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Data Visualization Enterprise Landscape 2016

  1. Data Visualization Enterprise Landscape 2016 adoption use cases for agencies Image Source
  2. agenda • vendor landscape 1. Digital Marketing Oriented Platforms 2. Business and Analytics Applications 3. Specialized Software and White Glove Services 4. Agency Built Portals • takeaways
  3. digital marketing reporting platforms • ExamplesExamples
  4. digital marketing reporting platforms Characteristics Platforms built specifically for digital marketing data • Typically have API connectors directly to major platforms such as Doubleclick, Sizmek, Facebook Ads, Google Adwords, and other popular vendors that handles the ETL relatively seamlessly for general reporting (eg. just campaign outputs and not additional layers of modeling). • Often has pre-built Dimensions and Measures from its ETL process to be easily drag and dropped in building from a pre-defined HTML5 visuals • Visuals tend to look much more sleek than other platforms and usually are built with an HTML5 and Javascript engine • Likely have created their own visual libraries using raw Javascript to customize to their platform and data model • Tends to be a three-part platform, one that takes care of data storage, data clean-up, and visualizations/reporting • Landscape increasingly commoditized and cluttered but not near consolidation
  5. digital Marketing reporting platforms • Usually built in HTML5 with very attractive graphics and sleek interfaces • Some are able to automatically populate dimensions and measures from data, eg. dates and clicks without work from end user • Reports are close to pre-built for standard campaign reporting • Have social and collaboration functions • Most easy to use for rank-and-file • Good for repetitive builds of the same report • Visual and dashboard customization are lacking from a pure features perspective (eg. hard to do client branding or customizing visuals with additional data pivots) and not good for creating visuals that explore data • Handing over data security and storage to an outside company and won’t be “on prem” • Can be very costly • Can need a lot of time with managed service layer to customize before being useful Strengths Weaknesses
  6. datorama example
  7. analytics and business applications • ExamplesExamples
  8. analytics and business applications Characteristics Software, usually Desktop rather than Browser-based, for working with data and performing analytical tasks that aren’t specialized toward a particular industry • Typically are used across verticals and adapted for different purposes • Able to do both exploratory and explanatory data visualization, which the other platforms tend to not be able to do very well • Purposes are for more than data visualization, data visualization tends to only be one component or an important feature of the tool. • Typically are not explicitly designed for visualizations or for use as a reporting platform even though they are commonly used for those purposes • Have ability to do analysis or integrate mathematical models either natively or run external packages • Common features are statistical outputs, eg. ANOVA window with outputs, ability to do forecasting, correlations, regression, etc. • Able to run packages written in R, Python, and possibly other scripting languages
  9. analytics and business applications • Able to connect to a wide variety of databases natively with strong security features • Has a broad range of features for analytics, such as statistical modeling and able to do exploratory data analysis • Most customizations of individual visuals if not entire dashboards • Most flexible in terms of scope • Visuals can look more clunky and dated since their build usually isn’t browser-based • Not specialized for any industry • Can require more time to master. Features can be overkill for smaller agencies. • Likely does not have strong collaborative tools or capabilities out-of-the-box compared to other platforms • Can be time-consuming to use Strengths Weaknesses
  10. powerbi example
  11. white glove or specialized platforms • ExamplesExamples
  12. White glove and specialized software Characteristics Dashboards or visuals created for a very narrow purpose or scope (even more than the digital marketing-oriented platforms). Tend to look the most stylish and specialized • Have a narrow customer base and purpose, such as specializing in showing an output for one client • Reporting or visualization dashboards that only cover a few API connectors and data types, but do them really well, eg. displaying Tweets or Google Analytics outputs • Usually shown at roadshows or at events • Typically are less mature products • Used by smaller or specialized agencies and businesses • People love the way they look • Likely don’t have an ETL layer and plug directly into APIs and datasets • Tend to be a black box to some degree and not quite plug-and-play
  13. White glove or specialized platforms • Have the biggest wow factor and work well for external presentations • Highly specialized for a particular set datasets and handles transformation and pre-populates dimensions and measures, but not as broadly as digital marketing platforms • Does a few things extremely well and needs high-touch teams • Can often be black boxes in terms of workflow • Usually single-purpose • Products don’t have a very long history or even shelf-live necessarily • Can take long to provision and customize, making it unsuitable for any broad purpose • Lack of complex analytics Strengths Weaknesses
  14. Tickr example
  15. agency built portals Characteristics Dashboards or reporting portals built from scratch within agencies to meet business intelligence needs. Usually specialized to exactly what agency thinks is important • Has exactly what agency wants • Can be complementary to other agency products • Looks like nothing else on the market and matches to each agency’s needs and brandings • Usually built with a mix of open source libraries and tools • Sits on top of an agency data layer or connects to another data source • Agency has complete control over the data • Can sit on prem • Can often not be as stable or scalable as other platforms due to lack staffing, specialization, external support issues, and lack of prioritization and buy-in within organizations
  16. agency built portals Strengths • Tailored to each individual agency’s needs • Complete control of data, ETL, and visualization/reporting layer • Highest level of customization possible • Can fit well within other agency offerings as an integrated technology layer and experience Weaknesses • Software development capabilities are agencies can sometimes not be on par with capabilities at enterprise companies specialized only in deploying reporting platforms and visualizations • Often do not have enough internal support to necessarily scale or be maintained • Costly to the organization to built and manage
  17. takeaways • Splits in approach lie in business needs when deciding between standard campaign reporting tools, business applications, specialized white glove platforms, and in-house tools • Each approach has significant pros and cons depending on needs or the trade-offs an organization is willing to make • Strengths and weaknesses tend to go hand-in-hand, increased customization usually means less specification toward particular applications and increased workload by rank-and-file but less provisioning time to have a platform be actionable • Eg. Anything other than a supported API connection for many of the platforms would require custom work by a professional services group • A main trade-off exists between ease-of-use and out-of-the-box visual creation for using digital marketing platforms or white glove platforms versus the work and data ownership needed to implement business applications or in-house created agency tools
  18. thank you Image Source