Openstage is a platform that enables artists and fans to better find each other and gives artists in-depth insights into fan behaviour, location and demand with one simple dashboard. Fans place markers for their favourite artists to tell the artists where they want to see them and connect with them so that fans can be ahead of the pack for all announcements and offers such as tickets, special pop up events or street team activations. Artists then have the ability to super-serve their most engaged fans and gain impactful results by making data-driven decisions.
Business Type: Software, Online Platform
Openstage’s clients are artists, specifically musicians (either independent musicians or band managers) who are planning their tours and want to engage with their fans better. In order to continue growing, Openstage’s sales team needs to onboard more artists to their platform, however, the artists that have higher chances of joining Openstage’s platform are in a particular phase, for example, those artists who are already trying to plan their tours are more likely to join, while those artists who just finished their tours are less likely to join. Manually checking all social media to check artists’ status, requires a lot of work because status is changing quickly, however, reaching out to all artists are also time-consuming and has less chance of success.
Openstage has a subscription plan for artists, and one of the main targets for Openstage is to increase revenues, therefore, they need to onboard more artists. In order to attract more artists to pay their subscription plan, Openstage needs to create more added values for the artists, specifically those artists that cannot easily do it themselves. Openstage has the platform that enables fans to drop markers to locations that they want the artist to visit.
We first conducted an assessment of the client’s business, then we also met with the sales team and executives to understand the existing sales workflow and what potential solutions would help in enhancing the process. In addition, we also held brainstorm sessions with Openstage to identify more potential added values for the artists, where could we get the data and how it could add value to both the artists and the client.
Based on the results of the business assessment and some potential features, we identified several social network data sources that could generate useful insights for both Openstage and the artists. With these, we assessed the technical feasibility of extracting relevant insights, built web crawlers, API connectors and conducted exploratory analysis on how these data sets would perform and whether the perceived added functions could be achieved.
In order to create the big picture for the development of the AI talent spotter platform and to make sure that the goals and objectives are well aligned with the core business objectives, our team prepared a roadmap for the development of an AI platform. The roadmap consists of multiple phases, where each phase delivered a set of features to the platform based on prioritisation consistent with business their objectives. Each phase was assessed in terms of technical requirements, as well as time and resources to allow Openstage to plan the project.
We developed crawlers and scrapers to gather relevant information from multiple sources. These data sources included extracting lists of artists, musicians, bands, etc. generating a list of potential artists from external sources. Next, we matched other data sources to find related Musicians/Bands etc and developed a Graph API call to extract the artist related social signals information (likes, loves, events, posts, replies etc).
From independent variables extracted as social signals, we calculated dependent measurements such as rate of change of a quantity, change in rate of change, absolute/relative change, to reflect the social behaviour of an artist. We developed a cross-artist comparison methodology to calculate Fame Score, Growth Score and Engagement Score, and ultimately the Openstage Readiness Score based on the acquired data. In order to provide more insights and added value to the artists, we developed a methodology to calculate event coverage and fan satisfaction per country and used these features to calculate ticket sales opportunity and virtual queuing opportunity for various geographical regions. We also integrated sentiment analysis tools and detected sentiment coming from artists’ own posts, tagged posts, fan posts and other posts relevant for the artist, and developed a methodology for identification of super fans and influencers.
One of the main features empowering the sales team is a several page PDF export of artist’s data in form of graphs and numerical values. The PDF document shows all insights for a selected artist including trends, scores, super fans, influencers, sentiment, peer comparison, geographical ticket sales opportunity, and more. Ultimately it allows the sales team to print a report and bring it to a meeting with an artist or manager.
Openstage’s sales process is transformed and empowered with efficiency and a higher hit rate. With this tool, Openstage’s sales team now know which artists to target next and have tangible value to show to new artists immediately by just opening the tool and gathering some basic artist details to start the AI analysis.
This app makes fan interaction, sentiment, behaviour and trends all in one place, helping artists connect with their fans better, for example, reward fans for their engagement in building artists a bigger audience and sharing your content, understand who is the artist’s most engaged fans, so artists can give them the superfan experience they deserve.
Note: Openstage and the related IP and technologies are proprietary to Openstageit Limited, if you are interested in knowing more about Openstage and their services and products, please feel free to email: email@example.com
We help OpenStage to build an AI platform to enhance their sales process and spot new talents from social network data through data sources centralisation, data analytics and statistical models development and sales report autogeneration, so their sales team know who to target and can show concrete values to onboard artists and artists have more understanding in their fan and engage with them deeper.