IntroductionThe IBM Behavior Based Fan Insight solution enables sports teams and live event venues to personalize their communications, improve experiences, and increase ticket sales and overall revenues.accessibilitysamplesdocumentationAudience This guide is for users of the Behavior Based Fan Insight solution. It describes the insight and analysis available from the Behavior Based Fan Insight reports that you can access in the cloud. Finding information To find product documentation on the web, including all translated documentation, access IBM Knowledge Center (www.ibm.com/support/knowledgecenter/SSNN4U_1.0.0).Accessibility features Accessibility features help users who have a physical disability, such as restricted mobility or limited vision, to use information technology products. For information about the commitment that IBM has to accessibility, see the IBM Accessibility Center (www.ibm.com/able). Behavior Based Fan Insight HTML documentation has accessibility features. PDF documents are supplemental and, as such, include no added accessibility features.Forward-looking statements This documentation describes the current functionality of the product. References to items that are not currently available may be included. No implication of any future availability should be inferred. Any such references are not a commitment, promise, or legal obligation to deliver any material, code, or functionality. The development, release, and timing of features or functionality remain at the sole discretion of IBM.Samples disclaimer Sample files may contain fictional data manually or machine generated, factual data compiled from academic or public sources, or data used with permission of the copyright holder, for use as sample data to develop sample applications. Product names referenced may be the trademarks of their respective owners. Unauthorized duplication is prohibited.

Introduction

The IBM Behavior Based Fan Insight solution enables sports teams and live event venues to personalize their communications, improve experiences, and increase ticket sales and overall revenues.

Audience

This guide is for users of the Behavior Based Fan Insight solution. It describes the insight and analysis available from the Behavior Based Fan Insight reports that you can access in the cloud.

Finding information

To find product documentation on the web, including all translated documentation, access IBM Knowledge Center (www.ibm.com/support/knowledgecenter/SSNN4U_1.0.0).

Accessibility features

Accessibility features help users who have a physical disability, such as restricted mobility or limited vision, to use information technology products.

For information about the commitment that IBM has to accessibility, see the IBM Accessibility Center (www.ibm.com/able).

Behavior Based Fan Insight HTML documentation has accessibility features. PDF documents are supplemental and, as such, include no added accessibility features.

Forward-looking statements

This documentation describes the current functionality of the product. References to items that are not currently available may be included. No implication of any future availability should be inferred. Any such references are not a commitment, promise, or legal obligation to deliver any material, code, or functionality. The development, release, and timing of features or functionality remain at the sole discretion of IBM®.

Samples disclaimer

Sample files may contain fictional data manually or machine generated, factual data compiled from academic or public sources, or data used with permission of the copyright holder, for use as sample data to develop sample applications. Product names referenced may be the trademarks of their respective owners. Unauthorized duplication is prohibited.

Overview of Behavior Based Fan InsightIBM Behavior Based Fan Insight is a prebuilt solution that provides a 360-degree view of your fans. By understanding fan behavior and leveraging fan segmentation and analysis, you can increase ticket sales, and increase revenue from concessions and retail sources.overviewThe source for much of the content in this section is the Ottawa Senators BBFI requirements v0.8 20151005.xls document.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 utilizing 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.What is "acceleration data"? Brian W can you reply?Brian W: Eric thought you might know the answer to this question. Behavior Based Fan Insight enables you to understand how contextual content impacts 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.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?

Overview of Behavior Based Fan Insight

IBM Behavior Based Fan Insight is a prebuilt solution that provides a 360-degree view of your fans. By understanding fan behavior and leveraging 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 utilizing 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 enables you to understand how contextual content impacts 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.

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?

The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors. reportsmetricskey performance indicatorsHere's the list of available reports:Customer SegmentationProvides a holistic view and better targeting opportunities for current fan base and potential fans and customers.View the customer segments, the metrics, and details about those segments. Drill down in a customer segment to view individual customers. Customer Target GroupsA bubble chart that groups customers in low, medium, high, and very high probability to churn. Generate a detailed customer list of the group and save it in Excel, CSV, and other formats.Customer DemographicsShows you demographic information for a customer segment. The report shows demographic characteristics such as household income, household size, education, age, and marital status.Customer ProfileGenerate this report from the Customer List. Shows contact information, detailed spend and ticket purchase behavior for one customer. Customer ListGenerate this report from many of the other reports in Behavior Based Fan Insight. It's a list report that shows specific customer information such as name, customer ID, and contact information - useful for phone or email marketing campaigns.Social and News Media ActivityShows you how emotions and sentiment are trending with your influencers, as well as the key topics in those trends.Influencer ProfileDetailed information about an influencer.Purchase Lead TimeA KPI line chart that shows summaries of purchase lead time by segment per event, or over a series of events.Track the performance and effectiveness of key initiatives by purchase lead time. Purchase lead time is the difference in days between when a customer buys a ticket and when that customer attends the event.Entrance Lead TimeA KPI line chart that shows how far in advance customers arrive at an event. Event Attendance By Price LevelA KPI bar chart that shows used and unused tickets by price level.Event Attendance By EventA KPI bar chart that shows used and unused tickets by event.Events ComparisonA KPI bar chart that shows summaries of customer ticket purchases per event.Track the performance and effectiveness of key initiatives by customer segment. Sales Trend and Predictive InsightsAn at-glance view of sales trends for your organization.Brand Social Activity and PopularityShows your brand's popularity through emotions and sentiment. It provides key topics of discussion and highlights the key sources of information.Predictive analytics data sources and input variables The following data sources and key input variables are in Behavior Based Fan Insight: Data sourcesPurchase, attendance, and demographics.Key input variablesTenure, type of fan, sport and non-sport event purchased and attended, sales channel, ticket type, seating level, sales channel, purchase lead times, distance to stadium, corporate/consumer, and game characteristics.Customer segmentation model The customer segmentation model helps you to launch targeted marketing campaigns by grouping customers into distinct clusters. You can adapt your marketing campaigns to each cluster with minimal effort. To find the clusters, Behavior Based Fan Insight uses the purchasing behavior of your customers, which is captured in their transactional data. The customer base of your organization consists of the following groups:Non-sport fansCustomers who attended only concerts in the past - no games.Casual fansCustomers who buy non-season tickets to attend games. They might also attend concerts.Season seat members (SSMs)Customers who buy season tickets to attend games. They might also attend concerts. To further break the previously listed groups into actionable clusters, the model differentiates between core and transient customers within each group. A core customer is one that attends multiple events, purchases multiple tickets, and spends higher than average per season. A transient customer attends fewer events and spends less. To determine whether a customer is core or transient, Behavior Based Fan Insight creates the following variables based on the transactional history of your customers:Most common ticket level purchased. For example, low, medium, and high. Average number of events and tickets purchased per seasonNumber of game packages purchased per season. For example, 3-game package and 5-game package. The customer segmentation model identifies outliers and places them into separate clusters. For example, groups, promotional customers, and ex-season seat members are considered casual fans but they are placed into separate clusters because their spending behavior is different than most casual fans. Scoring models Behavior Based Fan Insight also identifies the customers who are most likely to respond to certain marketing campaigns. The following classification models score your customers based on their transactional behavior:Become SSM modelIdentifies casual fans who are more likely to become season seat members.Upsell modelIdentifies casual fans who are likely to spend 10% more than what they spent in the previous season. For SSMs, this model identifies the customers who are likely to spend 15% more than they spent in the previous season.Turnover modelIdentifies customers who are most likely not to purchase game tickets.Become fan modelIdentifies the non-sport fans who are most likely to purchase game tickets. The scoring models are built based on the events that took place in the previous two seasons. For example, to build the turnover model for the 2015 season, Behavior Based Fan Insight finds the customers who purchased game tickets in the 2013 season, but did not purchase any game tickets in the 2014 model, and analyzes their spend behavior. The scoring models are periodically updated and rebuilt to account for changes in the transactional history of your customers.Metrics The following list describes some of the key metrics used in Behavior Based Fan Insight.Customer classThe way your organization groups its customers.Ticket typePredefined grouping options for purchase of tickets.Game typeIf the game is hot or cold based on ratings of Bronze, Silver, or Gold. A Bronze game is considered to be a lower draw than a Gold game. New scoreThe likelihood that a customer who has never bought a ticket before will buy a ticket. Expressed as a percentage.Renewal scoreThe likelihood that a customer who has previously purchased a ticket will buy tickets next year. Expressed as a percentage. The renewal score drops if they are likely to purchase fewer dollars of tickets than before.Up sell scoreThe likelihood that a casual buyer customer will buy at least 10% greater dollars of tickets over the prior year. Expressed as a percentage. Also, the likelihood that a season seat owner will buy at least 15% greater dollars of tickets over the prior year.Key performance indicators The reports refer to the following key performance indicators (KPIs):Type of consumerBusiness or individual.Ticket purchase spend or history by customer segmentCustomer class, ticket level, ticket type, amount spent, date purchased, time purchased, time of event, opponent, date (historical change over time).POS location by segmentTo make this non-Senators specific I changed this from CapitalTickets web site, stadium, call in, Canadian Tire Centre, or otherOnline tickets sales website, stadium, call in, stadium box office, or other.Top buyers by game by segment (revenue and number of tickets)Rank, amount spent, buyer information such as name, email address, or phone number, and number of tickets.Frequency of ticket purchases by segmentTicket type, location, amount spent, customer segment, and date. Customer retention percentage per segmentBy customer, segment, location, ticket type, and date.Household distance from stadium per segmentDistance in kilometers. Purchase lead time per game and per segmentBy customer, segment, location, ticket type, and date.Sales by event per segmentCustomer class, customer segment, ticket type, price of tickets purchased, and date.Ticket purchase performance by segmentCustomer class, customer segment, ticket type, price of tickets purchased, and date.Conversion by SegmentCustomer class, customer segment, ticket type, and date.Hot Game (Velocity of Sales)Determined by the number of tickets bought, date purchased, date of event, and lead time.Cold Game (Velocity of Sales)Determined by the number of tickets bought, date purchased, date of event, and lead time.Selecting and running a reportYou can access the reports from the Behavior Based Fan Insight home page.Customer SegmentationThe Customer Segmentation report provides a view of the customer segments, the metrics and details about those segments. Use it as a starting point to determine the segment for which you want to view customers.Customer Target GroupsThe Customer Target Groups report helps you to develop lead lists to improve targeting and define timing, and content and frequency of interactions with your fans. Use the analysis in the report to target the right fans or clients at the right time, with the right offer. Customer DemographicsThe Customer Demographics report shows you key demographic characteristics of a customer segment in an at-a-glance format. Customer ProfileTo see the Customer Profile report for a customer, click an email address in the Customer List report.Customer ListThe Customer List report shows detailed customer information such as name, customer ID, and contact information.Social and News Media ActivityThe Social and News Media Activity report shows you how emotions and sentiment are trending with your influencers, as well as the key topics in those trends. Searching for an influencerYou can search for a specific influencer and get detailed information about them in the Influencer Profile report.Influencer ProfileThe Influencer Profile report shows you the engagement habits, emotion and sentiment trends, and topics discussed for an influencer for the selected date range. You can also see detailed information about the influencer. Purchase Lead TimeThe Purchase Lead Time report shows you how far in advance ticket purchases are made by customer segment or by event.Entrance Lead TimeThe Entrance Lead Time report shows you how far in advance customers enter the venue for an event by customer segment. Event Attendance By Price LevelThe Event Attendance By Price Level report shows you used and unused tickets by price level. Event Attendance By EventThe Event Attendance By Event report shows you used and unused tickets by event. Events ComparisonThe Events Comparison report shows you ticket purchases by ticket type and customer segment. Sales Trend and Predictive InsightsThe Sales Trend and Predictive Insights provides you with an an at-glance view of sales trends for your organization. It contains several charts that show sales by customer segment, channel, event, and other indicators. There are also charts that show purchase lead time and probability to turn over or spend more. Brand Social Activity and PopularityThe Brand Social Activity and Popularity report shows your brand's popularity through emotions and sentiment. It provides key topics of discussion and highlights the key sources of information.

The reports

The reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Here's the list of available reports:

Customer Segmentation

Provides a holistic view and better targeting opportunities for current fan base and potential fans and customers.

View the customer segments, the metrics, and details about those segments. Drill down in a customer segment to view individual customers.

Customer Target Groups

A bubble chart that groups customers in low, medium, high, and very high probability to churn.

Generate a detailed customer list of the group and save it in Excel, CSV, and other formats.

Customer Demographics

Shows you demographic information for a customer segment. The report shows demographic characteristics such as household income, household size, education, age, and marital status.

Customer Profile

Generate this report from the Customer List. Shows contact information, detailed spend and ticket purchase behavior for one customer.

Customer List

Generate this report from many of the other reports in Behavior Based Fan Insight. It's a list report that shows specific customer information such as name, customer ID, and contact information - useful for phone or email marketing campaigns.

Social and News Media Activity

Shows you how emotions and sentiment are trending with your influencers, as well as the key topics in those trends.

Influencer Profile

Detailed information about an influencer.

Purchase Lead Time

A KPI line chart that shows summaries of purchase lead time by segment per event, or over a series of events.

Track the performance and effectiveness of key initiatives by purchase lead time. Purchase lead time is the difference in days between when a customer buys a ticket and when that customer attends the event.

Entrance Lead Time

A KPI line chart that shows how far in advance customers arrive at an event.

Event Attendance By Price Level

A KPI bar chart that shows used and unused tickets by price level.

Event Attendance By Event

A KPI bar chart that shows used and unused tickets by event.

Events Comparison

A KPI bar chart that shows summaries of customer ticket purchases per event.

Track the performance and effectiveness of key initiatives by customer segment.

Sales Trend and Predictive Insights

An at-glance view of sales trends for your organization.

Brand Social Activity and Popularity

Shows your brand's popularity through emotions and sentiment. It provides key topics of discussion and highlights the key sources of information.

Predictive analytics data sources and input variables

The following data sources and key input variables are in Behavior Based Fan Insight:

Data sources

Purchase, attendance, and demographics.

Key input variables

Tenure, type of fan, sport and non-sport event purchased and attended, sales channel, ticket type, seating level, sales channel, purchase lead times, distance to stadium, corporate/consumer, and game characteristics.

Customer segmentation model

The customer segmentation model helps you to launch targeted marketing campaigns by grouping customers into distinct clusters. You can adapt your marketing campaigns to each cluster with minimal effort. To find the clusters, Behavior Based Fan Insight uses the purchasing behavior of your customers, which is captured in their transactional data.

The customer base of your organization consists of the following groups:

Non-sport fans

Customers who attended only concerts in the past - no games.

Casual fans

Customers who buy non-season tickets to attend games. They might also attend concerts.

Season seat members (SSMs)

Customers who buy season tickets to attend games. They might also attend concerts.

