Our 2017 predictions for big data and analytics in the museum

This year, 21% of organizations will test the waters in big data and analytics, the most popular in the new technology set making its way into the enterprise. As 2017 begins, we take a look at the top data trends we expect the year to unveil for cultural institutions.

  1. Demand for immediate gratification
    Traditionally, the average elapsed reporting time for cultural institutions is up to a month, with some museums waiting a year or more for data. In 2017, the rise of analytics will be driven in part by a demand for more immediate gratification and a shift closer to real time data speeds. Projects will require quick turn around on proving business outcomes, placing higher emphasis on software as a service rather than bespoke software development, consumed almost entirely on the cloud. This trend will also transition the museum somewhat from fixed reports (particularly those manually generated and shared), to a higher use of live dashboards in decision forums.
  1. Articulating evidenced value
    This year, we expect to see the language of data take greater prominence in museums’ communications as a data culture grows in the wider public. Museums will benefit from additional, more timely and insightful evidence of their value to communities; see dramatic results from using data as a tool for attracting and retaining endowments and notably, are likely to experience a higher demand for data transparency from government funding authorities, with some municipalities and industry bodies looking to standardize technology tooling to support reporting flows. On a related note, we also expect to see creative examples of open data interactives and data journalism as part of digital exhibition experiences, especially from science museums.
  1. A move beyond the dashboard
    Moving on from 2016’s obsession with the dashboard and select data sources, leading institutions will begin to discuss their data strategies as an ecosystem, involving the notion of an integration hub and the possibilities for multiple analysis access methods for various data users. We will also hear more about the possibilities of analytics technology as a communication tool, plus various approaches to how insight is shared in collaborative discussion formats.
  1. Pivot from motivation to behavior
    Traditionally, visitor insights have focused on survey based segmentation by motivation. Presently, we’re seeing a shift to omnichannel data onsite and online, alongside a pivot from motivation to behavioral based studies. At a deeper level, customer journey insights centric to digital touch points are being replaced by more holistic visitor journey insights that look beyond the front door.  The focus going forward will concern understanding influences with the museum’s control alongside environmental circumstances to respond to, as levers for visitor, purchaser and member acquisition and retention. This pivot will open the long tail of a wider variety of data sources previously untapped for visitor studies and shine a spotlight on emerging key performance indicators such as net visitor value, visitor channel attribution and Net Promoter Score (NPS).
  1. Next best action
    As a result of this increased understanding through big data and analytics, cultural executives will look forward to actionable insight and expect to see measurable business value in decision making, elevating the analytics business case from cost savings to value generating. To this end, we will see museum management adopt split testing practices common in the digital realm across the analog experience – proving experimental innovation and improvements as a precursor to wider development investment.
  1. The data driven museum professional
    From a human resources perspective, discussions of digital literacy in the cultural sector will give way to data literacy, requiring technology confidence alongside statistical know how and the ability to communicate with data, as the museum gains independence from analysts and crucially transitions insight roles into data coaches rather than gatekeepers. In the museum job market, we’ll continue to see larger cultural institutions make specialist data hires, redefine traditional roles with a unique data flavor and place a greater degree of importance on data orientation in executive ranks.
  1. The rise of the machine
    Lastly, the rumblings of artificial intelligence in the cultural sector will give way to practical examples at the bleeding edge piloting the latest technology advancements. Rather than large scale dedicated technology projects, this will more likely creep in as a subtle influence on existing big data and analytics initiatives alongside other digital programs.