8. Fanbase information is the key

It is a given that for many the collection of information from a fan base is not the most sexy aspect in the world of EDM. However, this is a crucial chapter for DJs and event producers.

Estimated reading time 17 minutes

In 1958, Hans Peter Luhn coined the term Business Intelligence in his IBM-article, A Business Intelligence System. He defines business as a collection of activities that are carried out for a purpose in a broad sense, and views the business units that are involved in communication as an intelligence system.

Luhn describes intelligence as the ability to interpret the relation of facts presented in such a way that they lead to actions that result in a desired identifiable and measurable outcome; one or more objectives must be attained before a more or less fixed deadline expires. In 1989, information specialist Howard Dresner (who would become an analyst at the Gartner Group) proposed to use the concept of Business Intelligence as the catch-all phrase for concepts and methodsthat help to improve the process of business decision-making by implementing fact-based systems.

The term Business Intelligence (BI in short) is often used to describe the gathering, structuring and analysis of data in order to present these accessibly as information. This should result in knowledge and, if necessary, lead to action, such as decisions or changes in policy. The application of Business Intelligence helps to have a better understanding of the organization and its processes, and consequently of campaign results. The aim of Business Intelligence is to gain the upper hand in competition and to make the organization function at a more skillful level. Furthermore, Business Intelligence increases a companys value.

Presently, DJs and event producers will have to use data to further improve the clients or customers experience. Communication from context will be crucial. The better you understand the fan or customer as a person, the more relevant and efficient the interaction will be and the more valuable the company.

It is a given that for many the collection of information from a fan base is not the most sexy aspect in the world of EDM. Therefore, at first glance this chapter might be the least appealing to read. However, it is a crucial chapter for DJs and event producers. How to organize a platform a fan base so the collected data produce useful insights?

Three reasons for data collection

Personal contact with fans and listening to their hopes and wishes is what the music business is about these days. Fortunately, this is not hard to realize. Data no longer have to be purchased via a data broker, a company that collects data and sells it at a market price. It is easy to collect data yourself, for example via social opt-in, the large-scale collection and recording of data via email and/or text messages. It represents a vast (financial) value. Here are three reasons why the collection of data matters:

1.) Marketing and communication is changing

Just sending out messages via a small number of channels like traditional print media, television or even internet commercials is nearing its sell-by date. Multichannel and omnichannel marketing or multichannel communication is the name of the new game: various channels are used to send out a message, for instance by referring to a YouTube video in a Facebook post or on the website directing to the Facebook page.

2.) Data-analysis is available to all

New technology enables us to determine where, when and how frequently we request fan and client data; a social opt-in does the job very nicely. It is also possible to map out the online (shopping) behavior of your target audience. New technology allows you to do a comparative study and analyze online transactions. Moreover, it is possible to gain insight by analyzing queries and reviews on social media like Facebook and Twitter. Precision marketing, i.e. using known interests or the location of the fan for targeted promotional messages, will boost your success rate tremendously.

3.) It helps to play into the fans hopes and wishes as opposed to one message to all

Fans are no longer sensitive to one-way communication; they are more than just a receptacle for broadband messaging. They want to engage in a dialog. Analysis of social media conversations and interactions clarifies the wishes of the fan or client.

Dont lag behind the competition

Technological evolution compels DJs and event producers to adapt to the new times. More and more ways of connecting to a target audience are being developed, and DJs and event producers have to go along in order to stay ahead in the game. They have to keep their finger on the digital pulse and monitor the response to content, substituting failing messages for more successful ones. This state of affairs was exemplified at Eurosonic Noorderslag 2015. Students were polled on the dos and donts of online music consumption, data harvesting via the worldwide web and the willingness to pay (more) for music. The results: students appreciate technology, even when it comes to privacy issues. There is just one proviso: it should not be unnecessary or turn into a nuisance.

