1. Building a Big Data Analytics Roadmap Greg Doufas Director, Insight and Analytics

2. Why? Dont be part of the problem Hype Big Data = Big Money Nebulous concepts Business before Data Plan Proportion A Big-Data analytics strategy is essential in ensuring your approach is results oriented, transparent and PROPORTIONATE to the challenge you actually face. To get there, you must PLAN appropriately (and thoughtfully). A balanced and layered roadmap is the most powerful tool you will ever build. DO what you SAY 3. Start From the Top 1. Vision Who do you want to be? Whats the identity you are trying to create for your organizationyour teamyourself? Make it business oriented; find partners and allies We will lead the online retail sector as an innovator in the field of audience data acquisition, personalization and monetization. Analytics and data-based services will be a primary and driving factor in marketing, sales, product and business operations. 4. What are you going to do? 2. Business Objectives and Intentions What do you intend to accomplish? What capabilities are you building in order to realize your vision? It better derive value Target customer or visitors based on propensity to subscribe, churn, engage.. Recommend products and services to existing customers Optimize marketing channels and media spend Personalize and customize the user experience Develop performance indicators, business metrics (and leading indicators!) Shift to customer centric product development cycles Collect, harvest and manage new data sources (ie. Customer information) Introduce new revenue streams through the development of new data-based products and services Instill culture of fact based decision making 5. How are you going to do it? 3. Data Uses (Data Mining) What types analytics will be performed? This is also where people (talent) are factored These are skillsets that deliver the desired capabilities Target customer or visitors based on propensity to subscribe, churn, engage.. Recommend products and services to existing customers Optimize marketing channels and media spend Personalize and customize the user experience Develop performance indicators, business metrics (and leading indicators!) Shift to customer centric product development cycles Collect, harvest and manage new data sources (ie. Customer information) Introduce new revenue streams through the development of new data-based products and services Instill culture of fact based decision making Predictive Modeling and propensity analytics Collaborative filtering, basket analytics, probabilistic modeling etc. Mixed media measurement revenue mix modeling In-channel recommendation engines Reporting, multi-dimensional analysis, business analysis Customer and product profiling and usage analytics, segmentation Preference Centres, lifecycle analytics (CRM) 6. What data do you have/need? 4. Data Sources (data assets) What data sources do you already have? What do you need? Build an inventory (data and infrastructure) Element Description Volume Frequency Quality Source Website Data Raw web logs 100 Gb Daily 3 Omniture BW Billing Data Transactional 50 Gb Daily 5 Oracle DB First Party Data (partial) Instrumented logs (partial) 50 GB real time 4 Instrumented on device -- -- -- -- -- -- The Art of Data Mining: creating data from data Creativity, expertise and thought pays off a lot more than just data collection. Good data practitioners understand how to best leverage this data in order to address business objectives. Great data practitioners understand the power of creating new, derived data attributes from this data to gain even more robust customer or product attributes. 2 Start/Stop Billing Date data points can equate to 10 tenure attributes (variables) The development of data mining datasets is a powerful concept should drive us to consider our future state data palette Fosters customer centricity, efficiency, creativityvalue 7. Roadmap Data Sources Data Assets Data Uses Data Mining and Analysis Capabilities Business Objectives Intentions Value Big Data Infrastructure and Tools Technology serves our roadmap. Infrastructure and tools support and enable our capabilities they are not THE capabilities. 8. Technology: Things to Consider Be aware of your circumstances Understand infra and operational constraints (think about people, money, time) How much of the problem (and the solution) do you really own? Be proportionate How much do you really need? Investment in capabilities (talent) must be proportionate to investment in infrastructure and tools Tools What tools support your talent? (its not the other way around!) Think core competencies first, then tools Always refer back to the framework to keep yourself in-check 9. Technology: Choices Infrastructure Processing PIG . 10. Roadmap Find allies/partners. Layer the problem. Focus on the palette. Be proportionate 11. Thank You greg_doufas@hotmail.com