using the example of manufacturing pipelines (assembly lines). Early prediction of future failures allows for less expensive repairs or even discarding, which are usually more cost efficient than going through recall and warranty cost.
Microsoft Customer Example: