Predictive scoring for your activation scenarios
Posted: Thu Dec 05, 2024 6:47 am
Predictive scoring is a topic that is increasingly attracting marketers' interest, allowing them to push their activation campaigns to the next level. Following the success of a workshop given at the Activation Day , the experts at Moonfish , Actito's technology partner, share in this article the content of this workshop to help you see more clearly about predictive scoring, its use cases and its implementation.
Article_Predictive-Scoring
Summary
What is predictive scoring?
From mass market activation to advanced personalization
The different types of predictive scores
Key indicators of predictive scoring
How are predictive scores calculated?
Setting up APS in Actito
What is predictive scoring?
Predictive scoring is an advanced marketing segmentation technique list of austria whatsapp phone numbers that uses artificial intelligence (AI) and machine learning algorithms to predict future customer behavior. It assigns a score to each customer based on their likelihood of taking a specific action, such as purchasing, clicking, or unsubscribing.
Unlike traditional scoring which is mainly based on predefined rules and historical data, predictive scoring goes further by analyzing vast amounts of data (behavioral, demographic, transactional, etc.) to identify complex patterns and correlations invisible to the naked eye.
AI and machine learning play a key role in predictive scoring. Algorithms continuously learn from data, adapting and improving over time to provide increasingly accurate predictions. This allows them to detect weak signals, anticipate trends and personalize scores in real time for each individual.
The main advantages of predictive scoring are:
Better customer knowledge through predictive insights
Ultra-personalized and relevant marketing campaigns
Optimization of marketing resources by targeting the most receptive customers
Improved conversion rates and customer loyalty
Anticipation and prevention of risks (attrition, non-payment, etc.)
In short, predictive scoring allows you to move from reactive to proactive marketing, by predicting future customer behaviors rather than simply reacting to their past actions. It is a powerful tool for optimizing the entire customer journey .
From mass market activation to advanced personalization
If you have ever wondered what metrics to use to select the right customers and content, then this article will interest you. Marketing automation solutions have transformed CRM activation strategies from mass market campaigns to more differentiated and personalized content.
The first step was to set up activation sequences based on triggers or segmentations that take into account frequency, recency and purchase value. However, the real power of marketing automation lies in its ability to exploit all available data for hyper-personalization at all levels (trigger, moment, targeting, segmentation, content, channel, etc.).
This is where predictive scoring comes in , which allows you to assign a score to each customer to sort and classify them according to the value of this score, or to identify the specific product/content to offer them, depending on the desired use case.
Predictive scoring - campaign evolution
The different types of predictive scores
Actito has implemented the Actito Predective Scores (APS) in partnership with Moonfish. These scores are based on typical use cases of marketing issues and can be activated from the data already available in Actito. There are 2 types of APS:
" Global APS ", not linked to a specific product category
" Product APS ", corresponding to the affinity of customers for a specific group of products
Global APS
There are 3 main global APS, corresponding to different business situations:
Customer Future Lifetime Value (CFLV) : to identify high-potential customers and offer them a special deal. This algorithm predicts the future value of each customer in €.
Churn Decisive Moment : to reduce attrition by sending the “last chance offer” at the right time, just before customers become inactive. This algorithm predicts the date beyond which a customer is most likely not to come back.
Personalized Product Recommendations : to highlight in an email the products that each customer is most likely to buy, based on their purchase and visit history.
Promotional Aptitude : To target customers who are most sensitive to promotions or exclude those with a low propensity to purchase on promotion. This algorithm calculates a promotion sensitivity score for each customer.
APS Products
Product APSs help identify customers or prospects who are most likely to purchase a specific type of product. They are relevant in 2 situations:
Product affinity - upsell version : to carry out a clearance campaign on a group of products by targeting customers with the highest affinity score for these products.
Product affinity - cross-sell version : to carry out a cross-sell campaign targeting customers who have never purchased from a product range but have a high affinity score for it.
Predictive Scoring: APS Products
Key indicators of predictive scoring
Predictive scoring allows you to calculate different key indicators to assess the potential and risk of each customer. These indicators are real compasses to guide your marketing actions and optimize the allocation of your resources. Here are the main indicators to follow:
Engagement score
The engagement score is a visual indicator that allows you to check at a glance the degree of engagement of a profile towards your brand. This figure alone will allow you to distinguish the profiles that are highly engaged from the profiles that should instead be targeted by a reactivation campaign .
