Data democratisation: Liberate your data to unlock its true value
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Data democratisation: Liberate your data to unlock its true value
- 2. 19.03.2015 DATA DEMOCRATISATION: LIBERATE YOUR DATA TO UNLOCK ITS TRUE VALUE Webinars by AT Internet 2
- 3. DATA DEMOCRATISATION Nicole Pukala › Sales Manager, Central Europe Daria Vasilyeva › Digital Analytics Consultant, Moscow, Russia 3 ABOUT SPEAKERS
- 4. › How do we understand Data Democratisation at AT Internet? › What impact does the actual use of the data have on your business? › Examples: How can we help your business to manage a seemingly unbearable pool of information in a way that it can improve the online conversion of your business? 4 KEY QUESTIONS TO BE DEALT WITH TODAY
- 10. 10 › Avoiding data silos › Providing simple tools › Removing unnecessary restrictions › Teach people how to use data Delivering the right information to the right people at the same time DATA DEMOCRATISATION WHAT DOES IT MEAN?
- 11. 11 › Avoiding data silos › Providing simple tools › Removing unnecessary restrictions › Teach people how to use data Delivering the right information to the right people at the same time DATA DEMOCRATISATION WHAT DOES IT MEAN?
- 12. 12 › Avoiding data silos › Providing simple tools › Removing unnecessary restrictions › Teach people how to use data Delivering the right information to the right people at the same time DATA DEMOCRATISATION WHAT DOES IT MEAN?
- 13. 13 › Avoiding data silos › Providing simple tools › Removing unnecessary restrictions › Teach people how to use data Delivering the right information to the right people at the same time DATA DEMOCRATISATION WHAT DOES IT MEAN?
- 14. 14 › Reports designed by end users › Central repository for data analysis › User interaction › Scalable solution Delivering the right information to the right people at the same time DATA DEMOCRATISATION WHAT DOES IT MEAN?
- 15. 15 › Reports designed by end users › Central repository for data analysis › User interaction › Scalable solution Delivering the right information to the right people at the same time DATA DEMOCRATISATION WHAT DOES IT MEAN?
- 16. 16 › Reports designed by end users › Central repository for data analysis › User interaction › Scalable solution Delivering the right information to the right people at the same time DATA DEMOCRATISATION WHAT DOES IT MEAN?
- 17. 17 › Reports designed by end users › Central repository for data analysis › User interaction › Scalable solution Delivering the right information to the right people at the same time DATA DEMOCRATISATION WHAT DOES IT MEAN?
- 18. DATA DEMOCRATISATION SEGMENTATION AND API 18
- 19. DATA DEMOCRATISATION 19 THROUGH SEGMENTATION We need to ‘segment or die’ and stop trying to find the average audience but instead reaching all types of users. « » Avinash Kaushik, Web Analytics Evangelist AT Internet’s segmentation tool, available in DataExplorer module, provides online marketers/analysts not only with accurate, reliable data in real-time, but with data which can be exploited immediately. *DataExplorer is integrated as part of the Analyzer solution
- 20. 20 APPLICATION PROGRAMMING INTERFACE ’’ ’’ AND WHY IS IT USEFUL? WHAT IS AN API? Email Dashboard Excel CRM Ad Server API - architecture for sharing data between platforms and applications. Content that is created in one place can be dynamically reproduced and updated in multiple locations.
