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9th April 2019 Rebecca Moore

Personalised vs Basic #DigiLab

Danielle McLoughlin of Hull Truck Theatre talks us through her first experiment on Digital Lab and identifies four key challenges she has faced. 

I applied for a place on the CultureHive Digital Lab in the hope of gaining additional knowledge and support to develop the ideas and experiments that I wanted to implement at Hull Truck Theatre. I knew that the opportunity to work with a mentor and other fellows would be invaluable and allow for lots of interesting, cross-departmental discussions about best digital practices, which would then help contribute to the company’s longer term digital goals.

I had my first call with my mentor, Tom, and we discussed the various experiments I wanted to work on throughout the course. We talked about making sure that my experiment/s had clear aims and could be measured, and about making sure that each experiment contained limited variables so that we could analyse the outcomes effectively, getting meaningful results.

Tom really took me back to school with all of his talk about variables, action reflection cycles and methods of measurability, and following our conversation I had a much clearer idea of what my experimental goals were, and I was prepared to adapt to new ways of working.

Experiment Number 1

Goal: To encourage repeat attendance from customers, within an hour’s drive time, who booked tickets in 2017 (Hull City of Culture year) and have not returned since.

Experiment: To create an Oliver Twist (Christmas 2018) email split test and find out which type (Personalised vs Basic ‘What’s On’) encourages the most interaction and conversions.

Part One

  1. Extract all customers, within an hour’s drive time, who attended the theatre in 2017 but not since.
  2. Randomise these customers and separate in to four Groups (A, B, C, D) ensuring that there is an equal number of customers who booked for last years Christmas show, in each group.
  3. Email GROUP A a general Oliver Twist e-shot, including image, synopsis, dates, times and general booking information.
  4. Email GROUP B a personalised Oliver Twist e-shot, thanking them for being part of our ‘Year of Exceptional Drama’ and contributing to the City of Culture events, plus the above details.
  5. Analyse the interaction and conversions from both emails and make a conclusion about which email content was most successful.
  6. Use the ‘successful’ e-shot (let’s call this ‘e-shot X’) to then generate the next step of the experiment.

Part Two

  1. Email GROUP C with e-shot X.
  2. Email Group D with e-shot X, adding the show trailer, an animation or other visually engaging content.
  3. Analyse the interaction and conversions from both emails and make a conclusion about which email content was most successful.
  4. Use the ‘successful’ e-shot (let’s call this ‘e-shot Y’) to then inform how we might engage with lapsing bookers, digitally, in the future.

Following this my intention would be to carry out a similar experiment for out of town visitors that attended in 2017 but have not been back since. In terms of content this might be a simple show e-shot vs an e-shot with additional visitor information such as hotel links, packages, etc.

There have been numerous hurdles during the early stages of this experiment but whilst they have been challenging to overcome they have raised some valuable discussion points and issues that need to be addressed.

Challenge 1
Once I had planned my experiment I realised that to be able to analyse customer engagement effectively I would need to teach myself to use Google Analytics. I took part in the free online Google Analytics Academy and picked up the basics quickly. I also researched Google Analytics Tag Manager, as Tom said this would be useful and it will allow me to track which e-mail my web visitors had been referred from.

Challenge 2
I was eager to start setting up some filters and goals, on the Hull Truck Theatre live Google Analytics site, but the theatre didn’t have admin rights to its own Google Analytics account which limited the functions I could use.

Challenge 3 
The company who had admin rights for our account was an old OLD web host, who we no longer deal with and I needed to contact them to try and get admin rights. Luckily, we do still have a loose relationship with our old web host and he was extremely happy to work with us to resolve the issue. It took some discussion between myself, the old web host and our new web host (who we are just in the process of switching to – throwing another spanner in the works!) to find a solution but we now have admin rights to our Google Analytics account.

Challenge 4
When attempting to create a tracking tag so that I could see how many people converted and purchased tickets for Oliver Twist, I realised that the last seven pages of our checkout process have the same URI, hulltruck.co.uk/checkout. This means that I can’t tell whether someone fully checked out or dropped off at the donation, delivery, billing or summary pages. I am now in conversation with our ticketing provider, who deals with the iframes in question, to see if we can make these URI’s more unique and thus accurately track the customer journey.

 

Image courtesy of Hull Truck. Theatre. Oliver Twist at Hull Truck Theatre, Flo Wilson, Samuel Edward-Cook and Lauryn Redding. Photo by Sam Taylor.

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