Digital communication became more and more personalized during the last decade. Cultural organizations are in danger of loosing the bond to their audience if they cannot adapt.
The omnipresence of the (mobile) internet on smartphones has revolutionised communication over the past 10 years - we are now constantly online and connected. Yet it was not long ago when most visitors to orchestras and opera houses only checked their emails twice a week. Now, social networks like Facebook, Instagram and YouTube offer customised feeds and more personalised content than anyone can read, listen to or watch. And we have become accustomed to these uniquely tailored online experiences based on what we like and want to see.
Cultural institutions have not yet created anything comparable, nor have they been able to gain any meaningful additional insights into the interests of their visitors during this "decade of the feed". So far, no organiser, theatre, opera house or orchestra knows enough about its audience to be able to offer them personalised content.
Why is that and how can it be changed?
To solve the problem, we must first accept that it exists. Because cultural institutions simply know too little about the interests and motivations of their visitors to attend a certain concert. Perhaps in general, but not very specifically: Why do they buy a ticket for the concert with Beethoven's 3rd Symphony, but not for the one with Beethoven's 4th? It is true that surveys and market research have a long tradition in cultural institutions. However, no digital platform can create personalised content offers based on annual user surveys. Traditional market research does not help in offering digital, targeted content.
The fact is that cultural institutions have indicators and theories, and many individual team members know the reasons for a general visiting behaviour of their audience, but there is no concrete data about it. Thus, the existing knowledge cannot be used to display interest-based concert recommendations for individual visitors, nor can it be used to tailor online experiences to each visitor.
Furthermore, 18 months of pandemic have led to tectonic shifts in existing habits. Visitors have reorganised their lives, often filling the gaps with other activities.There is also a lot of catching up to do: people finally meet up with friends and family again, go on holidays, weekend trips or go to their favourite restaurant again. This means that competition has increased many times over, not only for the visitors' wallets, but especially for their time.
If the last decade was about digital communication, the next decade is about interest-based, personalised communication.
Winning back previous customers not just once, but consistently, could become hard work for cultural organisations. Knowing the original motivations for the visit and understanding the interest is essential. If the last decade was about digital communication, the next decade is about interest-based, personalised communication.
Visitor surveys typical of cultural institutions tend to have a large proportion of socio-demographic questions, discuss how guests found out about their organisation, how they got to the venue, or refer to anything else not related to the actual concert or performance. Because cultural institutions tend to focus too much on WHO comes through the door, not WHY they come. When in fact that is the information that is truly valuable. Not only on the superficial level of "music", "atmosphere" or "going out", but on a level of detail that distinguishes each individual concert from all others and describes it in its uniqueness with data.
The question of why a visitor bought a ticket for a concert with Beethoven's 3rd Symphony but not for Beethoven's 4th Symphony cannot be answered by the fact that this visitor is female, 45 years old and lives in the postcode 10119. However, a look at the concert attended itself and the music-historical significance of Beethoven's Third might help: In our example, the concert was conducted by a young and aspiring conductor and Beethoven's Third Symphony represents the beginning of a new era of symphonies. With this understanding, we can first establish that it is not Beethoven but the conductor who is the relevant feature, and then look for a suitable next event for this customer. Suggesting more and more Beethoven concerts will not add value to the customer and will create an unpleasant experience. Better recommendations could include programmes that feature category-defining works and emerging artists. Interest-based customer insights provide this level of understanding - automatically.
#sidenote: Income is another example of a useless segmentation metric. True, ticket prices sometimes limit access for visitors. But targeting people with high incomes for an opera performance because of high ticket prices misses the point. This can be observed especially in music festivals. The audience is predominantly from the age group between 20 and 30 and does not necessarily belong to the high-income groups. But they spend hundreds of euros on tickets, travel, accommodation and drinks. To extend the argument to the opera mentioned above: Perhaps one can predict whether someone is likely to attend the opera based on income or age, but more insightful analysis shows who wants to experience a particular work or will attend a particular performance, not "opera" in general.
Marketers will counter that persona approaches and segmentation tactics incorporate this idea. But there is hardly a company or organisation (from Bundesliga clubs to world-leading opera houses) that can deal with more than 5-7 personas. And then there is the challenge of varying tastes and interests. No customer is only interested in a certain genre, type of artist or aesthetic. Traditional methods of customer segmentation cannot deal with this diversity. In most cases, the interests of customers are only inadequately mapped because a reduction of characteristics is necessary to ensure a manageable number of customer clusters. Since one can have only one age but several interests, socio-demographic characteristics always end up dominating the customer clusters or personas.
Discover solutions in Part 2: Interest-based customer segmentation is the future