To further break the previously listed groups into actionable clusters, the model differentiates between core and transient customers within each group. A core customer is one that attends multiple events, purchases multiple tickets, and spends higher than average per season. A transient customer attends fewer events and spends less. To determine whether a customer is core or transient, Behavior Based Fan Insight creates the following variables based on the transactional history of your customers:

Most common ticket level purchased. For example, low, medium, and high.

Average number of events and tickets purchased per season

Number of game packages purchased per season. For example, 3-game package and 5-game package.

The customer segmentation model identifies outliers and places them into separate clusters. For example, groups, promotional customers, and ex-season seat members are considered casual fans but they are placed into separate clusters because their spending behavior is different than most casual fans.

Scoring models

Behavior Based Fan Insight also identifies the customers who are most likely to respond to certain marketing campaigns. The following classification models score your customers based on their transactional behavior:

Become SSM model

Identifies casual fans who are more likely to become season seat members.

Upsell model

Identifies casual fans who are likely to spend 10% more than what they spent in the previous season. For SSMs, this model identifies the customers who are likely to spend 15% more than they spent in the previous season.

Turnover model

Identifies customers who are most likely not to purchase game tickets.

Become fan model

Identifies the non-sport fans who are most likely to purchase game tickets.

The scoring models are built based on the events that took place in the previous two seasons. For example, to build the turnover model for the 2015 season, Behavior Based Fan Insight finds the customers who purchased game tickets in the 2013 season, but did not purchase any game tickets in the 2014 model, and analyzes their spend behavior. The scoring models are periodically updated and rebuilt to account for changes in the transactional history of your customers.

Metrics

The following list describes some of the key metrics used in Behavior Based Fan Insight.

Customer class

The way your organization groups its customers.

Ticket type

Predefined grouping options for purchase of tickets.

Game type

If the game is hot or cold based on ratings of Bronze, Silver, or Gold. A Bronze game is considered to be a lower draw than a Gold game.

New score

The likelihood that a customer who has never bought a ticket before will buy a ticket. Expressed as a percentage.

Renewal score

The likelihood that a customer who has previously purchased a ticket will buy tickets next year. Expressed as a percentage. The renewal score drops if they are likely to purchase fewer dollars of tickets than before.

Up sell score

The likelihood that a casual buyer customer will buy at least 10% greater dollars of tickets over the prior year. Expressed as a percentage. Also, the likelihood that a season seat owner will buy at least 15% greater dollars of tickets over the prior year.

Key performance indicators

The reports refer to the following key performance indicators (KPIs):

Type of consumer

Business or individual.

Ticket purchase spend or history by customer segment

Customer class, ticket level, ticket type, amount spent, date purchased, time purchased, time of event, opponent, date (historical change over time).

POS location by segment

Online tickets sales website, stadium, call in, stadium box office, or other.

Top buyers by game by segment (revenue and number of tickets)

Rank, amount spent, buyer information such as name, email address, or phone number, and number of tickets.

Frequency of ticket purchases by segment

Ticket type, location, amount spent, customer segment, and date.

Customer retention percentage per segment

By customer, segment, location, ticket type, and date.

Household distance from stadium per segment

Distance in kilometers.

Purchase lead time per game and per segment

By customer, segment, location, ticket type, and date.

Sales by event per segment

Customer class, customer segment, ticket type, price of tickets purchased, and date.

Ticket purchase performance by segment

Customer class, customer segment, ticket type, price of tickets purchased, and date.

Conversion by Segment

Customer class, customer segment, ticket type, and date.

Hot Game (Velocity of Sales)

Determined by the number of tickets bought, date purchased, date of event, and lead time.

Cold Game (Velocity of Sales)

Determined by the number of tickets bought, date purchased, date of event, and lead time.

Selecting and running a report
You can access the reports from the Behavior Based Fan Insight home page.

Customer Segmentation
The Customer Segmentation report provides a view of the customer segments, the metrics and details about those segments. Use it as a starting point to determine the segment for which you want to view customers.

Customer Target Groups
The Customer Target Groups report helps you to develop lead lists to improve targeting and define timing, and content and frequency of interactions with your fans. Use the analysis in the report to target the right fans or clients at the right time, with the right offer.

Customer Demographics
The Customer Demographics report shows you key demographic characteristics of a customer segment in an at-a-glance format.

Customer Profile
To see the Customer Profile report for a customer, click an email address in the Customer List report.

Customer List
The Customer List report shows detailed customer information such as name, customer ID, and contact information.

Social and News Media Activity
The Social and News Media Activity report shows you how emotions and sentiment are trending with your influencers, as well as the key topics in those trends.

Searching for an influencer
You can search for a specific influencer and get detailed information about them in the Influencer Profile report.

Influencer Profile
The Influencer Profile report shows you the engagement habits, emotion and sentiment trends, and topics discussed for an influencer for the selected date range. You can also see detailed information about the influencer.

Purchase Lead Time
The Purchase Lead Time report shows you how far in advance ticket purchases are made by customer segment or by event.

Entrance Lead Time
The Entrance Lead Time report shows you how far in advance customers enter the venue for an event by customer segment.

Event Attendance By Price Level
The Event Attendance By Price Level report shows you used and unused tickets by price level.

Event Attendance By Event
The Event Attendance By Event report shows you used and unused tickets by event.

Events Comparison
The Events Comparison report shows you ticket purchases by ticket type and customer segment.

Sales Trend and Predictive Insights
The Sales Trend and Predictive Insights provides you with an an at-glance view of sales trends for your organization. It contains several charts that show sales by customer segment, channel, event, and other indicators. There are also charts that show purchase lead time and probability to turn over or spend more.

Brand Social Activity and Popularity
The Brand Social Activity and Popularity report shows your brand's popularity through emotions and sentiment. It provides key topics of discussion and highlights the key sources of information.

Selecting and running a reportYou can access the reports from the Behavior Based Fan Insight home page.reportsrunningreportsselectingselecting a reportrunning a reportfilteringcascading filterFrom the home page, select Analyticsreport groupreport name.If the filter panel is not visible when the report opens, click the arrow on its border to maximize it. Click the arrow again to minimize the filter panel. You can also resize the filter panel by dragging its border.In the filter panel, select the filters that you want to apply to the report. A filter can be a cascading filter, which means its values determine the values in another filter. For example, there are two filters: month and day of month. When you select February in the month filter, then the day of month filter has the values 1 through 28. If you select July as the month, then the day of month filter has the values 1 through 31. When you can select only one value in a cascading filter, then any filters it affects are populated immediately. If you can select multiple values in a filter, then you must click Apply to populate the filters it affects and then select the values in the filter. The Purchase Lead Time contains several cascading filters, which means you'll have to select and apply several filters before you see the final report results. Click Apply to run the report. The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Selecting and running a report

You can access the reports from the Behavior Based Fan Insight home page.

Procedure

From the home page, select Analytics > report group > report name.

Note: If the filter panel is not visible when the report opens, click the arrow on its border to maximize it. Click the arrow again to minimize the filter panel. You can also resize the filter panel by dragging its border.

In the filter panel, select the filters that you want to apply to the report.

A filter can be a cascading filter, which means its values determine the values in another filter. For example, there are two filters: month and day of month. When you select February in the month filter, then the day of month filter has the values 1 through 28. If you select July as the month, then the day of month filter has the values 1 through 31.

When you can select only one value in a cascading filter, then any filters it affects are populated immediately. If you can select multiple values in a filter, then you must click Apply to populate the filters it affects and then select the values in the filter.

