stacker + analytics   193

Dimensions of Museum Data – Whitney Digital – Medium
With these three dimensions in place it becomes possible to build segments or reports based only on a single exhibition, but review data from everything they did across the site during that session, from watching videos to diving into the collection after reading about a show to purchasing tickets. It also becomes possible to build reports for all exhibitions, but limit it to a specific phase (e.g., pre-opening), or an exact range of days (e.g., the week before opening). All of that data was possible to gather before, but by building the attribution into the Google Analytics structure it becomes far less labor intensive.
Whitney_Museum_of_American_Art  exhibition  google_analytics  analytics  metrics 
november 2018 by stacker
Visitor Motivation Survey and Audience Segmentation for the Whitney Museum of Art Website
This post is a summary of the pilot research project at Pratt Institute undertaken by Sydney Stewart and Samantha Nullman. This research was conducted as part of the INFO 685 course: Digital Analytics: Web, Mobile and Social Media in collaboration with the Digital Media department at the Whitney Museum.
Whitney_Museum_of_American_Art  audience_research  analytics  metrics 
november 2018 by stacker
Ford's Theatre Blog · Ford's Theatre
Over the last three years, I’ve learned that digital tools allow us to collect and analyze certain kinds of quantitative data on our own. For example, our department now actually collects and analyzes user data from our website and social media platforms. We pull more detailed data from our new customer relationship management (CRM) platform in a way that lets us target audiences, analyze online resource usage and test communications with our teacher audiences. It has truly transformed our relationship with our marketing and communications department and made us data-driven in ways I would never have imagined possible.
analytics  Ford's_Theatre  Tessitura 
november 2018 by stacker
The art of analytics: using bigger data to create value in the arts and cultural sector | Nesta
It is still early days in the adoption of data-driven innovation in the arts and cultural sector, but the examples discussed above suggest that it has great potential. If arts and cultural organisations are going to fulfil this potential, they will need to access new data skills, develop an analytical culture, adapt their processes and think innovatively about how to measure the value that they generate. They will also need to learn how to address data pitfalls and biases, and maintain a critical attitude.
nesta  metrics  analytics 
august 2018 by stacker
gtm-ecommerce-platforms/shopify.md at master · toddheslin/gtm-ecommerce-platforms
Shopify has three primary ways of collecting analytics data.

The Shopify built-in analytics tracking (limited to higher plans)
Adding the Google Analytics universal tag and Facebook Pixel into Online Store/Preferences setting
Injecting tracking code or a tag manager into the theme.liquid file (e.g Google Tag Manager)
You can also add 'Additional content and scripts' in the Settings/Checkout page, however this will only fire on the final confirmation page after a payment has been processed. It's also worth noting that all analytics enabled in (1) and (2) above will also fire on the confirmation page but you will also need to add GTM from option (3) if you want it to also fire on this page.
shopify  analytics  metrics 
july 2018 by stacker
What’s the most important metric for online science communicators?
Sometimes it feels like the key outcome of our social media activity is to generate statistics that feed impressive-looking monthly reports. It’s easy to lose sight of the fact that those reports should reflect the actual goals of activity, not be an end-point themselves. My advice for most people trying to make sense of their social media analytics: for the next couple of months, dramatically simplify what you’re looking at.
social_media  metrics  analytics 
july 2018 by stacker
Culture KPIs | Transformation – digital and beyond
Like most organisations we have KPIs and other performance data that we need to collect every year in order to meet funding requirements e.g. the ACE NPO Annual Return. We also collect lots of performance data which goes beyond this, but we don’t necessarily have a joined up picture of how each team is performing and how we are performing as a whole service.

Why KPIs?

The first thing to say is that they’re not a cynical tool to catch out teams for poor performance. The operative word in KPI is ‘indicator’; the data should be a litmus test of overall performance. The second thing is that KPIs should not be viewed in a vacuum. They make sense only in a given context; typically comparing KPIs month by month, quarter by quarter, etc. to track growth or to look for patterns over time such as busy periods.

