Uncovering the hidden wealth in your data for enhanced decision making.

Editor's Notes

• #3: Uncovering the hidden wealth in your data for enhanced decision making Gaining deeper insights with data analysis to inform your decision making processTools and techniques for data analysis – from simple to sophisticatedBest practice lessons from the private sector and international governments Dheeraj ChowdhuryGroup Leader – Digital Media, Business ServicesDepartment of Education & Communities, NSW
• #4: No one way to solve this challenge
• #5: No one way to solve this challenge
• #6: Before we start lets briefly look at:Why social mediaWhy social media metrics
• #7: Before we start lets briefly look at:Why social mediaWhy social media metrics
• #8: Before we start lets briefly look at:Why social mediaWhy social media metrics
• #9: We found three categories of benefits from the use of big data in public sector administration:1. Operational efficiency savings. We applied the percentage of potential operational cost savings to estimated addressable European OECD government expenditure (net of transfers).2. Reduction of cost of fraud and errors. We applied the percentage of potential fraud reduction to estimated addressable European OECD government transfer payments by multiplying the percentage of transfer payments. The estimated addressable transfer payment took into account the percentage of transfer payment that has a non-negligible amount of fraud and error and the estimated percentage of the cost of fraud and errors.3. Increase in tax revenue collection. We applied a percentage potential
• #10: No one way to solve this challenge
• #11: Before we start lets briefly look at:Why social mediaWhy social media metrics
• #12: Before we start lets briefly look at:Why social mediaWhy social media metrics
• #13: No one way to solve this challenge
• #14: Before we start lets briefly look at:Why social mediaWhy social media metrics
• #15: To put it perspective – multi channel, multi formatNo longer is the discussion - Are these going to stay?Is Facebook going to be around or is it going to be like MySpace?A show of hands who is using what
• #16: this is the opportunity
• #17: Demographic DataThis data types enables an effecient way to create context about consumers, yet broad survey-based research may not yield specific nuances and needs about specific individual taste as today’s consumers are given more choices and have more discrete needs. Some marketers are able to glean demographic data from social accounts gender, age range, by profile data, profile pictures, or searching public records like Zabasearch and Spokeo.Product DataA data type commonly used in ecommerce websites, this data type is used to match similar products with each other, in order to cross-sell and up-sell products. Often combined with demographic data, this data type, mixed with referral and behaviorial data yields greater accuracy. Visit any ecommerce website from Amazon, BestBuy and beyond to find examples of product matching.Psychographic DataAs the social web exploded in the past few years, consumers are volunteraily self-expressing their woes, pains, and aspirations in websites. This provides those who want to reach them increased opportunities to market based on lifestyle, painpoints, beyond just product sets. This data type is useful in both message and conversation creation as well as identifying features and products to improve or fix. To learn more about lifestyle and pain point positioning see the 5 stages of positioning by Lifestyle, Pain, Brand, Product, or Features.Behavioral DataThere’s at least two ways to find this data, it’s in both existing customer records like CRM or ecommerce systems or also in the “digital breadcrumbs” that users are leaving in social networks using a variety of web techniques from cookies, FB connect, and other social sign on technologies. The opportunity to suggest content, media, deals, and products to them that matches their previous behaviors will yield a greater conversion.Referral DataCustomers are emitting their recommendations for products, but positively –and negatively. Both explicitly through ratings and reviews, as well as implcity though gestures like the ‘like’ button to their social network. Vendors like Bazaarvoice (disclosure: client) offer a suite of tools for customer feedback and intelligene, Zuberance fosters positive WOM through positive ratings, and ExpoTV is a catalyst for conversation using video reviews, and see the well known case study from Levi’s who implemented the Facebook Like button.Location DataAs location based technology and services emerge for consumers to emit signals where they are using mobile devices, this data helps to triangulate context around location and time for brands to reach them. From Foursquare checkins and the associated contextual ads that emerge to ‘players’ to Facebook places, consumers can now emit their location, in exchange for contextual information, see how Awareness Hub (client) is able to surface influencers by location in Foursquare Perspectives.Intention DataThe most innacurate, this volatile data type holds great opportunity to predict what consumers will do in the future. Wish lists, social calanders like Facebook Events, Zvents, and aspirational websites like PlanCast, 43 Things allow consumers to broadcast their future plansSavvy marketers will harness explicit content and serve up the right messages in advance – as well as poach from competitors. Learn more about intention data –which is faster than real time.
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• #19: See this as an opportunity
• #20: Very easy to jump into measurement
• #21: Very easy to jump into measurement
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• #27: PeopleProcessTechnolgy
• #31: No one way to solve this challenge
• #39: Before we start lets briefly look at:Why social mediaWhy social media metrics
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