The Purchase Lead Time contains several cascading filters, which means you'll have to select and apply several filters before you see the final report results.

Click Apply to run the report.

Parent topic: The reports

Customer SegmentationThe Customer Segmentation report provides a view of the customer segments, the metrics and details about those segments. Use it as a starting point to determine the segment for which you want to view customers.reportsCustomer SegmentationCustomer Segmentationkey driversThe Customer Segmentation report displays a donut chart that is divided into customer segments. You can filter the data in the report in the following ways: By season seat members or non-season seat members. After you select a value, the customer segment filter is populated.By customer segmentBy corporate or non-corporate clientsClick Apply to generate or refresh the report.Hover over a segment to see the total customers in the segment. Under Hockey Factors and General Factors, you'll see the factors used to the determine the counts for each segment. To see a detailed customer list of the report, click Customer List. The customer list displays customer name, customer ID number, customer type, contact name, contact information, and other details about each customer. Click Customer Segmentation to return to the Customer Segmentation report. The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Customer Segmentation

The Customer Segmentation report provides a view of the customer segments, the metrics and details about those segments. Use it as a starting point to determine the segment for which you want to view customers.

The Customer Segmentation report displays a donut chart that is divided into customer segments. You can filter the data in the report in the following ways:

By season seat members or non-season seat members. After you select a value, the customer segment filter is populated.

By customer segment

By corporate or non-corporate clients

Click Apply to generate or refresh the report.

Hover over a segment to see the total customers in the segment.

Under Hockey Factors and General Factors, you'll see the factors used to the determine the counts for each segment.

To see a detailed customer list of the report, click Customer List. The customer list displays customer name, customer ID number, customer type, contact name, contact information, and other details about each customer. Click Customer Segmentation to return to the Customer Segmentation report.

Parent topic: The reports

Customer Target GroupsThe Customer Target Groups report helps you to develop lead lists to improve targeting and define timing, and content and frequency of interactions with your fans. Use the analysis in the report to target the right fans or clients at the right time, with the right offer. reportsCustomer Target GroupsCustomer ListCustomer Target GroupsCustomer Listpredictive factorsThe Customer Target Groups report is bubble chart that shows your customers' probability to churn in four ranges. Each bubble indicates a low, medium, high, or very high probability of customers to do one of the following things: turnover, spend more, become a season seat member, or become a fan. The y-axis displays the ticket quantity and the x-axis displays the season spend amount. Hover over a bubble to see the probability range, season spend amount, ticket quantity, and customer count. You can filter the data in the report in the following ways: By season seat members or non-season seat members. After you select a value, the customer segment filter is populated.By customer segmentBy customer typeClick Apply to generate or refresh the report.After the report is generated, you can view the data in the following ways: By probability typeProbability to turnover, probability to spend more, probability to become a season seat member, and probability to become a fan.By amount spentTotal amount spent or average amount spent.To see a detailed list of customers in a particular probability to churn range and probability type, right-click a bubble and select Go ToCustomer List. The customer list displays customer name, email address, customer ID number, customer segment, probability type and range, contact information, and other details about each customer. You can view this list in Excel, CSV, and other formats and then save it in a file.To see the factors that determine the churn prediction in a particular probability to churn range and probability type, right-click a bubble and select Go ToPredictive Factors. Click Customer List to display the full list of all customers in the report. This list displays customer name, customer ID number, email address, customer segment, and probability information.To sort the report, click the up down icon in a column heading.The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Customer Target Groups

The Customer Target Groups report helps you to develop lead lists to improve targeting and define timing, and content and frequency of interactions with your fans. Use the analysis in the report to target the right fans or clients at the right time, with the right offer.

The Customer Target Groups report is bubble chart that shows your customers' probability to churn in four ranges. Each bubble indicates a low, medium, high, or very high probability of customers to do one of the following things: turnover, spend more, become a season seat member, or become a fan. The y-axis displays the ticket quantity and the x-axis displays the season spend amount. Hover over a bubble to see the probability range, season spend amount, ticket quantity, and customer count.

You can filter the data in the report in the following ways:

By season seat members or non-season seat members. After you select a value, the customer segment filter is populated.

By customer segment

By customer type

Click Apply to generate or refresh the report.

After the report is generated, you can view the data in the following ways:

By probability type

Probability to turnover, probability to spend more, probability to become a season seat member, and probability to become a fan.

By amount spent

Total amount spent or average amount spent.

To see a detailed list of customers in a particular probability to churn range and probability type, right-click a bubble and select Go To > Customer List. The customer list displays customer name, email address, customer ID number, customer segment, probability type and range, contact information, and other details about each customer. You can view this list in Excel, CSV, and other formats and then save it in a file.

To see the factors that determine the churn prediction in a particular probability to churn range and probability type, right-click a bubble and select Go To > Predictive Factors.

Click Customer List to display the full list of all customers in the report. This list displays customer name, customer ID number, email address, customer segment, and probability information.

To sort the report, click the up down icon in a column heading.

Parent topic: The reports

Customer DemographicsThe Customer Demographics report shows you key demographic characteristics of a customer segment in an at-a-glance format. reportsCustomer DemographicsCustomer Demographicskey driversYou can filter the customer segment data to focus on specific demographic characteristics. Once you have determined the demographic characteristics that you want to target, you can generate a list of customers that have those demographic characteristics.You can filter the data in the report in the following ways: By season seat members or non-season seat members. After you select a value, the customer segment filter is populated.By customer segmentBy customer typeBy probability typeBy probability rangeClick Apply to generate or refresh the report.The report displays the following information for the selected customer segment (with the selected filter critieria): Number of households, average household income, average household size, and number of children in the householdDonut charts that show community, age group, occupation, and education. Each chart is divided into ranges showing the percentage of customers that fall into a range. For example, the age group donut chart is divided into age ranges of 10 to 20, 21 to 30, 31 to 40, and +40. Bar charts that show gender, employment status, own or rent a residence, and marital statusTo see a detailed list of customers for the selected filter criteria, click Customer List. The customer list displays customer name, email address, customer ID number, customer type, contact information, and other details about each customer. To export the Customer List report to a file, see Exporting the Customer List reportYou can export the Customer List to a file..The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Customer Demographics

The Customer Demographics report shows you key demographic characteristics of a customer segment in an at-a-glance format.

You can filter the customer segment data to focus on specific demographic characteristics. Once you have determined the demographic characteristics that you want to target, you can generate a list of customers that have those demographic characteristics.

You can filter the data in the report in the following ways:

By season seat members or non-season seat members. After you select a value, the customer segment filter is populated.

By customer segment

By customer type

By probability type

By probability range

Click Apply to generate or refresh the report.

The report displays the following information for the selected customer segment (with the selected filter critieria):

Number of households, average household income, average household size, and number of children in the household

Donut charts that show community, age group, occupation, and education. Each chart is divided into ranges showing the percentage of customers that fall into a range. For example, the age group donut chart is divided into age ranges of 10 to 20, 21 to 30, 31 to 40, and +40.

Bar charts that show gender, employment status, own or rent a residence, and marital status

To see a detailed list of customers for the selected filter criteria, click Customer List. The customer list displays customer name, email address, customer ID number, customer type, contact information, and other details about each customer. To export the Customer List report to a file, see Exporting the Customer List report.