A great resource we’ve been using for a few years is the Service Manual produced by the Government Digital Service (GDS) https://www.gov.uk/service-manual. They provide really focused advice on performance data. Under the heading ‘what to measure’, the service manual specifies four mandatory metrics to understand how a service is performing:

cost per transaction– how much it costs … each time someone completes the task your service provides
user satisfaction– what percentage of users are satisfied with their experience of using your service
completion rate– what percentage of transactions users successfully complete
digital take-up– what percentage of users choose … digital services to complete their task
Bristol_Museums_Service  kpis  metrics  analytics  dashboard  google_analytics 
may 2018 by stacker
Exploring the Relationship between Visitor Motivation and Engagement in Online Museum Audiences | museumsandtheweb.com
In this paper, the authors will describe the rationale, methodology, and results of a series of studies that have been conducted with visitors to the Indianapolis Museum of Art website. The objective of the studies is to better understand people’s motivation for visiting the site and whether this motivation has an impact on the way they engage online. The hope is that these results will provide a reference dataset, and a replicable model for other museums that are interested in better understanding their online audience and in conducting similar studies for their own web efforts.
mw2012  metrics  analytics  audience_research  ima 
april 2018 by stacker
Levelling Up: Towards Best Practice in Evaluating Museum Games | museumsandtheweb.com
Museums make games because games can provide compelling educational engagement with museum themes and content, and the market for games is enormous. Truly understanding whether games are achieving your goals requires evaluation. In this paper, we identify the kind of games that museums make and use case studies of our own casual games to look at the benefits and means of evaluation. Beginning by identifying different kinds of evaluation within the broad framework of formative and summative practices, we suggest ways to plan an evaluation strategy and set objectives for your game. We then look in detail at evaluation methods: paper and wireframe testing, play-testing, soft launching, Google Analytics, surveys, and analysing responses “in the wild.” While we draw on our own experience for examples of best practice, we recognize that this is an area in which everyone has a lot to learn, and we conclude by suggesting some tactics for sharing knowledge across the museums’ sector.
mw2012  games  evaluation  metrics  analytics  audience_research 
april 2018 by stacker
Resources | Dexibit
Whitepaper: data driven insight in the cultural institution
This whitepaper explores the business drivers and return on investment for analytics and outlines a leadership approach to people, process and technology with options analysis and implementation best practices.
resources  analytics  metrics 
april 2018 by stacker
Creating Access beyond metmuseum.org: The Met Collection on Wikipedia
The Met’s adoption of an Open Access licensing policy for images and data received attention from a number of international media outlets, which generated a significant increase in user activity in the online collection on metmuseum.org. In the weeks following launch, we experienced a 21% increase in sessions (fig. 1), a 38% increase in pageviews (fig. 2), and an incredible 260% increase in image downloads (fig. 3).
Metropolitan_Museum_of_Art  collection  open_access  commons  Wikipedia  analytics 
february 2018 by stacker
Digital analytics – in conversation with Chris Unitt | Victoria and Albert Museum
The data layer is different. You can think of it as a little store of data containing extra information about a web page (amongst other things). This is useful because, by default, Google Analytics only collects the page title and URL for each page a person visits.
google_analytics  metrics  analytics  V&A  google_tag_manager 
february 2018 by stacker
Blog del Museu Nacional d'Art de Catalunya » Analysis of the digital experience in the museum
The next step is the definition of a data strategy.  This document should include what the goals are in terms of collecting and using data.  For example, the results of the data analysis can be used for:

getting to know the users
creating segments
personalizing the experience
optimizing our digital offer
increasing the revenues
measuring the results of distinct marketing campaigns
showing the impact of our activities
informing about the strategy
This document should be accompanied by an implementation plan of the digital analytics where the specific tasks to be carried out, are defined along with a timing.
analytics  metrics  Elena_Villaespesa 
october 2017 by stacker
Do people want access to digitised collections? - Open Objects
Someone asked me recently if there’s any evidence that people really want access to digitised collections, so I popped onto twitter and asked, ‘Does anyone have a good example of a digitised image on Wikimedia or similar that reached a huge audience compared to the GLAM’s own site?’. Here are the responses I received:
wikimedia  Wikipedia  analytics  metrics 
october 2017 by stacker
BaGLAMa 2
BaGLAMa shows you page view numbers for pages on Wikipedia (and other Wikimedia sites) containing Commons files in a specific category. Since February 2014, a new software is used to aggregate page views, so there may be minute differences.
Wikipedia  metrics  analytics  wikimedia  glam 
october 2017 by stacker
The E-Commerce Benchmark KPI Study 2017: 15 Essential Takeaways - Moz
E-commerce websites averaged 1.6% overall. Travel came in at 2.4%. Online-only retailers saw 1.8% conversion rates, while their multichannel counterparts averaged 1.2%
ecommerce  kpis  metrics  benchmarks  analytics  2017 
september 2017 by stacker
Observations and advice on analytics at the Getty | July 19, 2017 - Google Slides
We don’t set objectives often enough so it’s hard or impossible to measure success
Goals = broad outcomes; Objectives = measurable steps
Don’t begin with “What does the audience want?”