- 21. “The easy to use Data Query tool, means that your web analysts are completely autonomous in creating API URLs.” Bruno Guilbot Data and Behavioural Marketing Manager Solocal Group REST API DATA QUERY TO SET UP REST URL
- 22. SCM E-PROC ERP CRM EXTERNAL DATA ETL PROCESS EXTRACT – TRANSFORM - LOAD DATA WAREHOUSE Information is generated, stored and distributed Data Marts OLAP Cubes 22 Reports Tables Dashboards Scorecards Forecasts API API API API DATA SOURCE LAYER ETL LAYER DATA WAREHOUSE LAYER ANALYTICAL LAYER THE API DATA LAYERS
- 23. USE CASES 23
- 24. # GOALS • Increase user loyalty • Grow and develop audience & readership # RESULTS • Visitors return to the site and consume even more content • Visits from Google News grew +74% (in 4 months) EXAMPLE - MEDIA AND PUBLISHING ACTUAL USE OF DATA
- 25. AMAZON EMR PIG RUBY SCRIPTS COPY ETL Scripts ETL Scripts Staging Area Data Warehouse Data Exploration EXAMPLE - MULTIMEDIA CLIENT ACTUAL USE OF DATA
- 26. ABANDONED THE QUOTE. RETURNED ON THE WEBSITE. THANKS TO TMS THE RIGHT CONTENT IS ONLINE TRIGGER TO CMS TO PUBLISH A REMINDER CASEA ACESS THE HOMEPAGE FROM EXTERNAL CAMPAIGN CONTENT IS ADAPTED ACC. TO THE CAMPAIGN THE CAMPAIGN IS IDENTIFIED BY AXA CASEB IDENTIFY VISITOR ANALYSE BEHAVIOUR CHOOSE THE CONTENT CROSS INFO CRM DATA END TO END MODELLING AT AXA INVESTMENT BANKING ACTUAL USE OF DATA
- 27. ACTUAL USE OF DATA 27 TAG MANAGEMENT ACTIONS › Choose tag management system like Tag Commander › Insert tags › Create rules when tag has to be set › Standard WA tag shall be submitted for every page hit › Sales tracker tag shall just be called when a sales or subscription is done › Internal search shall just be submitted when a search is done › etc.
- 28. OBJECTIVES • Standardize the KPI’s and metrics for all internet businesses • Create a group-wide kpi dashboard, plus local dashboards to pilot digital activities in real time ACHIEVEMENTS • KPI and dashboards for HQ and for each business units delivered (more than 200 sites/apps) • Automated data collection for all dashboards via api ACTUAL USE OF DATA END TO END DASHBOARDS - CLASSIFIEDS
- 29. DATA WAREHOUSE CHIEF EDITOR SALES AND MAKETING MANAGEMENT ACTUAL USE OF DATA customised exports automation data culture DATA MANAGEMENT AT MEINE STADT
- 30. DATA WAREHOUSE CHIEF EDITOR SALES AND MAKETING MANAGEMENT ACTUAL USE OF DATA customised exports automation data culture DATA MANAGEMENT AT MEINE STADT
- 31. ACTUAL USE OF DATA 31 CONVERSION OPTIMISATION - BANKING OBJECTIVES Improve usability to increase conversion by combining MV testing with web analytics ACHIEVEMENTS • Conversion rates have improved in the majority of funnels • Every new revamp project relies on MV testing waves before being published online DATA DEMOCRATIZATION • WA & MV data in one system • All stakeholders get access to data
- 32. ACTUAL USE OF DATA JOHN SEES TV ADVERT JOHN VISITS THE ADVERTISER’S WEBSITE DRIVE-TO-WEB ANALYSIS TV ADVERT RECOGNITION TV TRACKING
- 33. ACTUAL USE OF DATA TV TRACKING DASHBOARD
- 34. TV TRACKING DASHBOARD ACTUAL USE OF DATA
- 35. DASHBOARDING 35
- 36. DASHBOARDING 36 › External cognition › Communication › Visualization of connectional content › Exploration › Enhancement of productivity GOALS Delivering the right information to the right people at the same time
- 37. DASHBOARDING › Too much data › No insights included › Colours are more important than insights › Show only one dimension and have no significance › Silly scale – no comparisons are possible (i.e.sparklines) › No clear message 37 BAD DASHBOARDS
- 39. DASHBOARDING Benchmark & segment Isolate your critical few metrics Don´t stop at metrics – include insights! • Insight • Recommendation for action • Business insights The power of a single page Churn and stay relevant – evolve constantly 39 5 RULES FOR A GOOD DASHBOARD
- 41. TABLEAU TOOLS FOR DATA VISUALISATION
- 42. QLICKVIEW TOOLS FOR DATA VISUALISATION
- 43. MANEYES TOOLS FOR DATA VISUALISATION
- 44. https://apps.atinternet-solutions.com/ AT INTERNET - DASHBOARD APP TOOLS FOR DATA VISUALISATION
- 45. WWW.ATINTERNET.COM Daria.Vasilyeva@atinternet.com Daria Vasilyeva – Digital Analytics Consultant
Editor's Notes
- Technically speaking, a data layer is a JavaScript object that contains all the contextual data of a page and the user behavior on that page (ex.1) or all the ecommerce transactional details (ex.2). Essentially, a data layer is the behind-the-scenes data and structure that drive customer interactions in web, mobile, and other digital channels. To ensure business value, accuracy, and consistency, data layers are often modeled and constructed through a collaboration between marketing and IT or web development professionals. But instead of data layers we have data silos what we’re going to talk about next.