Business Intelligence and the incitement of communication, marketing and sales activities will have to get a greater role in the organization of the DJ or event producer. It is important to link hard and measurable data and thus create the proper context for outlining and testing the digital strategy. The fan base should be analyzed monthly or annually, depending on the volume of available data and the ambitions. Thus data will become the guide for the DJ’s or event producers marketing, communication and sales activities, or at least hint at the correct budgetary priorities.

An extensive analysis of the available information must be the first priority for the DJ and his management. Data analysis is the only next step that makes sense for, for instance, sales and marketing activities as well as booking agents, merchandisers and sponsor recruiters. Just aggregating hits in search engines, advertising and being visible to the target audience no longer suffices. Delving into data, connecting results and transforming these into a digital strategy that complements the marketing strategyits the new course the DJ and his organization should sail. It is obvious this new course requires a new mind frame. All this applies equally to event producers

EDM and the Digital Domain

Access is data

Record companies, music publishers and DJs are and will be dependent on target audiences. In the digital realm, these are smaller and more specific. Fragmentation and convergence are a threat on the one hand, however they provide new opportunities to connect to and create a bond with the very audience of the artist. Content owners such as the music business publish their content on all available platforms: print, radio, television and internet. The corresponding earning model displays a fragmentation of the sources of income. The function of data is increasingly clear. They are actually the new source of income for the music business. This impacts the business model as described in chapter 3.

For some time now it is evident that access to content is crucial. Looking at late 1990s online services such as Kazaa, LimeWire, Napster and many more, it is hard not to conclude that these services offer access to vast amounts of content and are in fact immense sources of data. All these services invoke the sense that all content (i.e. music, movies, photos and software) is available where they actually just provide access.

Access to digital content and online servicing are the keystone of future earning models for all who are involved in the exploitation of music, or, for that matter, books, daily papers and magazines. This outlook is relevant to many lines of business as well. Sales of physical products to fans, customers or aficionados will decrease drastically. Up-to-date digital fans no longer feel the need to own a hard-copy, as was de rigueur in the age of physical sound (and media) carriers. Take a closer look at portals such as Apple Music, Deezer and Spotify, but also DropBox, Google Drive and many more, and one thing catches the eye: they provide access. Access to music (or other content) replaces ownership of music (or other content) via hard-copy or in digital form. Access means user data. Data are crucial to EDMs business model.

Company value

Data sources of interest are social networks, business transactions, logbooks and journals, research reports and the findings of monitoring and analysis. Getting to work with data poses a series of issues regarding the recording, management, storage, processing and security of data. New opportunities arise, data analysis leads to ground-breaking insights. Data analysis results in added company value.

Goodwill is defined as willingness or favor. In the financial sector, goodwill stands for that part of a companys market value that is not accountable as assets or liabilities: the surplus value of a company on top of its net value. Thus viewed, goodwill represents future earnings of companies, organizations or brands; not yet expressed in the balance sheet, though present in the form of know-how, knowledge, clients, brands, human resources and the like.

The sale of (Dutch company) ID&T to (American business conglomerate) SFX constitutes a fair example of how in-house data can impact the price of a business in take-over situations. By looking at the aspects knowledgeand clientsof the concept goodwill, a new, additional value emerges; it is rooted in data. The introduction of social media seized by ID&T for the recording of all data generated by fans and followers via online interaction and conversation has obvious consequences for the valuation of companies and goodwill. SFX Entertainments valuation of ID&T clearly indicates that the data generated by fans and followers of ID&T events worldwide will add value to the organization.

One can wonder how big a deal the loss of a few data is. Does it really matter? And who will find out? However, the consequences can be disastrous. Remember the news stories on Sony Playstation and its loss of data. Users have dropped the brand and its product after worrying about privacy issues. And it does not stop there. Dissatisfied customers shared their stories, with friends, family, acquaintances and others, probably via social media. It shows how loss of data can result in a damaged image very hard to repair and subsequent financial damage. After all, the companys intellectual property is located in data. Leakage or loss of information will have serious consequences.