Do begin with “What do we want to achieve with this project?”
Many silos of responsibility
Collaboration across programs has challenges (but the audience just wants its content)
presentation  Getty  analytics  kpis  metrics 
august 2017 by stacker
@GettyHub Objectives + KPIs (July 2017) - Google Docs
The purpose of the social media pilot is to determine whether audience-first, cross-Program social media is currently viable at the Getty.

The goal of the @GettyHub Twitter account is to provide an interdisciplinary social media destination representing all Getty programs that meet the needs of scholars and professionals for trustworthy resources for research, practice, and teaching.
Getty  collaboration  metrics  analytics  kpis 
august 2017 by stacker
How Mia’s new strategy uses data to create personalized visitor experiences | Alliance Labs
So Mia made data a priority. Our first step was audience segmentation. We looked at our roadmap of the audience journey—which we created based on the Daniel C. Funk and Jeff James study on guiding consumers from awareness to allegiance—with the understanding that visitors cannot be lumped into one generic category. They have different needs, different motivating factors, and different expectations, and in order to move them toward allegiance, we have to understand how best to fulfill what they’re looking for.
Minneapolis_Institute_of_Arts  audience_research  segmentation  analytics 
june 2017 by stacker
Hiring a data scientist – Wikimedia Blog
We recently needed to backfill a data analyst position at the Wikimedia Foundation. If you’ve hired for this type of position in the past, you know that this is no easy task. Based on our successful hiring process, we’d like to share what we learned, and how we drew on existing resources to synthesize a better approach to interviewing and hiring a new member of our team.
analytics  job_descriptions  wikimedia 
june 2017 by stacker
Digital footsteps: Can you measure museum visits without counting them? | Nesta
The analysis is part of a wider trend of using machine learning and new data sources, such as the data generated by social networks and mobile phones, to help with the hard task of tracking people’s movements. For example, data generated by mobile phones and collected by network operators has been used to understand how many people take part in a certain event. In a similar fashion, Twitter and FourSquare data has also been used for similar purposes. [2]
nesta  metrics  analytics  foursquare  Twitter  audience_research 
april 2017 by stacker
Becoming a Data Startup – Part 2 | Alliance Labs
It’s time again for our next installment of Becoming a Data Startup! For those of you who read along in our last post, you learned some simple tips and tricks for formatting your data that I promised would make things easier for analysis and visualization. This week’s post will take advantage of the work you did to venture into the world of Business Intelligence tools to take some simple next steps in analyzing your data.
analytics 
april 2017 by stacker
What Does Data Have to Do with It? – Digital @ MoMA – Medium
As the spring 2017 intern in the department of Digital Media at MoMA, my goal has been to try to answer to the rather exciting question: “how should we integrate digital analytics into our work?”
analytics  metrics  MoMA 
april 2017 by stacker
Are Mobile Apps Worth It For Cultural Organizations? (DATA) | Know Your Own Bone
Are mobile applications working to best serve our audiences? Do organizations need them? Do data suggest that mobile applications are generally an effective use of funds? The data-informed answer – to all of these questions – is no.
app  analytics  Strategy  mobile 
april 2017 by stacker
Finding the motivation behind a click: Definition and implementation of a website audience segmentation | MW2015: Museums and the Web 2015
Understanding our audiences is a key element in the design of the digital experiences we offer. Our digital strategy principles aim for an approach that is audience centred and insight driven. The Tate website gets approximately 1.5 million visits a month, and while analytics and other tracking tools provide a huge amount of data about user behaviour on the website, there are some limitations in getting to know the motivations and experience behind a click. In order to get a better understanding of who comes to our website, we have carried out substantial research divided into two phases whose methodology and results is explained in this paper. The first phase consisted of the analysis of the motivations and usage of the online collection. There is a wide range of reasons behind the visits to this section of the website, from research to looking for inspiration or remembering with emotion an artwork seen during a gallery visit. Moreover, visitors have different levels of art knowledge; therefore, the information required and content needs vary. This audience-research work helped to define our second piece of research, a survey for the whole website aimed to better know our online visitors and, as a result, define a segmentation that classified website visits based primarily on the motivations driving users to the site, but also taking into account a set of variables such as knowledge of art, vocational connection, online behaviour, and the connection of a particular website visit with the gallery experience. The nine segments defined at the end of the research were: personal interest research, student research, professional research, inspiration, enjoyment, art news, repeat visit planning, first visit planning, and organisational information.