Parent topic: The reports

Customer ProfileTo see the Customer Profile report for a customer, click an email address in the Customer List report.This report contains a Customer Profile tab and a Sales Transactions tab.Customer Profile tab This tab displays gender, phone, email address, mailing address, as well as household income, customer type, season seat membership, and customer segment. It shows the most common entrance lead time, purchase day, and purchase method. It also displays the following values:Lifetime ValueThe potential lifetime amount that the customer could spend.Avg Season Spend AmountThe average amount that the customer spends in a season.Total Spend AmountThe amount the customer has spent to date . The following charts for the customer are displayed: Spend amount by seasonProbabilities such as probability to turnover and probability to spend more Spend amount by genreTicket quantity by purchase lead time and sales channelTicket quantity by ticket level and ticket typeUsed and unused tickets by day of weekSales Transactions tabThis tab lists all of the transactions for the customer by season. A season is a group of scheduled events at the venue, such as the season games for a sports team or an annual concert schedule. The transaction information includes things like order date, the event, the number of tickets, and total amount of the transaction. The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Customer Profile

To see the Customer Profile report for a customer, click an email address in the Customer List report.

This report contains a Customer Profile tab and a Sales Transactions tab.

Customer Profile tab

This tab displays gender, phone, email address, mailing address, as well as household income, customer type, season seat membership, and customer segment. It shows the most common entrance lead time, purchase day, and purchase method. It also displays the following values:

Lifetime Value

The potential lifetime amount that the customer could spend.

Avg Season Spend Amount

The average amount that the customer spends in a season.

Total Spend Amount

The amount the customer has spent to date .

The following charts for the customer are displayed:

Spend amount by season

Probabilities such as probability to turnover and probability to spend more

Spend amount by genre

Ticket quantity by purchase lead time and sales channel

Ticket quantity by ticket level and ticket type

Used and unused tickets by day of week

Sales Transactions tab

This tab lists all of the transactions for the customer by season. A season is a group of scheduled events at the venue, such as the season games for a sports team or an annual concert schedule. The transaction information includes things like order date, the event, the number of tickets, and total amount of the transaction.

Parent topic: The reports

Customer ListThe Customer List report shows detailed customer information such as name, customer ID, and contact information.This report can be generated from many other reports in Behavior Based Fan Insight to give you a detailed list of the customers included in the report. You can also access an individual Customer Profile report from the Customer List report.The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors. Exporting the Customer List reportYou can export the Customer List to a file.

Customer List

The Customer List report shows detailed customer information such as name, customer ID, and contact information.

This report can be generated from many other reports in Behavior Based Fan Insight to give you a detailed list of the customers included in the report. You can also access an individual Customer Profile report from the Customer List report.

Exporting the Customer List report
You can export the Customer List to a file.

Parent topic: The reports

Exporting the Customer List reportYou can export the Customer List to a file.Customer ListexportingYou can export the report in the following formats: PDFExcel 2007 dataExcel 2007Excel 2002CSVXMLRight-click anywhere in the Customer List report, select Widget ActionsExport to, and then select the format to export to.Customer ListThe Customer List report shows detailed customer information such as name, customer ID, and contact information.

Exporting the Customer List report

You can export the Customer List to a file.

About this task

You can export the report in the following formats:

PDF

Excel 2007 data

Excel 2007

Excel 2002

CSV

XML

Procedure

Right-click anywhere in the Customer List report, select Widget Actions > Export to, and then select the format to export to.

Parent topic: Customer List

Social and News Media ActivityThe Social and News Media Activity report shows you how emotions and sentiment are trending with your influencers, as well as the key topics in those trends. reportsSocial and News Media ActivitySocial and News Media Activitylook-alikeinfluencerkey driversThe data in the Social and News Media Activity report is based on social media and news media influencers. A social media influencer is a user with a large follower base who actively engages with the brand through social media. A news media influencer is a writer who actively publishes articles about the brand. and their look-alikes or individuals that are similar to the influencers.The Social and News Media Activity report also shows you look-alikes. A look-alike is a non-influential user who follows your brand online or is active on social media about your brand. An example of a look-alike is someone who tweets about your brand every now and then, but not as much as an influencer does. A look-alike has the potential to engage with your brand given the right message. You can use an online campaign to specifically target look-alikes. The following values and charts are displayed in the Social and News Media Activity report:Number of documents, users, shares, and favoritesA count of each of these items for the selected filter criteria.Emotions trendArea chart that displays emotions such as anger, sadness, fear, joy, and disgust.Sentiments trendArea chart that displays neutral, negative, and positive sentiment. InfluencersBubble chart that displays social media and news media influencers. The larger the bubble, the greater the influence. Mouse over a bubble to see the source type, name of the influencer, and number of documents published. Click a bubble to see the Influencer Profile report which provides detailed information about the influencer. For more information, see Influencer ProfileThe Influencer Profile report shows you the engagement habits, emotion and sentiment trends, and topics discussed for an influencer for the selected date range. You can also see detailed information about the influencer. .Look-alikesBubble chart that displays look-alikes. The larger the bubble, the more active the look-alike is on social media.The larger the bubble, the more documents a user has published, which I rephrased as above.You can click a bubble to get detailed information about a specific look-alike. Emotions for key topicsBar chart that displays emotions for the top four topics.Sentiments for key topicsBar chart that displays sentiments for the top four topics.TopicsWord cloud that displays the topics being discussed.Publication sourcesWord cloud that displays the publication sources of the news media influencers.You can filter the data in the following ways: By date rangeSource typeBy theme. A theme identifies a group of related topics within a brand. For example, a professional sports team or a jazz music festival.By sentimentBy emotionThe reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Social and News Media Activity

The Social and News Media Activity report shows you how emotions and sentiment are trending with your influencers, as well as the key topics in those trends.

The data in the Social and News Media Activity report is based on social media and news media influencers. A social media influencer is a user with a large follower base who actively engages with the brand through social media. A news media influencer is a writer who actively publishes articles about the brand. and their look-alikes or individuals that are similar to the influencers.

The Social and News Media Activity report also shows you look-alikes. A look-alike is a non-influential user who follows your brand online or is active on social media about your brand. An example of a look-alike is someone who tweets about your brand every now and then, but not as much as an influencer does. A look-alike has the potential to engage with your brand given the right message. You can use an online campaign to specifically target look-alikes.

The following values and charts are displayed in the Social and News Media Activity report:

Number of documents, users, shares, and favorites

A count of each of these items for the selected filter criteria.

Emotions trend

Area chart that displays emotions such as anger, sadness, fear, joy, and disgust.

Sentiments trend

Area chart that displays neutral, negative, and positive sentiment.

Influencers

Bubble chart that displays social media and news media influencers. The larger the bubble, the greater the influence. Mouse over a bubble to see the source type, name of the influencer, and number of documents published. Click a bubble to see the Influencer Profile report which provides detailed information about the influencer. For more information, see Influencer Profile.

Look-alikes

Bubble chart that displays look-alikes. The larger the bubble, the more active the look-alike is on social media.You can click a bubble to get detailed information about a specific look-alike.

Emotions for key topics

Bar chart that displays emotions for the top four topics.

Sentiments for key topics

Bar chart that displays sentiments for the top four topics.

Topics

Word cloud that displays the topics being discussed.

Publication sources

Word cloud that displays the publication sources of the news media influencers.

You can filter the data in the following ways:

By date range

Source type

By theme. A theme identifies a group of related topics within a brand. For example, a professional sports team or a jazz music festival.