Business first

If we can point out one issue that has recently risen to the top of the agenda, it is the understanding that organizations, one way or the other, have to do somethingwith all the available data; both data within the organization as well as data accessible via outside sources. The latter can be used to enhance the profile of fans and clients.

Increasingly, funds are budgeted for the implementation of platforms that enable the contextualization of the data that are harvested from various and diverse sources. The companys business model (with its goals and targets) dictates the nature of the questions this platform must provide answers for. So the system has to be business-driven, not data-driven. This is important. Data for datas sake is not the future, it will lead to loss of focus and confusion. The rule of thumb for building a platform of this kind, a fan base, is business first.

Having data at ones disposal is the key. Having an insight in the current situation is one thing, however, it might be even more important to have at least some semblance of an idea of what the future will look like and how changes in the organizations strategy and policy will impact the organizations results. Data that really add value to the companys business model is not the result of harvesting and analysis, it is the data that help to formulate the companys business objectives and the strategy that will achieve these goals. How will we lead the process? What is it that we would like to know? What data do we need and how must we analyze these data?

EDM and the Digital Domain

How does data collecting work?

Data mean nothing without context. When put into context, meaningless data morph into useful information, suggesting lines of action. It can be used to conceptualize and design marketing campaigns that can be activated automatically or manually. So research what data are available, place them in the proper context so they turn into useful information and take action.

The next step is a full-grown reporting, analysis and dashboard environment. It is possible to execute more complex analyses, tap into new data sources and to link observations or phenomena that appeared to be unrelated. Insights will gain depth and become more valuable to the company. This is the process, but how does it work?

In order to turn data into information that can be used for decision-making, they must be processed via a series of operations. First of all, the data from various sources must be collated and integrated. Next step is the assessment of the data quality: do they warrant any conclusions?

When the data quality justifies further analysis, the search for patterns and links can start by retrieving the data from the database. Terms and names must be standardized, so that data from various sources can be processed as one batch. Furthermore, the information will be presented in a model. This is dedicated software, especially written for reporting and analysis purposes.

The process of improving your data utilization comprises four steps:

1.) Data collection

The first step includes the retrieval of data from various and diverse sources, the so-called data integration or data connection. Think of integrating data from systems like ERP and CRM. This step includes the link-up to outdoor data sets of, for example, ticket providers, merchandisers, music and video services, social media and mail-out lists. Data from all available sources are stored in a data warehouse.

2.) Data transformation

A data warehouse is the place where you store the data you have retrieved from various sources, including third parties. It has several functions: the data are available faster, better accessible, and more uniform. It helps to define entities like customer, turnover, etc.

Both in-house and third-party sources contribute to the data set. All data sources of the organization, think of in-house systems such as supply & delivery, accounting and CRM. Outside sources like social media and ticket providers supply additional data, that have to be integrated in the in-house data in order to produce a uniform (thus workable) data set. The transformation of diverse data sets into one unified collection of data is the second step.

3.) Data analysis

Data mining is an advanced method of data analysis. It involves complementary statistical analysis and sophisticated algorithms. It is a method of processing vast quantities of data that is used, for instance, by the meteorological office in weather forecasting and by insurance companies for risk analysis. It is important to prepare the data and make them available in a single format. This set is the source material for the analysis. Depending on the need for information, the analysis should produce practical information, and, ultimately, new insights.

4.) Presenting the information

The final step is the presentation of the information resulting from the analysis. Obviously, this can be done in a multitude of ways, depending on your needs and business practice. For instance, standardized reports are mailed out at fixed intervals. Dashboards make it possible to present in a dynamic, real time form. A series of reporting environments offer options for ad hoc info presentation and collection.