Elena_Villaespesa  analytics  audience_research  mw2015 
march 2017 by stacker
What makes good video? Using data to do better with our content.
The Media Production and Branding SIG and the Data and Insights SIG have combined efforts to develop an online survey to gain an understanding of the scope of production and goals of production in museums today. In this talk we will present an analysis of the collected data from the survey to gain understanding of the state of video production in museums.
Elena_Villaespesa  video  analytics 
february 2017 by stacker
Digital Works #1 |
Session 1: Digital as a business function – procurement
Session 2: Digital as a business function – when to outsource
Session 3: Analytics, data and agility – analytics and user testing
Session 4: The digital user experience – Content creation and distribution
Session 5: The digital user experience – Connecting physical and digital experiences
Session 6: Future focus – bots, AI and automation in an arts context
Final thoughts
procurement  managing  project_management  conference  video_production  analytics 
february 2017 by stacker
The power of applied data for museums | Alliance Labs
At the Art Institute of Chicago, this set of challenges has led us to apply data and analytics to decision-making across all areas of our organization. In the process, we have gained valuable insight into how our museum works, unprecedented growth in operating revenue and operational efficiency, and, most importantly, greater confidence in using our resources most effectively to pursue our mission to educate and inspire future generations of museum visitors.
art_institute_of_chicago  data  analytics  kpis 
january 2017 by stacker
If We Are Digital – Make Better Social Media Metrics/Goals for 2017
As we set our social media goals for the new year, perhaps we should not be striving for higher follower numbers but for quality followers – that is, more enaged followers. That might mean that we have to stop thinking of them as “followers” who just passively follow along and more as community members. And to set higher standards for how and how often we interact with them.
social_media  analytics  kpis 
january 2017 by stacker
Optimize for Return Visits, not Bounce Rate
Use bounce rate as a red flag to find possible issues lurking on your site, but then switch your focus to large site goals: purchasing a product, contacting for a quote, registering for a newsletter, signing up for an account, returning to the site as a resource for information, and so on. Ask how each page supports these bigger goals and don’t push for single-visit actions. Optimize for the deeper end-goals that often take multiple visits to accomplish and keep your focus on the more important task of encouraging continued engagement and building loyalty. Of course, increasing loyalty and reducing bounce rates aren’t mutually exclusive. But strive to reduce bounce rates via usable means, such as providing relevant related content, and not by adding gimmicks.
analytics  kpis  bounce_rate 
january 2017 by stacker
Wikipedia Pageviews Analysis
Comparison of pageviews across multiple pages
Wikipedia  analytics 
november 2016 by stacker
100+ Questions To Data Analytics – Medio Blog
This is why I have made a list of examples of genuinely important metrics and analytical scenarios from different environments and projects. By far not all of them will apply to your specific website and the list is by far not exhaustive. My goal today is to give you some clues as to what you might also consider keeping track of and what sort of questions you could and should ask.
analytics  kpis 
october 2016 by stacker
Understanding a museum’s digital audience - Optimal Workshop
At Te Papa the digital team created six audience personas to inform their site redesign, based on user research:
Te_Papa  audience_research  segmentation  redesign  analytics 
september 2016 by stacker
British Museum Collection Online (2013)
Presentation by Matthew Cock, Head of Wed at the British Museum, given on 31 January 2013 at University College London
slideshare  British_Museum  collection  analytics 
september 2016 by stacker
Scholarly Information-Seeking Behaviour in the British Museum Online Collection | museumsandtheweb.com
This paper presents a collaborative study between UCL Centre for Digital Humanities and the British Museum. It considers the use and information-seeking behaviour by scholars of the British Museum's Collection Online. The research focuses on user perspectives, search strategies and general use of museum digital resources, highlights the scholarly value of museum digital resources, and examines the existing structures of presentation and representation of the British Museum Collection Online for aiding academic information seeking. It provides an example of how, with detailed analysis of user survey data, museums can elucidate academic user groups' perceptions of museum collection information environments, and improve their understanding of how the functionality and usability of museum's digital collections aids individual's information searching.
University_College_London  British_Museum  collection  mw2011  analytics 
september 2016 by stacker
Measure what you can: data to support innovation in the arts | Nesta
The reason for this, as we see it, is that use of digital technology can rarely be separated from other social factors that contribute to the success of a project – your organisational culture, or the way your audience perceive you, for example. We have seen many digital projects that, whilst not necessarily a bad idea, have failed to achieve the intended benefits because they were not based on a full understanding of the context around a particular challenge. 
nesta  audience_research  analytics 
august 2016 by stacker
Weeknotes 33: What you need to know before making a mobile experience | Frankly, Green + Webb
I thought I would share it here because it might have wider use for people either considering creating a new mobile experience or needing inspiration to improve the usage/experience for one. If you’re not in either of those groups – then scoot down to the bottom where our normal weekly update including a bit of news about the team.