By sentiment

By emotion

Parent topic: The reports

Searching for an influencerYou can search for a specific influencer and get detailed information about them in the Influencer Profile report.reportsInfluencer ProfileInfluencer ProfileinfluencerFrom the home page, select AnalyticsSocialInfluence Profile.Select search criteria.From Datestart dateTo Dateend dateSource Typenews media or social mediaSentimentpositive, neutral, or negativeEnter Influencer keywords and choose a search option.You can also make the search case insensitive. Click Search.Under Choice, select an influencer from the list that displays.Click Apply.The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Searching for an influencer

You can search for a specific influencer and get detailed information about them in the Influencer Profile report.

Procedure

From the home page, select Analytics > Social > Influence Profile.

Select search criteria.

Option | Description
From Date | start date
To Date | end date
Source Type | news media or social media
Sentiment | positive, neutral, or negative

Enter Influencer keywords and choose a search option. You can also make the search case insensitive.

Click Search.

Under Choice, select an influencer from the list that displays.

Click Apply.

Parent topic: The reports

Influencer ProfileThe Influencer Profile report shows you the engagement habits, emotion and sentiment trends, and topics discussed for an influencer for the selected date range. You can also see detailed information about the influencer. reportsInfluencer ProfileInfluencer Profilekey driversYou can access the Influencer Profile report in the following ways:By clicking a bubble in the Influencers chart contained in the Social and News Media Activityreport.Takes you directly to the report for the selected influencer.By selecting it from the Analytics menu on the home page.Allows you to search for an influencer to report on. For more information, see Searching for an influencerYou can search for a specific influencer and get detailed information about them in the Influencer Profile report..A photo of the influencer, if available, is displayed along with their influencer score, number of followers, number of updates, number of documents published, the URL of their Twitter profile, gender, community they belong to, and main publication source. The Influencer Profile and Activities tab contains the following charts: Engagement habitsA heat map that shows you when the influencer is most active. Emotions trendArea chart that displays emotions such as anger, sadness, fear, joy, and disgust.Sentiments trendArea chart that displays neutral, negative, and positive sentiment. Key topicsDisplays the topics that the influencer talks about the most and the emotions associated with them. Topics that are unrelated to the selected brand or theme are shown. You can filter by emotion.Main topics by themeA word cloud that displays the topics that the influencer is talking about. Emotions for key topicsEach topic has a bar chart with the emotions displayed as sections in the bar. Sentiments for key topicsEach topic has a bar chart with the sentiments displayed as sections in the bar.To change the date range for the report, change the From Date and To Date fields, and then click Apply. The Look-alikes tab contains a list of look-alikes. A look-alike is a non-influential user who follows your brand online or is active on social media about your brand. For each look-alike, information such as user name, location, email address, gender, marital status, look-alike's primary and secondary influencer is displayed. The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Influencer Profile

The Influencer Profile report shows you the engagement habits, emotion and sentiment trends, and topics discussed for an influencer for the selected date range. You can also see detailed information about the influencer.

You can access the Influencer Profile report in the following ways:

By clicking a bubble in the Influencers chart contained in the Social and News Media Activityreport.

Takes you directly to the report for the selected influencer.

By selecting it from the Analytics menu on the home page.

Allows you to search for an influencer to report on. For more information, see Searching for an influencer.

A photo of the influencer, if available, is displayed along with their influencer score, number of followers, number of updates, number of documents published, the URL of their Twitter profile, gender, community they belong to, and main publication source.

The Influencer Profile and Activities tab contains the following charts:

Engagement habits

A heat map that shows you when the influencer is most active.

Emotions trend

Area chart that displays emotions such as anger, sadness, fear, joy, and disgust.

Sentiments trend

Area chart that displays neutral, negative, and positive sentiment.

Key topics

Displays the topics that the influencer talks about the most and the emotions associated with them. Topics that are unrelated to the selected brand or theme are shown. You can filter by emotion.

Main topics by theme

A word cloud that displays the topics that the influencer is talking about.

Emotions for key topics

Each topic has a bar chart with the emotions displayed as sections in the bar.

Sentiments for key topics

Each topic has a bar chart with the sentiments displayed as sections in the bar.

To change the date range for the report, change the From Date and To Date fields, and then click Apply.

The Look-alikes tab contains a list of look-alikes. A look-alike is a non-influential user who follows your brand online or is active on social media about your brand. For each look-alike, information such as user name, location, email address, gender, marital status, look-alike's primary and secondary influencer is displayed.

Parent topic: The reports

Purchase Lead TimeThe Purchase Lead Time report shows you how far in advance ticket purchases are made by customer segment or by event.reportsPurchase Lead TimePurchase Lead TimeThis report is a line chart with summaries of purchase lead time by customer segment or event. Each line represents a customer segment or event. The y-axis shows the number of tickets purchased. The x-axis shows the lead time of ticket purchase by customer segment or event. You can filter the data in the report in the following ways: By season seat members or non-season seat members. After you select a value, the customer segment filter is populated.By customer segmentBy corporate or non-corporate clientsBy season. After you select a value, the event group, ticket class, ticket type, and ticket level filters are populated. By ticket classBy ticket typeBy ticket levelBy event group. You can select multiple values in this filter. After you finish your selections, you must click Apply to populate the day of week filter.By day of week. You can select multiple values in this filter. After you finish your selections, you must click Apply to populate the event filter.By eventClick Apply to generate or refresh the report.After the report is generated, you can view the data by customer segment or event.To see detailed information about each customer in the report, click Customer List. The customer list displays customer name, customer ID number, customer type, contact name, contact information, and other details about each customer.Click Purchase Lead Time to return to the Purchase Lead Time report.The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Purchase Lead Time

The Purchase Lead Time report shows you how far in advance ticket purchases are made by customer segment or by event.

This report is a line chart with summaries of purchase lead time by customer segment or event. Each line represents a customer segment or event. The y-axis shows the number of tickets purchased. The x-axis shows the lead time of ticket purchase by customer segment or event.

You can filter the data in the report in the following ways:

By season seat members or non-season seat members. After you select a value, the customer segment filter is populated.

By customer segment

By corporate or non-corporate clients

By season. After you select a value, the event group, ticket class, ticket type, and ticket level filters are populated.

By ticket class

By ticket type

By ticket level

By event group. You can select multiple values in this filter. After you finish your selections, you must click Apply to populate the day of week filter.

By day of week. You can select multiple values in this filter. After you finish your selections, you must click Apply to populate the event filter.

By event

Click Apply to generate or refresh the report.

After the report is generated, you can view the data by customer segment or event.

To see detailed information about each customer in the report, click Customer List. The customer list displays customer name, customer ID number, customer type, contact name, contact information, and other details about each customer.

Click Purchase Lead Time to return to the Purchase Lead Time report.

Parent topic: The reports

Entrance Lead TimeThe Entrance Lead Time report shows you how far in advance customers enter the venue for an event by customer segment. reportsEntrance Lead TimeEntrance Lead TimeEach line in the report represents a customer segment. The y-axis shows the number of tickets used. The x-axis shows the lead time of entry up to a maximum of 2 hours prior to and after the start of the event in 15 minute intervals. You can filter the data in the report in the following ways:By seasonBy eventBy season seat members or non-season seat members. After you select a value, the customer segment filter is populated.By customer segmentClick Apply to generate or refresh the report.After the report is generated, you can view the data by customer segment or event.The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Entrance Lead Time

The Entrance Lead Time report shows you how far in advance customers enter the venue for an event by customer segment.

Each line in the report represents a customer segment. The y-axis shows the number of tickets used. The x-axis shows the lead time of entry up to a maximum of 2 hours prior to and after the start of the event in 15 minute intervals.

