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1 © WolfBrown 2009 All Rights Reserved
2 Knowing Me, Knowing You Emerging Practices in Arts Consumer Segmentation Alan Brown, Principal, WolfBrown San Francisco, USA
3 © WolfBrown 2009 All Rights Reserved Agenda The backdrop: increasing diversity Introduction to customer segmentation General market models - Arts typologies New customer models in the arts - Prospect models - Behavioral customer models - Attitudinal customer models Lessons learned thus far Next steps – a vision for the future
4 © WolfBrown 2009 All Rights Reserved
5 © WolfBrown 2009 All Rights Reserved The Backdrop: Increasing diversity within the audience (and community) Fragmentation and diversification of cultural tastes, especially music New frontiers of digital consumption The critical role of social context in driving attendance Expectation that all types of leisure experiences can be customized Demand for shorter, more intense, more convenient experiences More value attached to setting and format Demand for more interpretive assistance
6 © WolfBrown 2009 All Rights Reserved What is customer segmentation?
7 © WolfBrown 2009 All Rights Reserved Definition Customer Segmentation is the subdivision of a market into discrete customer groups that share similar characteristics.
8 © WolfBrown 2009 All Rights Reserved In the commercial world, businesses use customer segmentation to… Prioritize new product development efforts Develop customized marketing programs (targeting) Choose specific product features (packaging) Establish appropriate service options Design an optimal distribution strategy (sales channel) Determine appropriate product pricing Source: Bain & Co. website
9 © WolfBrown 2009 All Rights Reserved Types of Segmentation Models Demographic models (1950s - now) Geodemographic models (Prizm, Mosaic) Product-specific market models - New ACE model of all U.K. adults based on their level and nature of arts engagement Prospect models for a specific product or category - Classical music prospect model (Knight Foundation, 2002) Institution-specific customer models - Major University Presenters - Philadelphia Orchestra - Steppenwolf Theatre Company - Welsh National Opera
10 © WolfBrown 2009 All Rights Reserved Many arts groups do some customer modeling on a behavioral basis… Usually for direct mail or telemarketing purposes Predictive models are based on past purchase behavior - Donor-subscribers - Subscribers/series buyers - Dance buyers, classical music buyers, family buyers etc. - Single-ticket buyers - More sophisticated response models
11 © WolfBrown 2009 All Rights Reserved … but attitudes, beliefs, self-perceptions and values drive purchase behaviors Coming to Concurrence: Addressable Attitudes and the New Model for Marketing Productivity - By J. Walker Smith, Ann Clurman and Craig Wood
12 © WolfBrown 2009 All Rights Reserved General Population Model for Arts Attendance and Participation (Arts Council England)
13 © WolfBrown 2009 All Rights Reserved New ACE Model
14 © WolfBrown 2009 All Rights Reserved Traditional Culture Vultures (4%)
15 © WolfBrown 2009 All Rights Reserved Prospect Models: Classical Music Consumer Segmentation Study (Audience Insight, 2002)
16 © WolfBrown 2009 All Rights Reserved Prospect Model based on Relationship with the Art Form: Input Variables # of types of concerts attended over the past year (pops, classical, chamber, etc.) Lifetime history attending different types of classical music concerts Frequency of consumption via radio Frequency of consumption via recordings Level of knowledge about classical music (self-reported) Desire to learn more about classical music Critical vs. casual listener (self-defined) Social context of attendance
17 © WolfBrown 2009 All Rights Reserved Prospect Model based on Relationship with the Art Form
18 © WolfBrown 2009 All Rights Reserved Prospect Model based on Relationship with the Local Orchestra: Input Variables Ever attended a concert by the orchestra Ever subscribed Ever personally bought tickets Recency of last concert attendance Frequency of current attendance If friends or family members attend Attitude about future attendance
19 © WolfBrown 2009 All Rights Reserved Prospect Model based on Relationship with the Local Orchestra
20 © WolfBrown 2009 All Rights Reserved Integrated Prospect Model
21 © WolfBrown 2009 All Rights Reserved Ticket Buyer Model: Major University Presenters (2007)
22 © WolfBrown 2009 All Rights Reserved Online Survey Methodology Protocol builds on qualitative data from 195 interviews 51,541 invitations sent to 14 lists 7,645 responses received (~15% response) Lengthy survey (about 15 minutes to complete) Aggressive use of incentives Survey data matched to purchase data through address Acknowledge bias from self-selection and bias from online administration
23 © WolfBrown 2009 All Rights Reserved Ticket Buyer Model: Input Variables Core values (13 inner-directed, 9 outer-directed) - e.g. Rejecting authority and making your own rules Cultural attitudes (e.g, interest in specific cultures) Preference levels for 27 types of performances Appetite for educational content Price sensitivity Social context of attendance Political and religious beliefs Innate intelligences (Howard Gardners model)
24 © WolfBrown 2009 All Rights Reserved Analysis Approach: Cluster Analysis Different combinations of variables were tried Segments are designed to be as different as possible Data on Gardners intelligences are intuitive and useful Very multi-dimensional model Driven by core values, cultural attitudes, preferences and tastes - NOT driven by demographics or purchase behaviors
25 © WolfBrown 2009 All Rights Reserved Purchase behaviors paint an incomplete picture of preferences
26 © WolfBrown 2009 All Rights Reserved Overview of the Ticket Buyer Model: Ordered by Risk Tolerance
27 © WolfBrown 2009 All Rights Reserved 1. Mavericks Fearless, values-driven consumers Core value is challenging authority Thought leaders with existential intelligence Primary attraction is to linguistic art forms - Fantasy-seeking theatre-goers About six in ten are students, many are artists Quintessentially adventurous - Risk for risks sake Very price sensitive Most attend with friends, but also not afraid to attend alone
