BEGIN:VCALENDAR VERSION:2.0 PRODID:-//ChamberMaster//Event Calendar 2.0//EN METHOD:PUBLISH X-PUBLISHED-TTL:P3D REFRESH-INTERVAL:P3D CALSCALE:GREGORIAN BEGIN:VEVENT DTSTART:20181120T180000Z DTEND:20181120T191500Z X-MICROSOFT-CDO-ALLDAYEVENT:FALSE SUMMARY:Tech Mash Up: "Using Machine Learning to Predict Customer Behaviour" - November 20th\, 2018 DESCRIPTION:* This is a free event\, if you don't have an ICTAM login\, register above under the non-member form\, or email stownsend@ictam.ca for login information.\n\n\n\nThis Tech Mash Up is thanks to our GOLD sponsor\n\n\n\n \n\nUsing Machine Learning to Predict Customer Behaviour\n\nPresented by DecisionWorks Consulting Inc.\n\n\n\n\n\nDescription:\n\nA good business strives to meet their client's needs. The challenge in marketing to new clients is knowing exactly what those needs are and when they are required to be met. Think what the impact to your customer experience\, your marketing strategy\, and your bottom line would be if you could predict your client's next purchase and when that purchase is likely to happen.\n\n \n\nBy relying solely on their own historical data\, businesses can become masters of predicting customer behavior without relying on external data sources and external vendors to provide predictive business intelligence using more traditional demographic profiling. \n\n \n\nWorking with representatives from Applied Computer Science at the University of Winnipeg\, DecisionWorks has proven reusable solutions to take historical member purchasing patterns (big data)\, and\, using customized machine learning algorithms\, predict future purchases with a high degree of accuracy.\n\n \n\nThe innovative aspect of this work is that state-of-the-art techniques in recurrent neural networks (RNN) will be used to make high-accuracy predictions on financial data\, which is a new problem domain for these networks. The result will be greater differentiation for these financial services organizations\, improved customer service and higher returns for members and stakeholders. \n\n\n\n\n\nCo-Presenters:\n\n\n\nGrant Barkman\, BSc\, MBA President and Lead Facilitator\, DecisionWorks Consulting Inc.\n\nGrant Barkman is a seasoned business transformation consultant with a particular depth of experience in digital transformation\, process redesign\, organizational redesign\, change management\, consensus-based decision-making and strategy / IT alignment. Grant is confident in both the public and private sectors and virtually all major industries with a particular focus on finance\, healthcare\, insurance\, customer care\, manufacturing and supply chain. Always striving to learn and improve\, Grant has evolved DecisionWorks in becoming a leading innovator of predictive analytics and machine learning with the goal of providing the best business intelligence to support their client's strategic and operational decision-making. Grant is highly mobile and has a well-balanced blend of international experience including living and working in Canada\, the US\, the UK and Europe. All of his experience is complimented with enthusiasm\, the willingness to listen and learn\, and a desire to create and work in an atmosphere of mutual respect. \n\n\n\n\n\n\n\nDr Christopher Henry\, Phd\, P.Eng. University of Winnipeg\n\nDr. Christopher Henry is an associate professor in the Department of Applied Computer Science at The University of Winnipeg. He obtained his PhD from the University of Manitoba while studying in the Computational Intelligence Laboratory in the Department of Electrical and Computer Engineering. The majority of Dr. Henry's most recent industrial collaborations have focused on application of deep artificial neural networks. Industrial collaborations provide opportunities to deepen experience\, build expertise\, and provide a source of problems and datasets that will allow for comparison and contrast of my new methods with established approaches such as machine learning algorithms. This line of work has also provided opportunities to test hybrid approaches of machine learning and computational proximity.\n\n\n\n\n\nAbout DecisionWorks Consulting Inc.\n\nDecisionWorks Consulting started 12 years ago with one simple and central business value proposition: great decisions drive positive change. Our services are specifically designed to create a culture of consensus-based decision-making that can drive digital transformation\, cultural and organizational change programs. Our proprietary methodology uses graphical facilitation\, visualization\, consensus-based decision-making\, predictive analytics\, machine learning and organizational change management to diminish risk\, improve efficiency\, and reduce cost. www.decisionworks.ca. X-ALT-DESC;FMTTYPE=text/html:

* This is a free event\, if you don'\;t have an ICTAM login\, register above under the non-member form\, or email stownsend@ictam.ca for login information.
\n
\nThis Tech Mash Up is thanks to our GOLD sponsor
\n
\n \;

\n\n

Using Machine Learning to Predict Customer Behaviour
\nPresented by DecisionWorks Consulting Inc.
\n
\n
\nDescription:
\nA good business strives to meet their client&rsquo\;s needs. The challenge in marketing to new clients is knowing exactly what those needs are and when they are required to be met. Think what the impact to your customer experience\, your marketing strategy\, and your bottom line would be if you could predict your client&rsquo\;s next purchase and when that purchase is likely to happen.
\n \;
\nBy relying solely on their own historical data\, businesses can become masters of predicting customer behavior without relying on external data sources and external vendors to provide predictive business intelligence using more traditional demographic profiling.
\n \;
\nWorking with representatives from Applied Computer Science at the University of Winnipeg\, DecisionWorks has proven reusable solutions to take historical member purchasing patterns (big data)\, and\, using customized machine learning algorithms\, predict future purchases with a high degree of accuracy.
\n \;
\nThe innovative aspect of this work is that state-of-the-art techniques in recurrent neural networks (RNN) will be used to make high-accuracy predictions on financial data\, which is a new problem domain for these networks. The result will be greater differentiation for these financial services organizations\, improved customer service and higher returns for members and stakeholders.
\n
\n
\nCo-Presenters:
\n
\nGrant Barkman\, BSc\, MBA &ndash\; President and Lead Facilitator\, DecisionWorks Consulting Inc.
\nGrant Barkman is a seasoned business transformation consultant with a particular depth of experience in digital transformation\, process redesign\, organizational redesign\, change management\, consensus-based decision-making and strategy / IT alignment.  \;Grant is confident in both the public and private sectors and virtually all major industries with a particular focus on finance\, healthcare\, insurance\, customer care\, manufacturing and supply chain. \; Always striving to learn and improve\, Grant has evolved DecisionWorks in becoming a leading innovator of predictive analytics and machine learning with the goal of providing the best business intelligence to support their client&rsquo\;s strategic and operational decision-making. \; Grant is highly mobile and has a well-balanced blend of international experience including living and working in Canada\, the US\, the UK and Europe. \; All of his experience is complimented with enthusiasm\, the willingness to listen and learn\, and a desire to create and work in an atmosphere of mutual respect. \;
\n
\n
\n
\nDr Christopher Henry\, Phd\, P.Eng. &ndash\; University of Winnipeg
\nDr. Christopher Henry is an associate professor in the Department of Applied Computer Science at The University of Winnipeg. \; He obtained his PhD from the University of Manitoba while studying in the Computational Intelligence Laboratory in the Department of Electrical and Computer Engineering. \; The majority of Dr. Henry&rsquo\;s most recent industrial collaborations have focused on application of deep artificial neural networks. Industrial collaborations provide opportunities to deepen experience\, build expertise\, and provide a source of problems and datasets that will allow for comparison and contrast of my new methods with established approaches such as machine learning algorithms. This line of work has also provided opportunities to test hybrid approaches of machine learning and computational proximity.
\n
\n
\nAbout DecisionWorks Consulting Inc.
\nDecisionWorks Consulting started 12 years ago with one simple and central business value proposition: great decisions drive positive change. \; Our services are specifically designed to create a culture of consensus-based decision-making that can drive digital transformation\, cultural and organizational change programs. \; Our proprietary methodology uses graphical facilitation\, visualization\, consensus-based decision-making\, predictive analytics\, machine learning and organizational change management to diminish risk\, improve efficiency\, and reduce cost.  \;www.decisionworks.ca.
\n \;

\n LOCATION:435 Ellice Ave\, NRC Building UID:e.9429.1064 SEQUENCE:3 DTSTAMP:20260419T222059Z URL:https://members.techmanitoba.ca/events/details/tech-mash-up-using-machine-learning-to-predict-customer-behaviour-november-20th-2018-1064 END:VEVENT END:VCALENDAR