2017 has been named the year of ‘Evidencing the Museum’ by Museums Aotearoa, encouraging cultural institutions to explore more ways to utilize data for planning and advocacy, locally and nationally. We explore innovations for this effort in the form of big data analytics (article originally published by Museums Aotearoa).
Globally, the ground under museums is shifting. Government funding changes, endowment tax variations and competition with entertainment alternatives all impact our institutions’ future. In this landscape, evidencing the museum is vital to manage economic sustainability of the museum model, while supporting the changing role of museums in society. Despite the value of culture to society and follow on benefits – increased education, reduced criminality and improved health – being widely appreciated, museums still face their own commercial realities behind achieving social good. Borrowing innovative thinking and technology from the for profit sector in the form of big data analytics financially enables the museum mission.
Given ‘What gets measured, gets managed’, establishing a set of key performance indicators to forecast, goal and track sets the focus to evidence the museum. Core metrics, which need to be continually, consistently and clearly communicated until they become a mantra for the museum team, include:
- Visitorship, depending on the museum’s funding structure and remit, including targets to even seasonal spread, increase repeat locals, improve tourist share or achieve demographic diversity
- Engagement, reflected onsite and online, articulated as a conversion funnel to from reach to admission, activation, revenue and retention
- Performance, evaluating the key levers of the museum business model, such as Average Revenue Per Visitor (ARPV), Average Admission Per Visitor (AAPV) and Average Upsell Per Visitor (AUPV) – together with OPEX per visit, sometimes expressed as Net Value Per Visitor (NVPV); or together with repeat visit rate, as Annual Visitor Value (AVV) or Lifetime Visitor Value (LVV) for locals or members
- Satisfaction, taken from visitor surveys, Net Promoter Score (NPS), social media (such as Trip Advisor, Facebook or Google reviews) or a combination (note the concept of ‘satisfaction’ may need to be carefully revisited if exhibitions deal with a challenging topic matter)
- Evaluation motivations and educational outcomes, expressed in both quantitative and qualitative terms
Whilst knowing the museum’s data points is an important step, the next level involves understanding deeper insight, revealing trends requiring a museum response. Chiefly, the museum should look for factors influencing performance, delineating those within the museum’s control to tweak (such as exhibition scheduling, marketing budgets, opening hours) and aspects outside its sphere of control to respond to (weather, regional events, school holidays); particularly when the museum is not on plan. In a museum’s internal culture, a shift of language to focus on the numbers helps disassociate individual attachments to ideas (avoiding manifesting ego) and direct the conversation to ‘why’, over ‘who’ (avoiding manifesting blame).
Evidencing the museum supports community discussion of the museum, as any new build will attest to, given common scrutiny following an opening. Data demonstrates economic value – such as tourism draw, to secure grants. Transparency around numbers inspires investment, in the form of funding, sponsorship and endowment – decreasing donor attrition following reporting. These indications help the museum’s leadership to drive performance and create a transparent, open culture across the institution.
Museums can start by stocktaking data and understanding data governance. How are visitors counted? What else do we know about visitors? What can be analysed? What about members? What about the wealth of digital data, such as web or social media? What’s happening in the wider region?
Once this data is at hand, the museum can begin building capability to put this in the hands of decision makers and work on challenges or opportunities insight addresses. This is where technology aids in bringing disparate data sources together, maintaining a data warehouse as a central store, automating insights and delivering these in a business ready manner to match how museums need evidence. Technology innovation shifts evidence in museums from historic reporting, to in the moment updates, to predictions for the future.