{"id":32814,"date":"2021-11-22T16:45:01","date_gmt":"2021-11-22T16:45:01","guid":{"rendered":"https:\/\/digileaders.com\/?p=32814"},"modified":"2021-11-22T16:45:01","modified_gmt":"2021-11-22T16:45:01","slug":"we-ran-a-data-and-analytics-retro-for-charities-heres-what-we-learnt","status":"publish","type":"post","link":"https:\/\/digileaders.com\/we-ran-a-data-and-analytics-retro-for-charities-heres-what-we-learnt\/","title":{"rendered":"We ran a data and analytics retro for charities \u2014 here\u2019s what we learnt"},"content":{"rendered":"
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As a nonprofit digital agency,\u00a0DEV<\/a>\u00a0are often asked about data and analytics by our charity partners. Whether we\u2019re building a new website or designing a digital report, our partners want to know how they can use digital to find out about their target audience.<\/p>\n

Retrospectives (or \u2018retros\u2019) are a meeting format that allows us to review a project once it\u2019s complete. During a retro, we look at what worked well and what worked less well. We then use this as a starting point to identify ideas for improvement, and define next steps.<\/p>\n

In Septe<\/span>mber, we decided to run a retro on data and analytics for nonprofits. Our aim was to understand the\u00a0why\u00a0<\/em>behind nonprofit data collection, and learn how we can best support our partners to keep their mission and purpose at the centre of the work they do.<\/p>\n

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\"\"Data and analytics retro board on Miro<\/div>\n<\/div>\n<\/figure>\n

We were joined by around thirty organisations who shared their experience and ideas. A huge thank you to everyone who joined and contributed!<\/p>\n

Here\u2019s what we learnt.<\/p>\n<\/div>\n<\/div>\n<\/section>\n

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How are charities and nonprofits using data and analytics?<\/h3>\n
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We started by mapping\u00a0what data was being used for<\/em>\u00a0by the organisations in the room.<\/p>\n

This led us to identify three different thematic areas:<\/p>\n

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  1. Fundraising and campaigns<\/strong><\/li>\n<\/ol>\n

    This included creating reports for donors, supporting new ideas and segmenting audiences \u2014 for example by donation amount. Data was also collected to provide stats for press releases, or to measure impact in support of a campaign.<\/p>\n

    2. Strategy<\/strong><\/p>\n

    Participants explained that they used data to understand where there\u2019s high demand for services, and used this to inform their strategy. They were also able to use data to understand how people interacted with their communications, and to compare trends in their data with \u2018world trends\u2019<\/p>\n

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    \u201cAs a Digital Comms officer, I mostly compare current trends on my charity\u2019s website with world news and base my advice to the organisation at large on my conclusions\u201d<\/p>\n<\/blockquote>\n

    3. Performance Management<\/strong><\/p>\n

    The third area was performance management \u2014 making sure they were meeting their goals, managing volunteers and supporting logistics.<\/p>\n

    We then asked about the\u00a0how\u00a0<\/em>\u2014 the tools that were being used.<\/p>\n

    The short answer here was \u2018Google Analytics\u2019! Insight tools from social media platforms were also mentioned.<\/p>\n<\/div>\n<\/div>\n<\/section>\n

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    Next, we asked about what\u00a0was<\/em>\u00a0working well, and what\u00a0wasn\u2019t<\/em>\u00a0working so well.<\/p>\n

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    What\u2019s working well?<\/h3>\n
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    1. People<\/strong><\/li>\n<\/ol>\n

      When we start to talk about data, we often think about the technology behind data collection. So it was a pleasant surprise that people got a big shout out \u2014 high fives to the data people out there!<\/p>\n

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      \u201cWe have an SEO person who does a great job helping us analyse our Google Analytics\u201d<\/p>\n

      \u201cOur CEO is really supportive \u2014 this demonstrates that our organisation buys in to data\u201d<\/p>\n<\/blockquote>\n

      2. Audience<\/strong><\/p>\n

      The second theme that emerged was about using data and analytics to understand their audience.<\/p>\n

      Charities are using data to better understand their supporter base, personalise their campaigns and look at levels of engagement. Data can also help them to identify trends \u2014 understanding why people engage in the first place.<\/p>\n

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      \u201cBecause we can understand what our supporters are interested in, we can make sure our policy responds to their interests and has their support\u201d<\/p>\n<\/blockquote>\n

      3. Reporting<\/strong><\/p>\n

      Not surprisingly, reporting was a big theme. Some organisations mentioned that they were\u00a0only\u00a0<\/em>collecting data for the purpose of reporting to funders requirements.<\/p>\n

      However, others mentioned that data helped them to ensure they were setting clear, measurable targets to support their projects. We also heard about how data could play an important role in communication, improving engagement with complex topics.<\/p>\n

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      \u201cThe data we collect helps us to report to our funders and, in turn, access more funding!\u201d<\/p>\n<\/blockquote>\n

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      What\u2019s not working well?<\/h3>\n

      There was less coherence about what wasn\u2019t working for the sector. Here, the main challenges included: linking up data, limitations with the tools people were using and demonstrating impact. Contradictorily, not enough data and too much data were also listed as challenges!<\/p>\n

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      1. Tools<\/strong><\/li>\n<\/ol>\n

        Collecting data isn\u2019t the same as analysing it, and people raised concerns about how data was being interpreted. This included not having enough budget to invest in tools, not having a CRM or not having an easy to use website \u2014 all of which placed limits on the usefulness of the data<\/p>\n

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        \u201cOur website is messy \u2014 so it\u2019s hard to know whether our bad stats are due to a lack of interest or a lack of ability for people to find information!\u201d<\/p>\n<\/blockquote>\n

        2. Linking up data<\/strong><\/p>\n

        There were lots of challenges around integrating analytics tools with different systems and databases. People also noted that mistakes such as duplicating data entries when working across multiple systems could lead to misleading data.<\/p>\n

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        \u201cBecause engagement comes from different sources, we\u2019re creating duplicate records which leads to a lot of confusion!\u201d<\/p>\n<\/blockquote>\n

        3. Demonstrating impact<\/strong><\/p>\n

        We heard how sometimes the need to demonstrate impact could lead to data being manipulated or poorly interpreted. People also commented that sometimes they don\u2019t decide what to report on until the end of the project \u2014 at which point it\u2019s too late to collect data in any meaningful way, and often the data that has been collected is made to fit the purpose.<\/p>\n

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        \u201cNo goals mean you can\u2019t fail\u2026.! But if you don\u2019t set these up front it also makes it challenging to measure impact\u201d<\/p>\n<\/blockquote>\n

        4. Not enough data or too much data<\/strong><\/p>\n

        Some organisations commented that they could only collect so much data \u2014 and this meant they were lacking the insights they needed. For others, the challenge was actually using all the data they collect, or having the time they needed to go deeper into their analysis.<\/p>\n

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        \u201cThe need for proper analysis is greater than our need to report these headline basic findings \u2014 but we often lack the time and resource\u201d<\/p>\n<\/blockquote>\n<\/div>\n<\/div>\n<\/section>\n

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        During the final part of the retro, we shared ideas and actions. This step is about applying the learning from the retro and understanding how we can improve our work. I\u2019ve summarised the ideas and actions below.<\/p>\n

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        Ideas<\/h3>\n