I’m going to use the customer journey as a model because we find it a good way to make sure you don’t miss what’s important for the visitor. Laura shared this model in a Museums and the Web paper with the Met in 2015.
mobile  app  research  user_journey  marketing  analytics 
august 2016 by stacker
Measuring Social Media Success: The value of the Balanced Scorecard as a tool for evaluation and strategic management in museums | arts & metrics
This Ph.D. research was triggered by the existing need for an evaluation model that will help museums to measure their social media success. This thesis defines a performance measurement framework that could be adopted to select the set of measures and tools required to carry out this evaluation task. In order to develop the framework, this thesis investigates the strategies and usage of social media based on original data collected from twenty cultural organisations as part of the UK’s ‘Let’s Get Real’ national action research project.
Elena_Villaespesa  thesis  analytics 
august 2016 by stacker
An Essential Training Task List for Junior SEOs - Moz
Have a look around at current SEO job listings. You might be surprised just how much we’re expected to know these days:
analytics  job_descriptions  SEO 
august 2016 by stacker
Digital Analysts Enhance The Online Visitor Experience | Create Hub
Chris Unitt discusses how cultural organisations have been slow to embrace digital analytics and explains the role that they can play in enhancing the online visitor experience.
analytics 
august 2016 by stacker
“Hey could you give me the numbers on that again?” — Digital @ MoMA — Medium
The vast majority of the work in building a dashboard for MoMA’s digital properties has been in figuring out why the numbers are what they are, and how to get them into a consistent and useable format. Updating them automatically on a schedule has been icing on the cake. This is a project that has taken me across the museum and a good chunk of the internet. And it’s become abundantly clear that there is no substitute for personal conversations.
MoMA  analytics  dashboard  google_docs 
august 2016 by stacker
Local Measure - Local Customer Intelligence
Select an address or area on a map for instant visibility into the social content posted from that place.
social_media  location_aware  analytics 
august 2016 by stacker
A new approach to museum audio tours, by the numbers — Detour Blog — Medium
Lee believes “many of the offbeat audio tours seem geared to those who rarely, if ever, set foot in a museum, underestimating much of SFMOMA’S audience.” So we took a look at the data to see what SFMOMA’s audience thinks. Here’s the list of the most popular content at the museum (as of today):
SFMOMA  audioguide  analytics 
august 2016 by stacker
Site Performance Reporting - Coding is for Losers
These report templates dig into the technical performance of your site. Are there any conversion leaks hiding in your funnel, across browsers or devices?

A set of four reports use Blockspring to pull Google Analytics data into a Google Spreadsheet, and analyze the impact of usability and page load speed on conversions.
analytics  performance  google_analytics 
july 2016 by stacker
Dashboards that Rock: Google Analytics, AdWords, Facebook
This report shows the progression of your customers from the first step to the last, allowing you to see where most people get lost in the process.
dashboard  conversion  checkout  analytics  tools 
june 2016 by stacker
Measuring Content: You’re Doing it Wrong - Moz
One metric that Medium uses, which I think adds a lot more value than pageviews, is "Total Time Reading (TTR)." This is a cumulative metric that quantifies the total number of minutes spent reading a piece of content. For example, if I had 10 visitors to one of my blog articles and they each stayed reading the article for 1 minute each, the total reading time would be 10 minutes.
content_strategy  buzzfeed  kpis  analytics 
may 2016 by stacker
What percentage of visits to your ecommerce sites are on mobiles or tablets? - MCG Archives
SESSIONS
Desktop 50%
Mobile 28%
Tablet 22%

REVENUE
Desktop 71%
Mobile 19%
Tablet 10%
V&A  mobile  ecommerce  ticketing  analytics 
april 2016 by stacker
The Web Analytics Maturity Model (pdf)
For the purpose of defining the Web Analytics Maturity Model, the definition of web analytics is:
“The extensive use of quantitative and qualitative data (primarily, but not limited to online data), statistical analysis, explanatory (e.g. multivariate testing) and predictive models (e.g. behavioral targeting), business process analysis and fact-based management to drive a continuous improvement of online activities; resulting in higher ROI.”
