Collaboratively developing the big data roadmap amongst key divisions
•
1 like•1,134 views
Understanding the types of data available for profitable business application Clarifying and analysing data to power the data project Involving key stakeholders to educate and determine expectations
Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Viewers also liked
Viewers also liked (17)
Similar to Collaboratively developing the big data roadmap amongst key divisions
Similar to Collaboratively developing the big data roadmap amongst key divisions (20)
Recently uploaded
Recently uploaded (20)
Collaboratively developing the big data roadmap amongst key divisions
- 1. ! Collaboratively developing the big data roadmap amongst key divisions! Digital Marketing Dialog! January 25th, London! ! !Luisella Giani! ! @luisella! #DM_Dialogue!
- 2. Worlwide most popular colour for cars is WHITE. #DM_Dialogue!@luisella! 2015. What colour 35% of buyers prefer? 11%! 25%! NORTH! AMERICA! 27%! 25%! SOUTH! AMERICA! EMEA! 19%! 34%! APAC!
- 3. Why should you care about Big Data & data science ?!
- 4. STORYTELLING doesn’t mean telling stories. Content shared must be true and autenthic TRUST SHARE PEER REVIEW COM PARE PURCHASE DECIDE EVANGELIZE RESEARCH SHARE DISCOVER SEARCH RESEARCH TRUST AWARENESS CONSIDERATION PURCHASE BUYER INFLUENCER Digital Peers Email Events Social Media Web/Mobile Company web/ mobile sites Sales PREFERENCE LOYALTY ACTION AWARENESS CONSIDERATION Decentralised, mobile centric, micromoments driven Customer Experience! INBOUND Want to know Want to buy Want to do Want to go #DM_Dialogue!@luisella!
- 5. To understand my customers well enough to: PR! ! GAIN MORE VISIBILITY! PRODUCT! ! DESIGN A BETTER PRODUCT FOR THEM! MARKETING! ! BETTER TARGETING, CHANNELS PRIORITIZATION! ADVERTISEMENT! ! OPTIMISE THE MEDIA INVESTMENT! CUSTOMER SUPPORT! ! OFFER THEM A BETTER SUPPORT! SALES! ! MAKE THEM AN OFFER THEY CAN’T REFUSE ( PRICING&PRODUCTS)! #DM_Dialogue!@luisella!
- 6. Data-driven product decisions! “Netflix was the only network that said “We believe in you. We’ve run our data, and it tells us that our audience would watch this series. We don’t need you to do a pilot” ” ! ! Kevin Spacey, actor and producer producer ! #DM_Dialogue!@luisella!
- 8. #DM_Dialogue!@luisella! ! Common cold and other upper respiratory tract infections! ! Last 28days! ! www.patient.co.uk/local-map!
- 9. Infographics are now a standard content marketing toolkit. Win on data visualizations driven by ORIGINAL data. You have access to more data than even before.Use it for top-notch marketing, don’t tuse it only for internal decision making, don’t treat your data like a state secret.! Data visualization for content marketing! #DM_Dialogue!@luisella!
- 10. Perfect targeting ! leading to privacy invasion and negative image?! My daughter got this in the mail!” he said. “She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?”! The manager apologized and then called a few days later to apologize again.! “I had a talk with my daughter. She’s due in August. I owe you an apology.”! #DM_Dialogue!@luisella!
- 11. Hyper personalization! My Starbucks Rewards Program, +28 percent YoY! 10.4 million members in the US alone Q3 2015 #DM_Dialogue!@luisella!
- 12. Big Data is the amount of data that doesn’t fit on your machine. ! #DM_Dialogue!@luisella! “ “
- 13. There are several use cases in different sectors like Retail, Healthcare, E-Commerce.! 73%! of companies Invested or Plan to Invest in Big Data in the Next Two Years - Gartner Survey! Big Data and data science ! aren’t only for Facebook and Google. ! eCOMMERCE RETAILNEWS HEALTHCARE LOYALTYBANKING #DM_Dialogue!@luisella!
- 14. #DM_Dialogue!@luisella! Big Data: Volume! Exabyte! until 2007 it was just a theoretical concept. Currently data, information and knowledge are created and collected at a rate rapidly approaching the exabyte/year range. ! Library of Congress: estimated to hold 10 terabytes of data in all printed material. Audio, video and digital materials estimated between 3 and 20 petabytes.!
- 15. #DM_Dialogue!@luisella! BIG DATA: range volume of exabytes, exceeding the capacity of current online storage systems and processing systems. ! STORAGE and DATA TRANSPORT are technology issues, solvable in the near-term, but represent longterm challenges. ! Big Data handle the exponential growth of MACHINE-GENERATED DATA: humans aren’t fast enough to outpace an old relational database.! Big Data: Volume&Velocity!
- 16. #DM_Dialogue!@luisella! of world’s data is still unstructured.! Volume! Variety! Velocity! Complexity! Value! Big Data: Variety! 80%! COLOR SOFTWARE BUSINESS INTELLIGENCEWEBSITESERP PICTURES, VIDEO eCOMMERCECAMPAIGNS SOCIALMEDIA CUSTOMER SUPPORT CRM It can’t easily be put into relational databases, ! e.g. pictures, video, social media updates. !
- 17. Big Data tools and frameworks - Hadoop, Spark- are needed to leverage the power of analytics on large scale.! 42! #DM_Dialogue!@luisella! The Hadoop’s guide to the Galaxy! BUT HADOOP IS NOT
- 18. #DM_Dialogue!@luisella! Not Big Data if…! Generated through HUMAN DATA ENTRY. ! OPERATIONAL DATABASE. CRM is never Big Data, and ERP is never Big Data.! Fit just fine in a MYSQL DATABASE. Even if a lot of RAM is in it, it’s still not Big Data.!