- Silos & non-involvement lead to bad data quality Bad data quality leads to misalignment of analytics and business goals
- Regardless of the systems your company is using “behind the scenes” the end users should work with simple tools
- No restrictions in extracting data and connecting all the data together
- Historically speaking, AT Internet has almost 20 years’ experience in the field of Web Analytics. We have been able to progress from a standard tracking tool provider (XiTi) to a business-oriented decison-making tool provider, responding to the needs and challenges of the largest companies out there.
- An operational data store (or "ODS") is a database designed to integrate data from multiple sources for additional operations on the data. Unlike a master data store the data is not passed back to operational systems. It may be passed for further operations and to the data warehouse for reporting. A data mart is the access layer of the data warehouse environment that is used to get data out to the users. The data mart is a subset of the data warehouse that is usually oriented to a specific business line or team. Data marts are small slices of the data warehouse. Whereas data warehouses have an enterprise-wide depth, the information in data marts pertains to a single department. In some deployments, each department or business unit is considered the owner of its data mart including all the hardware, software and data.[1] This enables each department to use, manipulate and develop their data any way they see fit; without altering information inside other data marts or the data warehouse. In other deployments where conformed dimensions are used, this business unit ownership will not hold true for shared dimensions like customer, product, etc. https://apirest.atinternet-solutions.com/data/v2/getData? &columns={d_visit_id,d_visitor_num_id,d_page,d_referrer_url,m_visits,m_page_views} &sort={-m_visits}&segment=100015136&space={s:403729}&period={R:{D:'-1'}}&max-results=20
- Who is Elle ? Elle is one of the titles belonging to Groupe Lagardère: Groupe Lagardère is a media group present in around 30 countries. The group is structured around 4 distinct and complementary activities: publishing, distribution, press (paper and digital), and sports and entertainment. The media branch of Groupe Lagardère (who has overall revenues of €8 billion) Lagardère Active is a leader of French press (magazines), radio and TV: More than 200 magazines: Elle, Paris Match, Télé 7 jours, Le Journal du dimanche. 29 radio stations in France and Eastern Europe: Europe 1, Virgin Radio, RFM 10 TV channels: Gulli Lagardère’s key figures: 11,000 employees Present in 40 countries Sales turnover of €1.7 billion Lagardère Active is composed of: 35 websites, 50 apps for tablets, 100 apps for mobile 19 million unique visitors on the web (2014) 5.3 million unique visitors on mobile In France, it’s the second-largest media group in terms of Internet audience, and the first-largest in terms of mobile audience. SOLUTION Thanks to AT Internet’s API, data is distributed in real time into the journalists’ CMS, editorial dashboards, various reports, etc. Journalists can view the performance of each article in real time and over the previous 8 hours: - Number of visits Trends (increases, decreases, stability) Number of page loads Using these performance indicators, the journalists can identify which topics are interesting to visitors, and the formats that work the best. Example: Based on the article’s performance, the journalist might decide to produce another similar article on the same topic/theme, or not. AT Internet gave specific guidance to Elle.fr’s editorial teams, training them on the tools and relevant editorial actions. Tools: AT Internet + Search Metrics (SEO) + Visual Revenue (predictive analytics) Refining article titles Optimisation of the homepage in real time Selecting high-performing keywords to integrate into article drafting Selecting the optimal publication time Optimisation of article visibility on Google News Working on creating “Google-friendly” articles Regarding Google News, Lagardère’s teams were able to identify that certain time slots – that were less costly and less competitive – showed nonetheless very good traffic potential. They were also able to put into place a system to manage and drive content based on the time of publication and content profitability.