This definition is broader than the official definition of the Web Analytics Association definition (Web Analytics Association n.d.) and is largely inspired from Thomas Davenport’s definition of analytics in “Competing on Analytics” (Davenport and Harris 2007)
analytics  digital_transformation 
march 2016 by stacker
A Very Happy & Open Birthday for the Pen | Cooper Hewitt Labs
March 10, 2015 to March 9, 2016 total number of times the Pen has been distributed – 154,812
March 10, 2015 to March 9, 2016 total objects collected – 3,972,359
March 10, 2015 to March 9, 2016 total visitor-made designs saved – 122,655
March 10, 2015 to March 9, 2016 mean zero collection rate – 23.8%
March 10, 2015 to March 9, 2016 mean time on campus – 110.63 minutes
Feb 25, 2016 to March 9, 2016 post visit website retrieval rate – 28.02%
Cooper-Hewitt  analytics 
march 2016 by stacker
Analysing Virtual Audiences (II). Connecting and Deepening the Relationship | Article | CCCB LAB
Understanding audiences and evaluating the impact and value of their digital experiences is an essential element in the digital transformation that cultural institutions are going through. The following text is a reflection on the implementation of digital practices centred around the audience and their needs, digital practices that should be informed precisely by an analysis and a study of the audience. Our goal is to apply this methodology to the Lab’s blog in order to make its contents more relevant, to improve the communication strategies and to adjust the format in which contents are presented in accordance to the users’ motivations and interests.
audience_research  analytics 
february 2016 by stacker
What motivates a visit to MoMA’s website? — Digital @ MoMA — Medium
Our redesign of moma.org started in the spring of 2015 with five insights from Google Analytics. Our audience is younger than we realized: More than half of visitors to moma.org are aged 18–34. They are increasingly mobile: Almost 30% of our visitors access the website from a mobile or tablet device. Our online audience is more local than international, which is the inverse of what we see at our 53rd Street building. Our collection is our core asset, both on- and off-line: It attracts almost 30% of engaged views and it’s what most visitors have searched for. Every piece of content is the homepage: With the dominance of search, and rise of social media, the MoMA homepage is less critical to discovery and navigation. Today, only a quarter of our visitors arrive at our website via the homepage.
Moma  redesign  analytics  google_analytics  audience_research 
february 2016 by stacker
10 Resolutions Every Arts Manager Should Make For Better Data Driven Decisions In 2016 | Arts Hacker
One of the best resources for data is right at your fingertips via website metrics and it doesn’t matter if you’re a neophyte or ninja, here are some resolutions you can make that will help you take control of 2016.
google_analytics  google_webmaster_tools  analytics 
january 2016 by stacker
MCA – Facts and Figures
The MCA collects a vast amount of data that tell the story of our exhibitions, programs, events, and community. This section presents a selection of those facts and figures. New visualizations will appear regularly.
Museum_of_Contemporary_Art_Chicago  dashboard  analytics 
november 2015 by stacker
Digital Dashboard - Carnegie Museums of Pittsburgh
From October 1, 2015 to October 31, 2015 the Carnegie Museums of Pittsburgh had 196,487 people visit their websites. Those users viewed 598,960 pages. During that time, visitors spent an average of 94.28 seconds using the website, viewing an average of 2.33 pages per visit.
Carnegie_Museums_of_Pittsburgh  dashboard  analytics 
november 2015 by stacker
The Digital Metrics Dashboard | Innovation Studio
Google Analytics is a staple utility that most organizations use to see all sorts of information about their digital properties, such as how many people viewed their site and what pages they viewed. It is a very useful tool to see what is working and what can be improved upon. However, it can be very overwhelming if you don’t know what you are looking for or how to find it. We wanted to create a much simpler interface that museum leadership and/or staffers with little-to-no experience with analytics could instantly understand.
Carnegie_Museum_of_Art  dashboard  analytics 
november 2015 by stacker
Data Stories Centralized: A Digital Analytics Dashboard | The Metropolitan Museum of Art
Based on the reporting requirements, I've sketched a basic mock-up—using dummy data—to discuss the metrics that should be included. The mock-up's overview page features Key Performance Indicators (KPIs) that can be used for high-level conversations about strategy. This page links to subsections that can show the metrics of specific digital initiatives. The data in the dashboard can be categorized in different ways according to strategic objectives, audiences, or usage context. For instance, one of the dashboard sections can focus on the digital experience of a visitor to the Museum, which means we would include data about the Met app, audio guide, Wi-Fi, in-gallery interactives, and website usage in relation to the visit.