Tools

The world is more complex than it used to be. In the old days, a hard copy of a report was an export from an application; now front, middle and back offices, applications and link-ups, partners in a supply chain, social media, collaborations with ticket providers, e-commerce parties and shared service centers are all part of our daily business practice. The world is changing faster and faster, so reliable information becomes essential in order to quickly respond and adapt to new developments.

Data offer limitless options, or so it seems. It becomes easier to collect and manage data that become available via a central platform. Software for data analysis is getting more advanced in its application and easier to handle for the user. It helps to reduce time spent on data collection, so more time is available for analysis of the customer journey.

The customer journey is the route fans or clients travel in order to, for instance, access content on your website or do a purchase in your web shop. It exemplifies how fans or clients orientate, what information they use from which sources, and how they eventually select. When you know your fan or clients customer journey, you know how to service him.

In order to combine data from various different sources (clients data base, social media and web analytics), departments and suppliers have to look beyond the digital products that are their first responsibility. The customer journey of the fan or client is not a straight line from A to B. Customers use apps, websites and social channels, and switch between offline and online. All these digital tools have to be attuned to lead to a successful customer journey.

Are old-school analytic tools still viable in the current phase of digital evolution? The answer is no. DJs and event producers can no longer rely on traditional data storehouses. For more and more companies, the norm is an infrastructure that works with unambiguous definitions and fully exemplifies the customer journey. Nowadays, DJs and event producers assemble data from all channels (Google Analytics, ticket sales, merchandise sales, music services, social media, newsletter files, single sign-on modules and all other available relevant channels) and handle these in a unified fashion.

Handling in a unified fashion implies that you use unambiguous definitions, for instance for the moments of contact with a fan or client. One central dashboard displays the complete customer journey, which comprises multi-channel communication and the aggregate of moments of contact.

Traditional systems for web analytics, such as Google Analytics, are not designed to produce or contextualize raw data. It is a stand-alone service, which processes and optimizes data, resulting in a chart or graph. This speeds up the process of visualization, however part of the information is lost. This exposes two drawbacks. Firstly, the quality of the data that you want to be processed by your contextualizing platform is sub-optimal. Secondly, traditional systems are not designed for fast output. These drawbacks disqualify traditional web analytics systems for inclusion in your platform.

Layout and management

You have to focus on the following aspects regarding the layout and management of an adequate information platform.

  • Presentation
  • Manageability
  • Scalability

The presentation aspect looks at how easy and how quickly the information is available. Manageability looks at how easy it is to add new sources at affordable costs. Scalability looks at the volume of data that can be processed at fixed costs.

Setting up your information platform is not that complex anymore and, moreover, it can be done a lot cheaper than it used to be. This trend is the result of the arrival of reliable cloud services. The Platform as a Service (PaaS) concept offers options for data storage and data processing without having to manage the required hardware. Furthermore, you do not have to concern yourself with hosting the platform. Use of the platform is available at a fixed price, frequently a monthly fee.

Fanalists, is an example of a non-residential cloud platform. It stores data and processes data into useful information.

In practice

The use of data for marketing, communication or sales purposes opens up various possibilities. The necessary data will be supplied by the DJs or event producers ecosystem and even beyond. The use of tags or parameters can focus on socio-demographics, area code, or the individual. Focus on geographic tags is usually not related to an individual, but aims for a particular target group. Data enrichment with regard to the target group is generally used to improve the data set for marketing and sales activities. So what to do? The key words are: validation, enrichment, profiling, segmenting, matching, locating and decision making.