- Solution: adopt “data democratization” approach: Provide simple tools to end users disregarding of infrastructure built Teach users how to use those tools and data itself Remove unnecessary data access restrictions Provide teams (internal customers) with the tools that enable communication, not silos Its not about reports, its about KPI-thinking and business impact thinking. Not data representation but data interpretation! Develop a culture when conclusions based on data sound legit. The key is: they could have built this amazing infrastructure, spent a LOT of money and resources… and at the end receive no value out of it if they hadn’t adopted DD approach.
- Case A 1) THE VISITOR STARTED A QUOTE AFTER LANDING ON THE FORM AND ABANDONED. HE CAME ON AXA HOME PAGE TO GATHER FURTHER INFORMATION. 2) BUSINESS RULES ARE APPLIED TO PUSH A TAG CALLING THE CMS TO PUBLISH A REMINDER ON THE HOME PAGE TO FINISH HIS QUOTE. 3) THE TMS ASKS THE CMS TO DISPLAY THE RIGHT CONTENT TO ANNOUNCE THE POSSIBILITY TO COMPLETE THE QUOTATION PROCESS. Case B 1) THE VISITOR WAS EXPOSED TO AN EXTERNAL CAMPAIGN ON THE “AAA.COM” WEBSITE. HE DIRECTLY ACCESS THE AXA HOME PAGE AFTERWARDS. 2) THE DISPLAYED CAMPAIGN IS IDENTIFIED. ADAPTATION OF THE CHOSEN CONTENT. 3) ADAPTED WEBSITE CONTENT IS UPLOADED ACCORDING TO THE CAMPAIGN PREVIOUSLY DISPLAYED.
- A few words about TMS
- Dashboard at an international level with Naspers: Naspers is a leading multinational media group with its principal operations in internet platforms (focusing on commerce, communities, content, communication and games), pay-television and the provision of related technologies and print media (including publishing, distribution and printing of magazines, newspapers and books). The group’s most significant operations are located in emerging markets. This includes South Africa and the rest of sub-Saharan Africa, China, Latin America, Central and Eastern Europe, Russia and India. Naspers’s mission is to develop into the leading group of media and e-commerce platforms in emerging markets. The strategy is to provide entertainment, gaming, trading opportunities, information and access to friends and family wherever they are. Currently each company within Naspers group manages their own analytics using various tools. This presents challenges in terms of reliability and accuracy of data feed and hinders the creation of ‘standardised scorecard’ across the group companies In order to achieve this goal, Naspers requires a robust web analytics solution to measure the current online performance but also to provide recommendations for further improvement. Objectives: Naspers wanted to create a group-wide homogeneous platform with KPI and dashboards to measure the performance across the group companies, using the same measurement method. SOLUTION FOR AN INTERNATIONAL GROUP (to be explained verbally): Our capability to accompany an international client at Group level, and the local subsidiaries The primary objective of this project is to create a ‘group-wide assessment platform’ across all companies. In order to achieve this, AT Internet recommended a group-level KPI workshop to be conducted between Naspers central management team and AT Internet. The objectives of this service were: To identify the group-wide objectives To identify & agree on Key Performance Indicators & KPI metrics Based on the identified KPIs and KPI metrics, AT Internet will create a dashboard for the group. This dashboard will become a main platform for measuring the performance across the group companies and will be automated in order to remove unnecessary manual intervention and save time. The deliverables of this service were, KPI workshop KPI document KPI dashboard The tagging plan was established accordingly afterwards, and as soon as our solutions were deployed, a similar process was carried out to identify KPIs and build dashboards at a local level for business units