dashboard  Metropolitan_Museum_of_Art  Elena_Villaespesa  analytics 
october 2015 by stacker
5 months with the Pen: data, data, data | Cooper Hewitt Labs
Its been five hectic months since the Pen started being distributed to visitors at the ticket counter, and we’ve been learning a lot. We last made some basic stats available at the 100 day mark, but how has usage changed – especially now that almost every area of the museum has been changed over in terms of exhibitions and objects? And what are the tweaks that have made the difference?
cooper-hewitt  interactive  analytics 
august 2015 by stacker
Embedding evaluation in the digital production process | arts & metrics
During the production phase it is crucial to set up the tools that will be needed to gather the desired data. For instance, in order to collect tweets on a particular exhibition, conference or performance, there are very useful tools such as Rowfeeder or a IFTTT recipe, but given the platform’s data access limitations is important to set up the queries in advance.
production  Elena_Villaespesa  analytics 
july 2015 by stacker
Data Guide available for download - Digital R&D Fund for the Arts
Data is a key learning theme from the Digital R&D Fund for the Arts. Data is influential when used correctly, and in context. Learning how to get the best from your data is the first step. Understanding what data to share, what data you could collect, and how you can combine it with data from other sources is the next.
nesta  Arts_Council  report  analytics 
july 2015 by stacker
analytics.usa.gov | The US government's web traffic.
This data provides a window into how people are interacting with the government online. The data comes from a unified Google Analytics account for U.S. federal government agencies known as the Digital Analytics Program. This program helps government agencies understand how people find, access, and use government services online. The program does not track individuals, and anonymizes the IP addresses of visitors.
analytics  dashboard  government2.0 
july 2015 by stacker
Analyzing #MetGala Engagement across the Globe | The Metropolitan Museum of Art
On Monday, May 4, 2015, the Met and Vogue hosted the annual Costume Institute Benefit, which celebrated this year's spring exhibition, China: Through the Looking Glass, on view through August 16. Notables from the worlds of fashion, film, society, sports, art, business, and music attended the Met Gala and were captured walking the red carpet across a wide range of social media.
Metropolitan_Museum_of_Art  analytics  social_media 
may 2015 by stacker
GLAM Tools
These are some Wikimedia-related tools for Galleries, Libraries, Archives, and Museums.
Wikipedia  analytics 
may 2015 by stacker
Comparing numbers: physical visitors and digital visitors | Digital at Southbank Centre
Our assumption is that, as the Southbank Centre starts to engage digital audiences more effectively through experiences and discussions (beyond getting those people to attend the venue) that audience will grow relative to the venue’s physical audience.
analytics  Southbank_Centre 
april 2015 by stacker
Four Things I Wish Analytics Tools Did - Inside Intercom
When traffic spikes, the question is Why? When conversions drop, the question is Why? When sign-ups flatline, the question is Why? Leaving your customers to do visual gymnastics as they try to piece together parts of your product is a bad experience.
analytics 
april 2015 by stacker
the warhol: digital metrics dashboard
These analytics snapshots reflect user activity across The Andy Warhol Museum's digital properties. The historic data reports are updated at the beginning of the calendar month, while the recent activity are updated at 5AM daily.
Andy_Warhol_Museum  dashboard  analytics 
april 2015 by stacker
Auto event tracking with Google Tag Manager
Implementing analytics, or any type of conversion tracking, is a big pain in the ass. There, I said it! But it’s been getting easier and easier with adoption of Tag Management tools. Google Tag Manager is going to make it even easier with the introduction of a new feature called Auto Event Tracking.
google_analytics  analytics 
march 2015 by stacker
Tate Kids: digital play and participation | Tate
For the last few months I have been researching into how users experience the Tate Kids microsite, what content they go to and what they think about it when they are there. The research was conducted through a mixed method approach, combining quantitative and qualitative practice. This included: Google analytics and heat maps, qualitative research (carried out by Fusion Research, a specialist agency) and desktop research into digital trends. You can read the report [PDF, 844.5kb] which includes analysis of Tate Kids users and details of their motivations for visiting the microsite.
Tate_Kids  audience_research  tate  analytics 
march 2015 by stacker
My Favorite 5 Analytics Dashboards - Whiteboard Friday - Moz
So, what's important? I have the top five dashboards that I like to share with my clients and create for them. These are the executive dashboards -- one for the CMO on the marketing side, new markets, content, and a tech check. You can actually create dashboards and make sure that everything is working.
dashboard  analytics  google_analytics 
march 2015 by stacker
New Source Alert: Wikipedia | Altmetric.com
Within those millions of articles exist hundreds of thousands of links to academic research. Publishers, institutions and researchers are increasingly moving to leverage the exposure and traffic that a reference on Wikipedia can generate for their content. Although the value and relevance of that traffic is sometimes debated, for their part Wikipedia enforce strict editorial guidelines to try and ensure that quality and standards are consistent across articles, and that undue bias isn’t shown towards over-zealous posters.
