PREMIUM E-BOOK

Software Review: Data Analytics, Visualisation & Dashboarding Tools 

Insight teams and agencies need new tools

'Research' data now comes in many different formats: surveys, CRM, e-commerce, audience panels and more.

You need the right software to integrate, model and visualise all this information.

But survey data is unique

It's not like financial, sales or other types of enterprise data.

It's complicated.

Survey data is based on samples of a population. These usually have to be weighted to get a representative picture. And sometimes groups are boosted, which makes things even trickier.

There are gaps in survey data. Respondents don't answer all the questions. You have to deal with missing values.

And there are inconsistencies. The same survey conducted in multiple countries can have different periods of measurement and other nuances.

Make sure you pick the right software  

This review covers the leading Business Intelligence platforms used by marketing and CMI teams.

Buy it now and:

  • Get an objective comparison of the main platforms 
  • Find out which vendors are right for you
  • Avoid hours of time spent on your own research   
Software Review - E-Book - Insight Platforms

£359 | €395 | $449

ABOUT THIS E-BOOK

13 major platforms reviewed

Software Review - E-Book Pages - Insight Platforms

13 Business Intelligence and Survey Analytics platforms reviewed, including Power BI, Qlik, Looker, Tableau, Dapresy, Displayr, Infotools and more.

20 assessment criteria to help you compare and choose, including analysis features, integration, customer service and ease of use.

Individual assessments of software tools, with guidance on the best applications and optimal user types for each data platform.

Comprehensive and expert-led

Sjoerd Koornstra Headshot - Insight Platforms
House of Insights logo - Insight Platforms

Author: Sjoerd Koornstra

Sjoerd is a partner at The House of Insights, a consultancy he founded after leading global insight teams for Heineken.

Over his career, he has led the design and structuring of global CMI departments; built strategic partnerships with leading global intelligence providers; and implemented global CMI ICT systems for data and knowledge management.

He is particularly expert in data analytics, behavioural economics, and consumer research & insights.

MOA logo - Insight Platforms

Publisher: MOA

MOA is the Expertise Centre for Marketing Insights, Research & Analytics in The Netherlands.

Its core areas include training and development; insights management; data quality and security; and data privacy, compliance & ethics. The organisation hosts annual events including the MIE (Dutch Marketing & Insights Event) and the DAC (Digital Analytics Congress); and leads regular workshops, events and meetings including the MOAcademy and MOA Expertise Sessions.

ASSESSMENT CRITERIA

Interfaces/connectivity: Data sources that are supported, including Multidimensional Expressions (MDX), XML, RSS feeds, Hadoop, Microsoft SharePoint list, API's, flat file and other. Describe the ease of loading data sources. Are data loaders available for Nielsen (retail audit tracking data) or GFK (consumer panel data)? Describe the ease of loading survey data.

Governance: Platform administration capabilities enable the security and administration of users, scaling the platform, optimizing performance and ensuring high availability and disaster recovery.

Metadata: Tools for enabling users to leverage the same systems-of-record semantic model and metadata. It includes business-user data mashup including drag-and-drop, user-driven data, and combinations of different sources as well as the creation of analytic models, such as user-defined measures, sets, groups, and hierarchies.

Development: The set of programmatic and visual tools as well as a development workbench for building reports, dashboards, queries and analysis. SDKs, APIs, and support for open standards, including advanced analytics for creating and modifying analytical content, visualizations and applications, embedding them into a business process, and/or an application or portal.

Integrated Business Logic: Defining rules for harmonizing data, KPIs, related to availability, missing, weighting or different time basis.

Cloud BI: Platform-as-a-service and analytic-application-as-a-service capabilities for building, deploying and managing analytics and analytic applications in the cloud, based on data both in the cloud and on the premises.

Microsoft Office Integration: The ability to export data into Excel spreadsheets, while preserving existing formatting of the report or supporting Excel-based formulas. The ability to export reports to PowerPoint which are editable.

User experience and UI features: This refers to the product's ease of use and range of tools designed for user interaction with the data and product. Take account Ad hoc queries and guided analytics which enable users to ask their own questions of the data, without relying on others (IT, third parties) to create a report. Is there a universal single sign-on? Do you support voice instructions

Mobile: Developing and delivering content to mobile devices in a publishing/interactive mode using their native capabilities, such as touchscreen, camera and location awareness.

Collaboration: Enables users to share and discuss information, analysis, analytic content and decisions via discussion threads, chat, storytelling and annotations. It also includes different ways of alerting.

Reporting: Ability to create highly formatted, print-ready and interactive reports/graphs, with or without parameters. Dashboards are reports that depict performance measures graphically. It also includes navigation to functionalities like drill down, pivoting, sorting, global filtering and dynamic selections.

Structured and unstructured data discovery: The ability to integrate/link/relate information in structured databases with unstructured content. Does it support cleansing, parsing, extracting entities, context, terms and pattern matches from text including sentiment, emotion, opinion extraction, semantic processing and ontologies?

Predictive Analytics and Data Mining: The analytical methods which are supported like decision trees, regression, neural networks, support vector machines, genetic algorithms, and other supervised learning techniques. It includes also interfaces to other analytical software packages like SPSS etc.

Augmented data discovery: Automatically finds, visualizes and narrates important findings such as correlations, exceptions, clusters, links and predictions in data that are relevant to users without requiring them to build models or write algorithms. Users explore data via visualizations, natural-language-generated narration, search and natural language query (NLQ) technologies.

Interactive visual exploration: Enables the exploration of data via an array of visualization options that go beyond those of basic table, pie, bar and line charts to include heat and tree maps, geographic maps, scatter plots and other special-purpose visuals. These features enable users to analyze and manipulate data by interacting directly with a visual representation of it, to display it as percentages, bins and groups as well as exception reporting.

Custom Analytics: The ability for the business user to create custom KPIs, custom groups etc. without relying on others (IT, third parties).

Implementation Support: Describe what training, documentation, online communities, and help desk services (location, hours etc.) are available.

Consultancy: What kind of consultancy is available? Where are these consultants based? Do you have experience in the Consumer Insights/Market Research Industry?

Pricing/Licenses: Describe your pricing structures and license models.

Future Developments: What is your product roadmap for the future and which areas are you focusing on?

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