- Goal: Provide business data to over 200 “internal customers” at all levels of hierarchy, or partners such as: - Product managers producing regional and local content: data on content performance - - Internal classified ad teams: data on traffic volume - Classified ad partners for houses and flats: data on click remuneration - Marketing teams: advertising and SEO data - Sales and senior management Challenges: Project scale Lack of resources Specific requirements for each team => it was no longer possible to provide ad hoc reports to each team on a regular basis Solution: Instead, M.de chose to focus on providing the required data set and advise teams on how to use it. Data sets are to be provided automatically. Technical aspects and output All data is automatically imported every day into a data warehouse, processed and aggregated according to meinestadt’s business requirements: AT Internet Analyzer data Media reach data SEM data Partner revenue data The data is then consolidated and exported into Excel templates created specifically for each team by the web analytics and business intelligence unit Analysts teach end users how to use it
- As we can see, the lack of resources is quite a typical problem but it doesn’t have to be the key one. Looking back at meinestadt.de case, their key challenge was the lack of data-driven culture within the company. 200 internal users could only rely on the analysts. This understanding allows to apply non-standard approach – “quality instead of quantity”: instead of hiring more analysts, it’s better to invest into the end users. meinestadt.de solution: trainings on how to use the tools for all the teams in order to synchronize their daily work and let them learn from each other. Result: Analysts support, advise guide instead of providing data sets The teams have embracedand the data culture and now speak the same language Thanks to this alliance of teams and analyst group top management now trusts to analytics as a process and making further investments into it.
- Who is Groupe Caisse d'épargne : In 2006 Groupe Caisse d'épargne merged its investment bank IXIS Corporate and Investment Bank with Groupe Banque Populaire's Natexis, creating Natixis, a publicly traded investment bank in which Caisse d'épargne and Groupe Banque Populaire currently hold an equal stake of 35.25%.[1] Groupe Caisse d'épargne has also since merged its private wealth management bank La Compagnie 1818 into the Natixis group. The group is listed in the 2007 ICA Global 300 list of mutual and co-operatives, ranked 11th by 2005 turnover, making it the 2nd largest co-operative banking group in the world, after Crédit Agricole.[2] It was the fourth French bank and the twenty-fifth bank in the world by total assets in 2008.[3]
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- Benchmark & Segment Never show metrics just without context – always insert time scale and Benchmarks or goals to improve actionability. Isolte your critical few metrics You should have less than ten metrics on your dashboard. You will segment on them and insert goals for every of them. Don´t stop at metrics – include insights! That means you should not only have number in your dashboard but include recommendations for actions The power of a single page it is a report if it is more than one page Curn and stay relevant – evolve constantly Businesses change, people come and go, high-level priorities evolve, we become smarter Why should our dashboards and metrics on dashboards stay the same over the span of a year? Tip: We have 2 interesting blog posts about how to create good dashboards, we will send it with our follow up email that also includes the webinar
- Tableau: various data from various systems can be integrated via BI system in a visualization tool. Already worked with it, very intuitive and scalable from each to operate without having dealt with Coding and Design
- data from CRM ERP (Enterprise Resource Planning use existing resources more efficiently for business processes) Data warehouse or other databases share with each other On mobile devices Easy to use
- uploaded data is available to all registered users
- Visualization of very important requirements of our customers. AT Internet has developed a new Dashboard Builder, released in July 2014. Help clients to present their data clearly