28 © WolfBrown 2009 All Rights Reserved 3. Remixers Urban arts omnivores - Love that art can be digitized, remixed and sampled Culturally-directed - Strong sense of their own cultural roots - High interest in specific cultures Preference for contemporary art forms, not classical - Healthy appetite for new work by living artists - Multiple intelligences Socially-driven, most likely to be Initiators Embrace technology Younger, but not students
29 © WolfBrown 2009 All Rights Reserved 4. Diversity Seekers Most outer-directed of all segments - Driven by a need to understand the world and their place in it - Sense of duty to mankind, commitment to social justice Most emotionally reflective of all segments - Need and ability to empathize with others High preference for world/folk music and dance Naturalistic intelligence Not into urban culture 80% female, strong nurturing instinct Likely to attend with children
30 © WolfBrown 2009 All Rights Reserved 10. Serenity Seekers Take comfort in the familiar, do not want to be challenged - 90% prefer a sure choice Desire a peaceful, calming experience - Not looking for emotional intensity High preference for symphonic music, chamber music - Little appetite for new works Attracted to authenticity and historical accuracy Tend to be males, retired, age 65+ Attend with spouse Conservative political views
31 © WolfBrown 2009 All Rights Reserved Donor Model: Major University Presenters (2007)
32 © WolfBrown 2009 All Rights Reserved Five Segment Donor Model, Based on Motivations for Giving
33 © WolfBrown 2009 All Rights Reserved Institution-Specific Attitudinal Customer Models: The Philadelphia Orchestra
34 © WolfBrown 2009 All Rights Reserved Philadelphia Orchestra Ticket Buyer Model: Input Variables Musical tastes: eclectic vs. classical-focused Knowledge level about classical music Appetite for new works by living composers Preferences for different concert formats Motivations for attending Influence of purchase decision factors Demographics and purchase behaviors were used only as descriptive variables, not segmentation variables
35 © WolfBrown 2009 All Rights Reserved Four-Segment Customer Model
36 © WolfBrown 2009 All Rights Reserved Three out of four segments prefer a format with brief introductions from the stage.
37 © WolfBrown 2009 All Rights Reserved Three out of four segments prefer a format with brief introductions from the stage.
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44 © WolfBrown 2009 All Rights Reserved Institution-Specific Attitudinal Customer Models: Steppenwolf
45 © WolfBrown 2009 All Rights Reserved Steppenwolf Customer Model Motivated by a desire to more deeply engage single-ticket buyers - Research supported by Wallace Foundation Survey probes knowledge and background in theatre, attitudes about risk, etc. A major focus on how people engage with the art form - Before shows, after shows
46 © WolfBrown 2009 All Rights Reserved Five Segment Customer Model
47 © WolfBrown 2009 All Rights Reserved Progressive Theatre Geeks (19%) Highest self-described knowledge level of theatre Most likely to be influenced by a critics review Most likely of all segments to be Multiple STBs In regards to the five engagement typologies, they are most likely of all segments to be Actors and Bloggers Shortest planning horizon of all segments (55% reporting they plan a week or less in advance) Strong skew towards males Many are found within the audience for visiting companies (27%)
48 © WolfBrown 2009 All Rights Reserved Engagement Questions How often do you do any of the following preparatory activities? - Read the play in advance of attending - Read a review of a production you are going to see - Seek out information about the play online - Attend pre-performance talks/lectures - Read Steppenwolfs Backstage magazine - Read program notes before curtain - Discuss an upcoming play with friends whove already seen it
49 © WolfBrown 2009 All Rights Reserved Engagement Questions How often do you do any of the following follow-up activities after a performance? - Talk about the play on the way home or over drinks or dinner - Stay afterwards for post-performance discussions - Discuss the play with others over the ensuing days and weeks - Read a review of the play - React to the play in an online blog or forum - Find out more about the cast, director, or production team
50 © WolfBrown 2009 All Rights Reserved Five engagement modalities overlap Readers (94%) Talkers (86%) Bloggers (26%) Listeners (18%) Actors (12%)
51 © WolfBrown 2009 All Rights Reserved Tactical Implementation: Scaling Up the Model
52 © WolfBrown 2009 All Rights Reserved Next Steps: Commitment to Tactical Implementation – The Vision Revise the segmentation protocol Add other, actionable data elements Design a new marketing data warehouse - TRG eMerge web-based marketing database - New module of TStats/Tessitura Survey the entire database Survey new buyers continuously Use the data on a daily basis for targeting offers and information
53 © WolfBrown 2009 All Rights Reserved Lessons Learned (So Far)
54 © WolfBrown 2009 All Rights Reserved Negative Indicators No up front discussion about why we need a model, how well use it - Research-phobia among artistic staff Belief that theres no point in segmenting customers because there arent enough marketing resources to do targeting Surly ad agency Disconnect between marketing and programming - No continuity of product for different segments - No possibility of aligning product/packaging for different segments
55 © WolfBrown 2009 All Rights Reserved Positive Indicators Entire leadership team is involved in defining the model Desire to align audience and programs Embracing taste diversity in the audience Valuing the full range of intrinsic impacts, from social to intellectual Willingness to adopt a new, common language to describe audiences - Allow results to infuse long-term thinking about marketing, development, programming, education
56 © WolfBrown 2009 All Rights Reserved
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