ASK AN EXPERT
Kath Hudson, journalist, Attractions Management
Can data analytics benefi t your attraction?
Could fi nding out that your customers buy online tickets in the middle of the night improve your revenue? Absolutely, say our experts – data is gold
D B
ata analytics allows operators to mine vital information about their customers, leading to decisions which boost the bottom line and improve customer experience.
Already well established in the retail and sports industries, data analytics is just starting to get a foothold in the attractions industry. It can help you fi nd out who your customers are, their habits, what they like and don’t like; it can even help operators predict how many staff to book according to the weather forecast.
Understanding customer behaviour can help attractions make more intelligent decisions This data can help operators develop
more effi cient, better targeted and more cost effective marketing campaigns. The data can be used to offer customer experiences which are attuned to them.
But is there a downside? To get the
most out of the system you need to be strategic or you'll drown in information. We asked the experts about the rewards and potential pitfalls of big data.
JOHN LUCAS
Director of Solutions Delivery Avnet Services
efore embarking on data analytics, attractions must decide, at a
strategic level, what they want to achieve for the business. If you jump in feet fi rst, you can drown in information, so it’s important to refi ne the search to two or three key goals. Most attractions face the
same challenges – usually an inability to see basic information, like who's visiting and their concessions data. Getting a near real-time view of who’s coming and what they’re spending their money on will help an attraction shape its marketing.
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other people who matched that criteria and emailed them. For a fraction of the cost of the email campaign we achieved a 10 to 12 per cent capture rate. Data analytics boosted
Most attractions use
blanket campaigns from a purchased list to attract new members. They'd expect a 1.8 to 2 per cent capture rate. At Cincinnati Zoo, rather than a carpet-bomb email, we did analytics on existing members, profi ling them and asking how many children they had and how many cars they owned, for example. Then we identifi ed
profi ts at Cincinnati Zoo by identifying a market for ice cream in the morning. More than $2,000 (£1,312, €1,750) was taken at one outlet in an hour. In one year, food sales increased by 25 per cent. With data analytics, it's
like going from blind to 20:20 vision, but it can be overwhelming. Attractions must evolve from being reactive to proactive, which means re-training staff. We usually provide this role and support for up to six months. After the initial dramatic
improvements the company evolves from reporting to true
Read Attractions Management online
attractionsmanagement.com/digital
analysis, asking more complex questions, such as: based on Sunday's weather forecast, how many staff will we need? Then, instead of looking
backwards, operators can start using predictive analytics, so they move from the past to the future. This evolution takes one to two years. Then they start using it in other departments, such as how to save on electricity. Cultural attractions have only discovered data analytics in the past two years. Retail is leading in this area. The next stage is to get closer to understanding the end user in order to improve engagement and become more personalised with marketing.
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AM 1 2015 ©Cybertrek 2015
PHOTO: SHUTTERSTOCK/MINERVA STUDIO
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