“Big Data in Museums” or the “Big Debate” (2/3)


12 September, 2018

“Big Data in Museums” or the “Big Debate” (2/3)

In the previous article – What’s the meaning of “Big Data in museums? we talked about the key to unlocking the value of Big Data: to convert data into knowledge. This conversion of data into knowledge obviously has a cost attached to it, or rather several. It usually involves an economic outlay, requires the consent of visitors, a certain level of employee training and beyond this, it will stimulate strategic changes for the management of the museum. These “costs” are at the centre of what some have come to call the “Big Debate”. The opinion polls show two sides to the argument. One group that believes the cost exceeds any potential benefit; whilst the other side believe the potential benefits far outweigh the cost. Although there are many other factors in play, the main sticking point in the argument is usually the economic variable.

At the heart of Big Data’s definition (at least one of the ones we like the most) lies the following phrase:

“Big Data refers to groups of data that are so large and complex that regular database management tools have difficulty capturing, managing, processing and analysing them using conventional technologies and methods.”

In short, what this technology should allow us is to simplify the processes of extraction and analysis so that the operation is worthwhile. No more quasi-manual surveys, unrepresentative samples and expensive research panels. Knowing our visitors nowadays should be both easier and more useful. What really matters however is what to do once we know them. Then we must ask ourselves whether or not the knowledge gained from the data will allow us to improve.

LUCA, Telefónicas analytical unit, speaks of 3 tools that will be useful for extracting data in museums:

  • Beacons – which need an app, an interactive guide or some device that allow for location services.
  • Chatboxes or an equivalent – machines answering questions from visitors in their native language.
  • Machine vision or machine learning – perhaps one of the main challenges of current R+D+I projects (such as CrossCult).

In museums such as the Bernabéu Tour (Real Madrid stadium), monuments such as the Alhambra or cities like Salamanaca (Spain), GVAM uses interactive guides with location services as one of the ways to capture data. Taking data from these tools is now a real possibility at a residual cost, since it makes use of one of the traditional channels of interaction with a museum audience: audioguides. It is also the only channel capable of tuning in with such a large sample during the visit (between 15-20%) and on a daily basis. Until recently, these devices were a unidirectional communication tool, whereas now all efforts are focused on making them more participatory and personalized.

But as we said, no matter how simple or difficult the data is to extract, what really matters is the use we make of it. In our case we understand that the interactive audioguide may be used to contribute to Big Data. It’s only a small part of the bigger picture, but can be essential when used with other technologies. The ultimate goal is to act on those issues most relevant to the management of the museum: attracting more people, generating more profit and getting the visitor to return.

At our upcoming conference titled Big Data in Museums (#bigdatamus), directed exclusively towards professionals in the sector, we will show examples of how exactly audioguides can contribute. Videos and conclusions from the conference will soon be posted on our YouTube channel.

Meanwhile, let us know what you think? Do you believe the benefit outweighs the cost? Or vice versa?

Send us an email at comunicacion@gvam.es or get in contact through one of our social channels!