You can filter the data in the report in the following ways:

By season

By event

By season seat members or non-season seat members. After you select a value, the customer segment filter is populated.

By customer segment

Click Apply to generate or refresh the report.

After the report is generated, you can view the data by customer segment or event.

Parent topic: The reports

Event Attendance By Price LevelThe Event Attendance By Price Level report shows you used and unused tickets by price level. reportsEvent Attendance By Price LevelEvent Attendance By Price LevelEach bar represents a section, which is divided into used and unused tickets. The y-axis shows the total number of tickets. The x-axis shows the price level. You can filter the data in the report in the following ways:By seasonBy eventBy season seat members or non-season seat members. After you select a value, the customer segment filter is populated.By customer segmentTo see detailed information about each customer in the report, click Customer List. The customer list displays customer name, customer ID number, email address, if the customer is a season seat member, ticket class, ticket level, name of service representative, number of used tickets, number of unused tickets, total tickets the customer has, and the used tickets expressed as a percentage. To return to the Event Attendance By Price Level report, click Ticket Breakage.The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Event Attendance By Price Level

The Event Attendance By Price Level report shows you used and unused tickets by price level.

Each bar represents a section, which is divided into used and unused tickets. The y-axis shows the total number of tickets. The x-axis shows the price level.

You can filter the data in the report in the following ways:

By season

By event

By season seat members or non-season seat members. After you select a value, the customer segment filter is populated.

By customer segment

To see detailed information about each customer in the report, click Customer List. The customer list displays customer name, customer ID number, email address, if the customer is a season seat member, ticket class, ticket level, name of service representative, number of used tickets, number of unused tickets, total tickets the customer has, and the used tickets expressed as a percentage. To return to the Event Attendance By Price Level report, click Ticket Breakage.

Parent topic: The reports

Event Attendance By EventThe Event Attendance By Event report shows you used and unused tickets by event. reportsEvent Attendance By EventEvent Attendance By EventEach bar represents a section, which is divided into used and unused tickets. The y-axis shows the total number of tickets. The x-axis shows the event. You can filter the data in the report in the following ways:By seasonBy ticket levelBy season seat members or non-season seat members. After you select a value, the customer segment filter is populated.By customer segmentThe reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Event Attendance By Event

The Event Attendance By Event report shows you used and unused tickets by event.

Each bar represents a section, which is divided into used and unused tickets. The y-axis shows the total number of tickets. The x-axis shows the event.

You can filter the data in the report in the following ways:

By season

By ticket level

By season seat members or non-season seat members. After you select a value, the customer segment filter is populated.

By customer segment

Parent topic: The reports

Events ComparisonThe Events Comparison report shows you ticket purchases by ticket type and customer segment. reportsEvents ComparisonEvents ComparisonThe report is a bar chart with summaries of ticket purchases by ticket measure. Ticket measure can be ticket level, ticket type, or ticket class. A customer segment is represented by a different color in a bar. The x-axis displays events by ticket measure. The y-axis displays the sum by unit of measure (ticket quantity, sales amount, or customer count).You can filter the data in the report in the following ways: By season seat members or non-season seat members. After you select a value, the customer segment filter is populated.By customer segmentBy corporate or non-corporate clientsBy season. After you select a value, the event group, ticket class, ticket type, and ticket level filters are populated. By ticket classBy ticket typeBy ticket levelBy event group. You can select multiple values in this filter. After you finish your selections, you must click Apply to populate the day of week filter.By day of week. You can select multiple values in this filter. After you finish your selections, you must click Apply to populate the event filter.By eventClick Apply to generate or refresh the report.After the report is generated, you can view the data in the following ways: By ticket type, ticket level, or ticket class.By ticket quantity, sales amount, or customer count.To see detailed information about each customer in the report, click Customer List. The customer list displays customer name, customer ID number, customer type, contact name, contact information, and other details about each customer.Click Customer Purchases to return to the Events Comparison report.The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Events Comparison

The Events Comparison report shows you ticket purchases by ticket type and customer segment.

The report is a bar chart with summaries of ticket purchases by ticket measure. Ticket measure can be ticket level, ticket type, or ticket class. A customer segment is represented by a different color in a bar. The x-axis displays events by ticket measure. The y-axis displays the sum by unit of measure (ticket quantity, sales amount, or customer count).

You can filter the data in the report in the following ways:

By season seat members or non-season seat members. After you select a value, the customer segment filter is populated.

By customer segment

By corporate or non-corporate clients

By season. After you select a value, the event group, ticket class, ticket type, and ticket level filters are populated.

By ticket class

By ticket type

By ticket level

By event group. You can select multiple values in this filter. After you finish your selections, you must click Apply to populate the day of week filter.

By day of week. You can select multiple values in this filter. After you finish your selections, you must click Apply to populate the event filter.

By event

Click Apply to generate or refresh the report.

After the report is generated, you can view the data in the following ways:

By ticket type, ticket level, or ticket class.

By ticket quantity, sales amount, or customer count.

To see detailed information about each customer in the report, click Customer List. The customer list displays customer name, customer ID number, customer type, contact name, contact information, and other details about each customer.

Click Customer Purchases to return to the Events Comparison report.

Parent topic: The reports

Sales Trend and Predictive InsightsThe Sales Trend and Predictive Insights provides you with an an at-glance view of sales trends for your organization. It contains several charts that show sales by customer segment, channel, event, and other indicators. There are also charts that show purchase lead time and probability to turn over or spend more. reportsSales Trend and Predictive InsightsSales Trend and Predictive InsightsThe following charts are displayed in the Sales Trend and Predictive Insights:Current year sales by customer segmentCurrent year lead scoring by sales amount (customer probability to churn)Purchase lead time by customer countSales by seat level season over seasonSales by channel season over seasonSales by event season over season You can filter the data in the dashboard in the following ways: By event typeBy season seat members or non-season seat membersClick a value in a chart to filter on a specific aspect and the other charts are automatically filtered in the same way. For example, if you click on a customer segment, the other charts in the dashboard are filtered to include only data for that customer segment. To clear the filter, click in an empty spot within the chart.The reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Sales Trend and Predictive Insights

The Sales Trend and Predictive Insights provides you with an an at-glance view of sales trends for your organization. It contains several charts that show sales by customer segment, channel, event, and other indicators. There are also charts that show purchase lead time and probability to turn over or spend more.

The following charts are displayed in the Sales Trend and Predictive Insights:

Current year sales by customer segment

Current year lead scoring by sales amount (customer probability to churn)

Purchase lead time by customer count

Sales by seat level season over season

Sales by channel season over season

Sales by event season over season

You can filter the data in the dashboard in the following ways:

By event type

By season seat members or non-season seat members

Click a value in a chart to filter on a specific aspect and the other charts are automatically filtered in the same way. For example, if you click on a customer segment, the other charts in the dashboard are filtered to include only data for that customer segment. To clear the filter, click in an empty spot within the chart.

Parent topic: The reports

Brand Social Activity and PopularityThe Brand Social Activity and Popularity report shows your brand's popularity through emotions and sentiment. It provides key topics of discussion and highlights the key sources of information.reportsBrand Social Activity and PopularityBrand Social Activity and Popularitykey driversThe following charts are displayed in the Brand Social Activity and Popularity report:Activity score over timePopularity score over timeEmotions over timeSentiment over timeMain themes and topics word cloudMain sources and themes word cloudThe reportsThe reports in IBM Behavior Based Fan Insight help you to get insight into your customers and their purchasing behaviors.

