Over the years, we have developed the ability to manage the integration between Small and Big data, using the most modern machine learning algorithms and the most effective predictive and prescriptive models. At the same time, we have made the data-driven management tools perfectly accessible to the various business functions involved. There are several areas of application where we can provide our collaboration, focusing with particular attention on the deployment of results and the consequent return on investment.

CRM Analytics

The CRM analytics area includes all the data analysis activity on customers behaviors collected in the various interaction steps with the company. The aim is to facilitate and optimize a wide spectrum of business decisions.

This is high-level reporting for the visualization of the main performance evaluation metrics compared with the related pre-set company targets. The result is the delivery of a complete performance summary of the company results in key time intervals for the company (e.g. month, quarter, comparison with the previous period, etc.).

The design and structure of this type of dashboard meets the needs of use by the company's management board.

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Many companies "talk" about risk management, they create lists, define mitigation strategies and employ consultants to support them. However, a much smaller number of companies use the available data to quantify the risk (not only financial) and to support the decision-making process in a proactive and modern way.

Small and Big Data Analytics tools can be used to:

  • Quantify risks based on historical data, information from similar organizations or third-party data
  • Use historical risk pattern information to predict future risks
  • Build models to support investment decisions, which take into account costs and risk probability
  • Developing risk models in order to support managers when there are only few historical data available
  • Use behavioral models to study emerging patterns, identify anomalies and anticipate future risk modes

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Social Media Analytics

Target Research proposes the monitoring of different data and metrics aimed at analyzing what is happening online in relation to your brand. Furthermore, it is not taking its cue exclusively from the world of social networks, such as Twitter, Instagram and Facebook, but proposing an integrated analysis system of all on-line media, such as news sites, blogs or forums.

Through this analysis system we can obtain:

  • a wider view of the brand's online presence; indeed, to monitor the performance of a single channel, the proprietary analytics tools of the channel are enough (Twitter Analytics, Facebook Insights ...), but if the client wants to have the complete and integrated picture of his performance he needs to have a social platform media analytics with an adequate analysis system;
  • monitoring the competitors' activities that allows to compare the performances of the different channels, the results of the campaigns and the market benchmarks; it is worth to notice that this type of activity cannot be managed simply through the use of proprietary analytics of the channels, which do not provide an overall view, but only specifical in relation to the single channel;
  • useful insights to understand how the brand is perceived not only on social networks but also on blogs, forums and online news websites, allowing to add relevant information with respect to traditional media monitoring focused on the press and television;
  • an idea of how the logo was used online thanks to the most advanced image recognition systems (image analytics): almost 80% of the images posted by users on the network contain an image in addition to the text: the fact of being able to recognize not only textual but also visual mentions are essential to obtain a complete picture of the potential visibility of the brand

In brief, through this approach we can monitor and analyze the reputation of the online brand, analyze and optimize the performance of online marketing activities, search for trends in order to integrate the market research and identify the different touch points during the customer journey.

IOT Analytics

In the industrial sphere, the latest developments in the field of big data and the Internet of Things are redefining the boundaries of what can be achieved with data generated by connected machines and devices.

The so-called Industrial Internet of Things (I-IoT), by making information available on connected equipment, makes it possible to prevent adverse events such as malfunctions, breakages or performance drops, while improving the flow of quality control and optimizing the production performances; at the same time, it allows the use of the same information to develop new products / services and generate additional and / or unconventional revenues.

Target Research, in this context, is able to develop advanced analysis systems, based on ad hoc machine learning algorithms and integrated with existing business systems; in detail, we provide solutions, services and support for:

  • Predictive Maintenance
  • Sensor/Feature Analytics
  • Top-N Failure Analytics

Our services for the IOT are aimed to:

  • provide predictive, and not just «final», indications on the status of products and machinery, thus anticipating the most critical phenomena such as breakages, downtime, accidents, etc.;
  • accelerate reaction times against drifts in the production process or events of any kind thanks to real-time or near-real-time analysis.
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