  • ValidationOne of the main problems in making contact with fans and clients is the quality of their data: are they up to date? Mutations that are not registered or recorded will quickly pollute a data set and make it obsolete. It is therefore important to safeguard the condition of the data set, it should be optimum. After all, it is the data that add value and control costs. Save money and operate more efficient by keeping the data clean, complete, accurate and up to date. Delete duplicate data, and enrich accurate data; try to complete missing data.
  • Enrichment If data are missing, it is often possible to complement (enrich) the data with information that is available via social media. Subsequently, you can start profiling.
  • ProfilingThe individual is the basis for the assembling and linking of all data that can be retrieved from the various sources: client files, newsletter files, social media, etc. This should make it possible to display all characteristics of an individual with just one click. Profiling is necessary for two reasons. Firstly, it makes it possible to compare all sorts of data. Secondly, it does not discriminate between what data sets could be useful and what not, so you will not narrow down your choice of data sets to use.
  • Segmenting There is no longer an average fan. Target groups often can be broken down in various clusters that ask for a varying approach. These can be pinpointed by way of segmenting: fans and clients are represented by easy-view charts or diagrams that break down the group into even segments.
  • MatchingThe perfect profile does not exist either, so dont define your query too narrow. For instance: when the profile of the target group reads like Female, 27 years of age, credit card, higher educated, interested in EDM and technology, it is possible that a 27-year old middle educated woman might be interesting too. It pays off to include in your search individuals that only partly match with the perfect profile.
  • LocatingIt is possible to visualize target groups for an area, say the Netherlands, and see where fans and clients are living. It can help an organization to set up an outdoor campaign, or attract fans or clients to a nearby event or festival.
  • Decision makingAn interesting insight is to what extent the fan base of real people matches with the supposedly perfect fan profile. Your fans could be females in the age bracket of 40+, not what you would have anticipated. You can apply decision trees to uncover characteristics of this type. A decision tree is a series of questions for the fan to complete. Each follow-up question is dependent on the answers to the previous questions. Applying the decision tree to the collected fan data will help you to categorize your fans. The resulting tree effectively shows the characteristics of your fans.

Summarized

Business Intelligence should be integrated in the daily business of a DJs or event producers company. It enables them to make better decisions and to search for new earning models. This can only be practical when data analysis is simple and feasible, not limited by technology.

Technology is not the starting point of data analysis. These are the people who do the analysis and the business objectives of the company. You should look for a method to collect data that fit your organization and its environment. There are various ways to store data collected from your website and social channels, and different companies use different methods. Third-party platforms are often appropriate, however, at times a do-it-yourself solution works as well, if not better.

Keep one thing in mind: your solution of choice should match with the existing infrastructure. Often, an infrastructure is capable of processing and storing data. If that is the case, it is relatively easy to extend your infrastructure. Next comes the choice between data hosting on your infrastructure or via a cloud service. The latter option is preferable, since it allows you to access the information wherever you are (and DJs often do their bit of globetrotting).

Use whatever you need in terms and analytics (tools), and add whatever is missing, step by step. The adoption will increase when your choice is implemented in the existing environment. It is often not necessary and even needless to build a new infrastructure. It makes more sense to invest in a data warehouse (the location of data storage: in the cloud); in data mining and the processing of raw data into useful information for reports; in dashboards and publishing tools.

The use of data for marketing, communication or sales purposes offers various possibilities. The required data are sourced from the DJs or event producers ecosystem and beyond. Used in this way, the data should be: validated, enriched, profiled, segmented, matched, located and supporting in the process of decision making. It creates the proper context and significantly increases the possibilities of relevance, reach, interaction and transaction.

After you have outlined the profile of your fans and clients, it is possible to engage in meaningful interactions and become relevant (again). The challenge is to work out the proper context by means of automated analyses. If adequately executed, it will avert, for instance, your fans and clients becoming annoyed by unseemly messages or content. Annoyance can undo the interaction and its value, the same as relevance can create value.

The data set of a DJ or an event producer is not a static entity, it is a dynamic environment. It is not a product, it is a process. It needs maintenance. It is open to continual optimization. The daily use of data requires the organization to function as an analytical company that views data as an asset, and considers analysis to be a core competition. The key to success is to organize the handling of data efficiently and effectively, and to select the right people within the organization who can improve this competence continually.

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