Brand Social Activity and Popularity

The Brand Social Activity and Popularity report shows your brand's popularity through emotions and sentiment. It provides key topics of discussion and highlights the key sources of information.

The following charts are displayed in the Brand Social Activity and Popularity report:

Activity score over time

Popularity score over time

Emotions over time

Sentiment over time

Main themes and topics word cloud

Main sources and themes word cloud

Parent topic: The reports

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Changes are periodically made to the information herein; these changes will be incorporated in new editions of the publication. IBM may make improvements and/or changes in the product(s) and/or the program(s) described in this publication at any time without notice. Any references in this information to non-IBM Web sites are provided for convenience only and do not in any manner serve as an endorsement of those Web sites. The materials at those Web sites are not part of the materials for this IBM product and use of those Web sites is at your own risk. IBM may use or distribute any of the information you supply in any way it believes appropriate without incurring any obligation to you.Licensees of this program who wish to have information about it for the purpose of enabling: (i) the exchange of information between independently created programs and other programs (including this one) and (ii) the mutual use of the information which has been exchanged, should contact: IBM Software Group Attention: Licensing 3755 Riverside Dr. Ottawa, ON K1V 1B7 Canada Such information may be available, subject to appropriate terms and conditions, including in some cases, payment of a fee. The licensed program described in this document and all licensed material available for it are provided by IBM under terms of the IBM Customer Agreement, IBM International Program License Agreement or any equivalent agreement between us.Any performance data contained herein was determined in a controlled environment. Therefore, the results obtained in other operating environments may vary significantly. Some measurements may have been made on development-level systems and there is no guarantee that these measurements will be the same on generally available systems. Furthermore, some measurements may have been estimated through extrapolation. Actual results may vary. Users of this document should verify the applicable data for their specific environment. Information concerning non-IBM products was obtained from the suppliers of those products, their published announcements or other publicly available sources. IBM has not tested those products and cannot confirm the accuracy of performance, compatibility or any other claims related to non-IBM products. Questions on the capabilities of non-IBM products should be addressed to the suppliers of those products. All statements regarding IBM's future direction or intent are subject to change or withdrawal without notice, and represent goals and objectives only. This information contains examples of data and reports used in daily business operations. To illustrate them as completely as possible, the examples include the names of individuals, companies, brands, and products. All of these names are fictitious and any similarity to the names and addresses used by an actual business enterprise is entirely coincidental. If you are viewing this information softcopy, the photographs and color illustrations may not appear.This Software Offering does not use cookies or other technologies to collect personally identifiable information.©

Notices

This information was developed for products and services offered in the U.S.A.

This material may be available from IBM in other languages. However, you may be required to own a copy of the product or product version in that language in order to access it.

IBM may not offer the products, services, or features discussed in this document in other countries. Consult your local IBM representative for information on the products and services currently available in your area. Any reference to an IBM product, program, or service is not intended to state or imply that only that IBM product, program, or service may be used. Any functionally equivalent product, program, or service that does not infringe any IBM intellectual property right may be used instead. However, it is the user's responsibility to evaluate and verify the operation of any non-IBM product, program, or service. This document may describe products, services, or features that are not included in the Program or license entitlement that you have purchased.

IBM may have patents or pending patent applications covering subject matter described in this document. The furnishing of this document does not grant you any license to these patents. You can send license inquiries, in writing, to:

IBM Director of Licensing

IBM Corporation

North Castle Drive

Armonk, NY 10504-1785

U.S.A.

For license inquiries regarding double-byte (DBCS) information, contact the IBM Intellectual Property Department in your country or send inquiries, in writing, to:

Intellectual Property Licensing

Legal and Intellectual Property Law

IBM Japan Ltd.

19-21, Nihonbashi-Hakozakicho, Chuo-ku

Tokyo 103-8510, Japan

The following paragraph does not apply to the United Kingdom or any other country where such provisions are inconsistent with local law: INTERNATIONAL BUSINESS MACHINES CORPORATION PROVIDES THIS PUBLICATION "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF NON-INFRINGEMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Some states do not allow disclaimer of express or implied warranties in certain transactions, therefore, this statement may not apply to you.

This information could include technical inaccuracies or typographical errors. Changes are periodically made to the information herein; these changes will be incorporated in new editions of the publication. IBM may make improvements and/or changes in the product(s) and/or the program(s) described in this publication at any time without notice.

Any references in this information to non-IBM Web sites are provided for convenience only and do not in any manner serve as an endorsement of those Web sites. The materials at those Web sites are not part of the materials for this IBM product and use of those Web sites is at your own risk.

IBM may use or distribute any of the information you supply in any way it believes appropriate without incurring any obligation to you.

Licensees of this program who wish to have information about it for the purpose of enabling: (i) the exchange of information between independently created programs and other programs (including this one) and (ii) the mutual use of the information which has been exchanged, should contact:

IBM Software Group

Attention: Licensing

3755 Riverside Dr.

Ottawa, ON

K1V 1B7

Canada

Such information may be available, subject to appropriate terms and conditions, including in some cases, payment of a fee.

The licensed program described in this document and all licensed material available for it are provided by IBM under terms of the IBM Customer Agreement, IBM International Program License Agreement or any equivalent agreement between us.

Any performance data contained herein was determined in a controlled environment. Therefore, the results obtained in other operating environments may vary significantly. Some measurements may have been made on development-level systems and there is no guarantee that these measurements will be the same on generally available systems. Furthermore, some measurements may have been estimated through extrapolation. Actual results may vary. Users of this document should verify the applicable data for their specific environment.

Information concerning non-IBM products was obtained from the suppliers of those products, their published announcements or other publicly available sources. IBM has not tested those products and cannot confirm the accuracy of performance, compatibility or any other claims related to non-IBM products. Questions on the capabilities of non-IBM products should be addressed to the suppliers of those products.

All statements regarding IBM's future direction or intent are subject to change or withdrawal without notice, and represent goals and objectives only.

This information contains examples of data and reports used in daily business operations. To illustrate them as completely as possible, the examples include the names of individuals, companies, brands, and products. All of these names are fictitious and any similarity to the names and addresses used by an actual business enterprise is entirely coincidental.

If you are viewing this information softcopy, the photographs and color illustrations may not appear.

This Software Offering does not use cookies or other technologies to collect personally identifiable information.

©

© Product Information This document applies to IBM Behavior Based Fan Insight and may also apply to subsequent releases. Copyright Licensed Materials - Property of IBM © Copyright IBM Corp. 2015, 2016. US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. IBM, the IBM logo and ibm.com are trademarks or registered trademarks of International Business Machines Corp., registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the Web at Copyright and trademark information at www.ibm.com/legal/copytrade.shtml. The following terms are trademarks or registered trademarks of other companies: Microsoft, Windows, Windows NT, and the Windows logo are trademarks of Microsoft Corporation in the United States, other countries, or both. Notices

©

Product Information

This document applies to IBM Behavior Based Fan Insight and may also apply to subsequent releases.

Copyright

Licensed Materials - Property of IBM

© Copyright IBM Corp. 2015, 2016.

US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp.

IBM, the IBM logo and ibm.com are trademarks or registered trademarks of International Business Machines Corp., registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the Web at " Copyright and trademark information " at www.ibm.com/legal/copytrade.shtml.

The following terms are trademarks or registered trademarks of other companies:

Microsoft, Windows, Windows NT, and the Windows logo are trademarks of Microsoft Corporation in the United States, other countries, or both.

Parent topic: Notices