Overview of Behavior Based Fan Insight

IBM® Behavior Based Fan Insight is prebuilt solution that provides a 360-degree view of your fans. By understanding fan behavior and using fan segmentation and analysis, you can increase ticket sales, and increase revenue from concessions and retail sources.

Information associated with fan behavior can provide a lot of value if insights from that data can be quickly and accurately attained. Behavior Based Fan Insight enables sports teams, concerts, and other live event venues to provide their fans with more personalized communications by using a comprehensive a suite of advanced data integration, analytical, and decision-making capabilities.

What makes Behavior Based Fan Insight different?

  • Behavior Based Fan Insight analyzes unstructured data such as social media, behavioral data, email, chat, audio, video, reviews, location data, and acceleration data.
  • Behavior Based Fan Insight lets you understand how contextual content can impact engagement.
  • Behavior Based Fan Insight provides increased information transparency between departments.
  • Behavior Based Fan Insight helps you to understand content preferences so that you can customize promotions.
  • Behavior Based Fan Insight provides real-time visibility into the value of your promotions.
  • Behavior Based Fan Insight provides cognitive campaign information to help you in the following areas:
    • Predicting campaign outcomes before they occur.
    • Measuring win rate and revenue predictions against target and actual figures.
    • Creating personalized campaigns that predict a client's propensity to spend, finding suitable offers based on their responses to past offers, and predicting the optimum time to contact them.
    • Self-learning and optimizing in near real-time based on client propensity scores and campaign responses.
  • Behavior Based Fan Insight provides a daily ranked list of recommended products for clients based on their current budget.

    It also shows projected revenue for products by providing lists of potential buyers. For previous clients of a product, it assumes their spend is equal to the value spent in the last season. For new clients, it assumes their spend is equal to the average value spent by previous buyers (weighted by a predicted rating).

  • Behavior Based Fan Insight provides social media and news media analytics to help you in the following areas:
    • Finding new prospects by using social media to understand your broader reach fan base, and targeting them with relevant offers.
    • Improving customer engagement and campaign effectiveness by understanding key topics, themes, and emotions, and incorporating them into your promotions.
    • Improving brand reputation and reducing customer turnover by understanding influencers and engaging with them directly.

      Often, social media is the first place where customers express their emotions about a product. Behavior Based Fan Insight can improve your brand perception by using social media to better interact with influencers to understand topics and themes that are relevant to them. Also, it can proactively track and address negative brand emotions.

    • Understanding the competitive landscape by using social media data to benchmark offers, promotions and messaging against your competitors. Behavior Based Fan Insight can optimize the offers and promotions to suit your clients.

What questions does Behavior Based Fan Insight answer?

How can we better understand and target our fans and customers?

What are the indicators by which we can measure our customer outreach?

Who are the right customers for targeted efforts, when and how do we interact with them effectively?

How far in advance do customers buy tickets before the event itself, and where and how do they buy tickets?

What are the different behavioral groups for casual buyers compared to season seat owners?

What are the ticket purchase transaction traits for different types of customers? Day of week? Time of event? Opponent? Channel of purchase?

What is the ticket purchase history of customers and what are the changes in their ticket purchasing behavior?

Which fans visit most and least often?

How do fans, season pass holders, and walk up buyers respond to special offers?