Wikipedia  analytics  citation 
march 2015 by stacker
Measuring Community Engagement: A Case Study from Chicago Public Media | RJI
Though we have only just begun, by tracking these metrics over time we hope to gain a better understanding of what works and why. Our goal is to demonstrate how engagement impacts civic health and increases the local significance of the station as a community institution. It is also our hope that this case study is helpful in furthering the industry’s collective understanding of community engagement initiatives and their impact, and that over time cooperation to share engagement numbers – as the industry does with listener and sales data – will one day be commonplace.
kpis  Chicago_Public_Media  engagement  community  analytics 
march 2015 by stacker
Museum 2.0: Data in the Museum: Experimenting on People or Improving Their Experience?
Consider the following scenarios. Is it ethical to... track the paths people take through galleries and alter museum maps based on what you learn? give people different materials for visitor comments and see whether the materials change the substance of their feedback? cull visitor comments to emphasize a particular perspective (or suite of perspectives)? offer visitors different incentives for repeat visitation based on behavior? send out two different versions of your annual membership appeal letter to see which one leads to more renewals? classify visitors as types based on behavior and offer different content to them accordingly?
nina_simon  analytics  personalisation 
february 2015 by stacker
An evaluation framework for success: Capture and measure your social-media strategy using the Balanced Scorecard | MW2015: Museums and the Web 2015
Despite the vast amount of data at their disposal, museums struggle to measure the impact and value of their social-media activities due to the lack of standard metrics, consistent tools, and clear guidelines from funders. This paper attempts to define a performance measurement framework that may help museums define the set of measures and tools required to carry out this evaluation task. The evaluation tool proposed is an adaptation of the Balanced Scorecard, a framework developed by Robert Kaplan and David Norton and presented in the Harvard Business Review in 1992.
Elena_Villaespesa  tate  social_media  analytics  strategy  mw2015 
february 2015 by stacker
#HEFCEMetrics: More on Metrics for the Arts and Humanities | Ernesto Priego
Altmetrics is “the creation and study of new metrics based on the Social Web for analyzing, and informing scholarship.” (Priem et al 2010). Altmetrics normally employ APIs and algorithms to track and create metrics from the activity on the web (normally social media platforms such as Twitter and Facebook, but also from online reference managers like Mendeley and tracked news sources) around the ‘mentioning’ (i.e. linking) of scholarly content. Scholarly content is recognised by their having an identifier such as a DOI, PubMed ID, ArXiv ID, or Handle. This means that outputs without these identifiers cannot be tracked and/or measured. Altmetrics are so far obtained through third-party commercial services such as Altmetric.com, Plu.mx and ImpactStory.
scholar  citation  altmetrics  library  doi  social_media  digital_humanities  analytics 
january 2015 by stacker
E-Commerce KPI Study: There's (Finally) a Benchmark for That - Moz
We often break down conversion rate into two parts: website-to-basket and basket-to-checkout. Industry norms tell us expect about 5% CR on website-to-basket and 30% on basket-to-checkout. Check which one of these conversion rates is most out of kilter on your site, then focus your attention there.
checkout  benchmarks  ecommerce  kpis  analytics 
january 2015 by stacker
Simplify your Google Analytics Reporting with Add-ons for Google Sheets - Analytics Blog
It's common for Google Analytics users to use spreadsheets to analyze their Google Analytics data or combine it with another data source. But exporting your data from Google Analytics to Google Sheets is a manual process, and it can be tedious if you run reports frequently or manage multiple accounts. With the release of Add-ons for Google Sheets, getting your Google Analytics data into Google Sheets has never been easier!
google_analytics  Google_Drive  analytics 
january 2015 by stacker
When the Art Is Watching You - WSJ
Across the country, museums are mining increasingly detailed layers of information about their guests, employing some of the same strategies that companies like Macy’s, Netflix and Wal-Mart have used in recent years to boost sales by tracking customer behavior. Museums are using the visitor data to inform decisions on everything from exhibit design to donor outreach to gift-shop marketing strategies.
wall_street_journal  big_data  Dallas_Museum_of_Art  Metropolitan_Museum_of_Art  personalisation  bluetooth_low_energy  analytics 
december 2014 by stacker
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