- 19. #DM_Dialogue!@luisella! Big Data meets Thick Data…!
- 20. #DM_Dialogue!@luisella! BIG DATA Technologies for storing and retrieving data characterized by Velocity, Volume, Variety (Gartner’s 3Vs) plus Value and Complexity.! Big, Small, Thick, Smart Data…! SMALL DATA THICK DATA SMART DATA Doesn’t require machine learning. Good tracking systems and segmentation of your data can produce huge results. ! Ethnography. Aim to understand intentions, emotions, feelings that underpin the customer experience. ! (Tricia Wang)! Analytics. Bigger isn’t always better. Aim to filter out the noise and hold the valuable data, to solve effectively business problems. (Veracity, Value).!
- 21. #DM_Dialogue!@luisella! and Thin, Long, Little Data…! THIN DATA LONG DATA LITTLE DATA Big Data without Ethnography. Limited to a context but only quantitative. E.g. iBeacons data streams, proximity- based but not providing marketing insights.! Data with historical context. Big Data looks at a timeframe of 5 years or less across different channels. Long term view (10, 20, 30 years) to better connect with customers and understand long term trends.! Personal quantified data. Provided by portable devices (Jawbone, Fitbit). Little Data is controlled by individuals. Companies grant permission for individuals to access Big Data, while individuals grant permission to organizations to access Little Data. !
- 22. #DM_Dialogue!@luisella! Making sense of Data! 1! Don’t forget Small Data while focusing on Big Data and new technologies. Many companies are not getting yet full advantage of matching data contained in relational databases to solve business problems. 2! Don’t forget that your consumers are Humans. Aim to understand the why and how: their intentions, emotions, feelings in the context (Thick Data).! 3! Making Data Actionable (Smart Data) means also building a good framework for getting insights applicable to daily business decisions. !
- 23. ! Company level! Order (cans) ! Delivery (cans)! Stock (volume)! Ingredient_cd! Layaway! ! Company level! Color info! Ingr. Volume! Timing info! Correctness! Measurements! Painter! Layaway! Company level! Color info! Formulation! Measurements! SETTINGS! STOCK! JOB! PRICE! JOBCARD! PERS. FORM! What is relevant?! Data from Color Retrieval software! #DM_Dialogue!@luisella!
- 24. 6.5 million visit/month! Each visit clicks, time spent on site, pages visit etc ! 3MB average visit data size ! 702 terabytes monthly WEBSITES 8 terabytes data/day processed! 500 million tweets/day ! 60 characters average tweet! 30GB of text content/day analysed. ! 0.5% of 8 terabytes. ! ! TWITTER ONLY A SMALL FRACTION OF DATA IS USEFUL FOR GENERATING ANY NON-TRIVIAL INSIGHT. ! #DM_Dialogue!@luisella!
- 25. Framing the right question! “ ”A. Einstein! If I had an hour to solve a problem I'd spend 55 minutes thinking about the problem and 5 minutes thinking about solutions.! #DM_Dialogue!@luisella!
- 26. #DM_Dialogue!@luisella! THE DREAMER ! THE REALIST! THE CRITIC! THE HELPER! The Disney brainstorming method!
- 27. #DM_Dialogue!@luisella! OPTIMISE SALES ROUTE,PREDICTIVE ANALYSIS! “ Give me the customers in EMEA who spent ! +200K/month (all sales channels: ecommerce, callcenter, sales account) who were visited at least once by a sales account! during the latest 3 months ”. ! OPTIMISE FUNNEL CONVERSION -MARKETING! “Give me the volume spent on eCommerce of the top costumers having the highest adoption rate for new products during the last 3years in Germany and France”. ! CUSTOMER SEGMENTATION, PREDICTIVE SUPPORT! “Give me the complains rate about the new product sold in the last year against the rate of formula adoption (customer ordered exactly the formula indicated by the color tool). ! Prioritize key questions for each team!
- 28. STORYTELLING or COTENT MARKETING doesn’t mean telling stories. Content shared must be true and autethic From Calcutta to Fontainebleau forest! SUPPORT! TRUST! SELF DISCIPLINE! Don’t change people, change the smell of the place. (Prof. Sumatra Goshal)! CONTROL COMPLIANCE CONTRACT CONSTRAIN AMBITIONS, VALUES! CONTINUOUS LEARNING ! REWARD INNOVATIVE APPROACH! FOCUS ON CREATING VALUE FOR&WITH COSTUMERS! SERVANT LEADERSHIP! CONTINUOUS IMPROVEMENT! #DM_Dialogue!@luisella!
- 29. Data analysis skills not confined to Digital team Define future skills requirements Undertake skills gap asessment! Bridge the GAP Keep up to speed: evaluate and evolve! Learning culture: ! Everyone become a student again! #DM_Dialogue!@luisella!
- 30. INTEGRITY! accuracy! consistency! honesty! INTERESTINGNESS! relevant! meaningful! new! What makes a good data visualization?! #DM_Dialogue!@luisella! USEFULNESS! useable! fitting! efficient! BEAUTY! structure! appearance! harmony! INFORMATION! The art of journalism! Structuring and harmonizing information! VISUALIZATION! The art of design! Structuring and harmonizing visuals!
- 31. A fraction of data can generate non-trivial insights! Prioritize key questions for each team!2! Build harmonized KPI’s framework across channels! Dashboard: underderstandable&visually attractive! 4! Extend data analysis skills beyond Digital team! 5! 3! Lessons learnt! #DM_Dialogue!@luisella!