Knowing the Score: Repertoire Scoring and Segmentation
A simple repertoire scoring system is far more effective than a crystal ball for predicting the popularity of a programme, setting budgets and segmenting an audience.
What do Beethoven’s Fifth Symphony, Shakespeare’s Romeo and Juliet and Van Gogh’ Sunflowers all have in common? They all rank among the greatest works of art with a strong appeal for many people. On the other hand, what about Berwald’s Sinfonie singulière, Montrose’s Cleansing the Isle and Marca-Relli’s collage action paintings? Now we’re talking about obscure work, which only a handful of people would probably have heard of.
These are extremes, so while it’s easy to acknowledge the different attractiveness in these examples, assessing the appeal of everything in between is more difficult. Even within the repertoire of a single composer like Mozart there is a range: The Magic Flute has a wide appeal, while La Clemenza di Tito less so.
And that’s not to mention the impact of a star singer or a famous director. The art of repertoire scoring relies on turning the subjectivity of artistic appeal into an objective score.
Range of applications
It’s all well and good scoring your repertoire, but it’s what you do with the results that matters. Our clients use repertoire scoring in a wide range of applications:
- Programming: The British Film Institute uses scores to inform decisions about how long to screen different films for, in which size space, and the price.
- Audience segmentation and marketing: The City of Birmingham Symphony Orchestra creates an average score for each customer based on their booking behavior, identifying whether they are risk-takers or comfort-seekers. They then tailor marketing messages accordingly. Read more about behavioral segmentation at the CBSO here.
- Forecasting and budgeting: London Symphony Orchestra creates sales and income targets by using past concerts with the same scores as future ones. Read more about how LSO sell spare inventory here.
- Variable and dynamic pricing: Los Angeles Philharmonic decides on its single ticket prices and dynamic pricing increments using a combination of repertoire score and subscription sales. Read more about read more about performance coding at LA Phil here.
- Subscription: Lyric Opera of Chicago uses scoring to ensure its subscription packages have a similar appeal.
Approaches to repertoire scoring
There are two key aspects to repertoire scoring:
- Identifying the different components that have an impact on overall appeal.
- Scoring these elements, from the perspective of your audience.
Seattle Opera splits each performance into five components: Title popularity; Composer popularity; Singer(s) popularity; Rarity; and ‘Buzz’ factor. These are scored independently by staff from marketing, programming and ticketing. The scores are then combined to create an overall score per performance ranging from 1 (limited appeal) to 7 (wide appeal).
In scoring, people are instructed to consider the appeal to the majority of customers, rather than opera buffs or opera newbies – customers who might know Madame Butterfly, but haven’t necessarily heard of The Girl of The Golden West.
The University Musical Society (UMS), which presents music, dance and theatre on the campus of the University of Michigan, offers another example of applying scores to audiences. It thinks about the adventurousness of customers. It combines scores for nine different criteria, including subject matter and unconventionality of format, for each performance. It then applies an average score to each customer based on their purchase history, using the Segmentation Engine.
Repertoire scoring in the Segmentation Engine
The Segmentation Engine includes functionality to store repertoire scores against performances, and then see customers’ aggregated scores. When configuring your scoring system, in addition to the numeric score, you can also write a description of that score to remind you that e.g. you used a score of 5 to mean ‘wide appeal’ and a score of 1 for ‘limited appeal’. Your range of numbers can be as wide as you like.
Scores are then applied to customers on your database to provide three behavioral variables: an average repertoire score for each customer, from the performances that customer has attended, as well as their minimum and maximum score. You can then cohort (group) the results (grouping together, for example, all customers with an average score above 4), creating segments for customers who are more likely to stick with the popular repertoire, those with a higher appetite for risk and those who go to everything.
UMS use the scores in the Segmentation Engine to divide customers into three categories: ‘Adventurous Souls’, who mostly attend challenging works; ‘Adventure Averse’, who go to things like Handel’s Messiah; and ‘Adventure Curious’, who are somewhere in between. It also uses the maximum and minimum scores to see which customers ever attend the extremes of the program, enabling it to improve its targeting. It is also developing an attitudinal survey to overlay against customer behavior. By identifying any mismatches – a customer self-identifying as an adventurer but with behavior suggesting otherwise – it can focus audience development work on these customers.
When implementing repertoire scoring, organisations have found it’s a great way of bringing together staff from different departments to have joined-up conversations. Are our forecasts and targets realistic? Is there enough popular work to bring in new audiences? Is there enough of a market for the risky repertoire this year?
Repertoire scoring offers a way to get everyone talking with a shared language about programming and audiences.