Insight Final Report

Full report available at https://www.blackradley.com/assets/Insight-Final-Report-2015-11-11.pdf

Background

These are troubled times for the cultural sector. In the wake of the ongoing reductions to public funding, museums and other cultural organisations are increasingly looking for alternative sources of income.

The drive to become more commercially astute is something that has gained momentum in recent years. Growing numbers of organisations are placing a greater emphasis on generating income through commercial activity; in particular, maximising visitor spend.

Museums are unique; unlike a shop or a restaurant, where numerous studies have been undertaken to understand what stimulates spend in those environments and indeed a discourse of best practice has evolved to respond to the marketplace, very little information exists on what drives commercial growth in the museum environment.

Many have a shop and a café, some charge for admission and some run special events. This consistency means that it might be possible to compare the commercial performance of museums together as a group, and discover exactly what factors are important in determining visitor spend and therefore commercial success.

The Project

In 2014 Black Radley formed a project partnership with Bath Spa University and The Ryan O’Neill Partnership to attempt to discover what factors drive visitor spend in the museum environment. This project came to be known as ‘Insight’.

Major advances in accessibility and applicability of machine learning technology meant it was now possible to determine which factors most affect museum performance and to use those factors to determine what the “ideal” expected performance might be for an individual museum.
In order to do this, the project partners needed to understand:

  • The best way of categorising museums based on commonality of offer (i.e. ‘museum’, ‘castle’, ‘historic house’, etc), that would also allow for representation of the differences between individual sites as related to visitor spend (i.e. presence of shop, frequency of events, etc);
  • The most likely ‘internal’ factors that have potential to influence visitor spend (i.e. marketing activity, scale of the site and it’s component parts);
  • The most likely ‘external’ factors that have potential to influence visitor spend (i.e. local demographic profile etc.);
  • The most appropriate means by which to collect this information;
  • The most appropriate means by which to report back the findings.

After a process of rigorous research and in consultation with a steering committee of museum sector representatives, an online platform was designed and built enabling individual museums to:

  • Identify their type of site through a set of common criteria;
  • Provide data about the kinds of activities undertaken at the site (i.e. marketing resource, and component parts such as type of shop and associated product lines, type of café offer, frequency of ‘special events’ etc.).
  • Submit performance data for each of these key component parts;
  • Access a personalised report which projected expected income for each of these component parts based on an analysis of data provided by participating sites and wider ‘environmental’ data such as demographics of the surrounding area;
  • Access toolkits enabling museums to best respond to their personalised reports.

Results

Despite high initial interest from the sector, eventual participation rates were low. During the life of the project significant resource had to be redirected to increasing the levels and quality of data submitted. Eventually only 64 out of 200 participating sites were able to provide a full 12 months’ worth of data.

It was decided that the focus of the research had to change direction in order to account for this unexpected outcome. The reason for this was that the process of encouraging museums to take part revealed that in many cases the degree of challenge museums experience to take part in such projects had been underestimated; these challenges have direct implications on the sector’s ability to successfully respond to future funding reductions.

The new direction of study resulted in four common ‘barrier to entry’ themes being identified:

  • Use of outdated technology within the sector;
  • Negative perceptions of data projects;
  • Inefficient internal flow of information within organisations;
  • Limited capacity to take part in non-core activity.

Despite low participation rates, the project was able to ascertain a statistically significant relationship between a variety of factors relating to commercial income, including:

  • Sites are likely to have increased visitor numbers if they identify as a ‘Museum’ or ‘Castle’;
  • Population density, presence of a café and having a larger museum has a positive effect on the amount a museum receives from (or can charge for) admission income;
  • Retail income is related to catering income (i.e. if a café is present, people are more likely to spend in the shop and vice versa);
  • Retail income is positively influenced by visitors having to exit through the shop;
  • Retail income is positively influenced by the presence of additional events;
  • Museums who identify as having a ‘park’ as part of their offer are likely to see higher refreshment spend;
  • Museums who provide ‘full meals’, vegetarian options, tea and coffee as part of their catering offer are likely to see increased refreshment spend.

Future

Overwhelmingly the response has been that further research is required to gain a deeper understanding of the factors that play a role in determining commercial performance. This is of course dependent on successfully resolving the challenges faced by museums that prevented participation in this study. Future opportunities for this study include:

  • Expanding the scope and power of the toolkits (and associated methods of deployment and implementation) to address the underlying sectoral issues the study uncovered;
  • Persevering with data collection activities directly with museums;
  • Combining data with that of other data collections and analysis projects to add depth and robustness to the analysis, join up findings, and demonstrate the value of combining research studies to add leverage to currently independent projects.

However, it is the belief of the project partners that the clear priority is to set about addressing the underlying difficulties the sector faces which prevented participation. These difficulties not only had implications for the Insight project, but will likely hamper the sector’s ability to successfully meet the financial challenges ahead.

The project partners are actively collaborating on the pursuit of future projects which aim to address these challenges.