from typing import Dict, List, Union rfm_info_tabs: List[Dict[str, Union[str, List[Dict[str, str]]]]] = [ { "type": "InfoTabs", "name": "Most valuable fans", "items": [ { "name": "Most valuable fans", "description": "These fans are among 25% of the fanbase with the most recent transaction dates. Their purchased item/ticket count is at least 4 and they spend more than 75% of the fan base does.", }, { "name": "Action", "description": 'These fans might be your superfans, champions, ambassadors. They are more eager to buy early releases or bundles/VIP packages. For being influencers, make them feel special as they promote your brand (create positive word-of-mouth amongst their circles). Give them early access to special content and exclusive offers. Create for them "Access All Areas" type of loyalty program.', }, ], }, { "type": "InfoTabs", "name": "Loyal fans", "items": [ { "name": "Loyal fans", "description": 'These fans are among 50% of the fanbase with the most recent transaction dates. They tend to buy at least 2 items/tickets and they might be more price-conscious. The main differences to "the most valuable fans" are their lower recency and lower frequency.', }, { "name": "Action", "description": 'These fans can be a good growth and upsell target. To transition them to "the most valuable fans", engage them by asking reviews or selling them bundles with good price/value ratio and offer special upsell offers, or occasional value-add discounts. They might be ready to buy higher quality merch/content.', }, ], }, { "type": "InfoTabs", "name": "Potential new valuable fans", "items": [ { "name": "Potential new valuable fans", "description": "These fans are among 50% of the fanbase with the most recent transaction dates.They are buying only one item but their purchase has been more valuable than purchases of 75% of the fan base.", }, { "name": "Action", "description": "These fans have proved that they are ready to spend money. Find ways to cross-sell them or offer free trials/free deliveries, for example.", }, ], }, { "type": "InfoTabs", "name": "Fans to win back", "items": [ { "name": "Fans to win back", "description": "These are the fans with a high item/ticket count and they have spent more than average but it's been a long time since their last purchase. 75% of the fanbase have a more recent transaction date compared to this segment.", }, { "name": "Action", "description": "The segment that used to be a valuable set of fans. Win back their interest by engaging actively with them - reconnect with personalized offers and content. Send a survey to understand why they have stopped interacting with your brand.", }, ], }, { "type": "InfoTabs", "name": "Asleep fans", "items": [ { "name": "Asleep fans", "description": "These fans tended to be active buyers (bought at least 2-3 items before) but it's been some time since their last purchase. 50-75% of the fanbase have a more recent transaction date compared to this segment.", }, { "name": "Action", "description": "If not acted upon, you may lose these fans. Offer them products/content that current loyal fans are enjoying. Special discounts might interest them. Try catchy calls-to-action in ads and subject lines in emails.", }, ], }, { "type": "InfoTabs", "name": "One time interaction fans", "items": [ { "name": "One time interaction fans", "description": "These are the fans with only 1 purchase with a variety of transaction values. Their transactions have occurred in the range of very recent dates up to a very long time ago.", }, { "name": "Action", "description": 'If "the loyal fans" is a group that can be transitioned into "the most valuable fans" segment then these fans can be grown into "the loyal fans" segment. For that, you can interact with them regularly (more often) to create interest by providing relevant and free content to keep them engaged. Grow the artist awareness for them, keep the artist in their top-of-mind.', }, ], }, ] ml_info_tabs: List[Dict[str, Union[str, List[Dict[str, str]]]]] = [ { "type": "InfoTabs", "name": "", "items": [ { "name": "", "description": "Each data collection is unique and therefore requires a dynamic approach. Machine learning-based clustering algorithms help to discover hidden patterns from data and create groups of fans that share similar attributes.", }, { "name": "", "description": "The traditional segmenting relies on predefined descriptions but it cannot cover all the different possibilities data may contain. Nor can it handle outliers or missing data well. The machine learning models tackle these issues and find the most relevant data points for describing segments.", }, { "name": "", "description": "The keywords-based clustering buckets fans by their most characteristic and important attributes. These keywords help to distinguish groups of fans for smarter personalized marketing.", }, ], }, ] superfans_info_tabs: List[Dict[str, Union[str, List[Dict[str, str]]]]] = [ { "type": "InfoTabs", "name": "", "items": [ { "name": "", "description": "Superfans are your most engaged fans. The engagement score is calculated using data points from events, purchases, digital assets, streaming platforms, and social media. Each data point describes actions taken by fans or expresses fan behavior. These data points as attributes are then mapped to different levels of engagement.", }, { "name": "", "description": 'The accuracy of superfan scoring depends on data quality. The more data points you add to the scoring algorithm, the more precise the levels. The most valuable segment is called "Most Intense Superfans" followed by different Superfan levels from 2 to 5.', }, ], }, ]