More than the current level of engagement of your profiles, this indicator will allow you to measure the impact of your campaigns on this engagement, by following its evolution over time. You will thus be able to identify the most effective levers to boost the engagement of your customers.
Conversion probability and customer lifetime value (LTV)
Conversion probability indicates the propensity of a prospect or customer to make a purchase or any other desired action (registration, download, store visit, etc.). This indicator allows you to prioritize your leads and customers according to their conversion potential, and thus focus your efforts on the most promising ones.
Customer Lifetime Value ( CLV) is a projection of the total value a customer will generate over the course of their relationship with your company. By cross-referencing conversion probability with CLV, you can identify your most valuable customers over the long term and tailor your retention strategies accordingly.
Attrition risk and detection of at-risk customers
Churn risk measures the likelihood that a customer will end their relationship with your business. This score is calculated by analyzing various warning signals, such as a decrease in purchase frequency, decreased engagement, repeated complaints, etc.
By segmenting your customers based on their churn score, you can implement targeted preventative actions for the customers most at risk: retention offers, reward programs, personalized communications, etc. The goal is to intervene at the right time to avoid churn and extend the customer's lifespan.
Monitoring the evolution of indicators using predictive scoring
One of the great benefits of predictive scoring is being able to track the evolution of these key indicators over time. By regularly recalculating the scores, you can measure the impact of your marketing actions and adjust your strategy accordingly.
Thanks to the Actito Predictive Scoring module, you have a complete dashboard to monitor your main indicators: customer engagement score, number of scenario executions, conversion rate, etc. You can therefore identify key moments in the customer journey and quickly detect reactivation opportunities when the customer relationship is at risk.
How are predictive scores calculated?
Predictive scoring algorithms are based on machine learning. They learn from past customer behaviors to derive predictive information and apply it to current behaviors. The more the algorithm is "fed" with a large volume of varied data, the more reliable the prediction will be.
Actito Predictive Score automatically retrieves learning data from your Actito data, without requiring intervention from your IT teams.
Article_Predictive-Scoring
Summary
What is predictive scoring?
From mass market activation to advanced personalization
The different types of predictive scores
Key indicators of predictive scoring
How are predictive scores calculated?
Setting up APS in Actito
What is predictive scoring?
Predictive scoring is an advanced marketing segmentation technique list of austria whatsapp phone numbers that uses artificial intelligence (AI) and machine learning algorithms to predict future customer behavior. It assigns a score to each customer based on their likelihood of taking a specific action, such as purchasing, clicking, or unsubscribing.
Unlike traditional scoring which is mainly based on predefined rules and historical data, predictive scoring goes further by analyzing vast amounts of data (behavioral, demographic, transactional, etc.) to identify complex patterns and correlations invisible to the naked eye.
AI and machine learning play a key role in predictive scoring. Algorithms continuously learn from data, adapting and improving over time to provide increasingly accurate predictions. This allows them to detect weak signals, anticipate trends and personalize scores in real time for each individual.
The main advantages of predictive scoring are:
Better customer knowledge through predictive insights
Ultra-personalized and relevant marketing campaigns
Optimization of marketing resources by targeting the most receptive customers
Improved conversion rates and customer loyalty
Anticipation and prevention of risks (attrition, non-payment, etc.)
In short, predictive scoring allows you to move from reactive to proactive marketing, by predicting future customer behaviors rather than simply reacting to their past actions. It is a powerful tool for optimizing the entire customer journey .
From mass market activation to advanced personalization
If you have ever wondered what metrics to use to select the right customers and content, then this article will interest you. Marketing automation solutions have transformed CRM activation strategies from mass market campaigns to more differentiated and personalized content.
The first step was to set up activation sequences based on triggers or segmentations that take into account frequency, recency and purchase value. However, the real power of marketing automation lies in its ability to exploit all available data for hyper-personalization at all levels (trigger, moment, targeting, segmentation, content, channel, etc.).
This is where predictive scoring comes in , which allows you to assign a score to each customer to sort and classify them according to the value of this score, or to identify the specific product/content to offer them, depending on the desired use case.
Predictive scoring - campaign evolution
The different types of predictive scores
Actito has implemented the Actito Predective Scores (APS) in partnership with Moonfish. These scores are based on typical use cases of marketing issues and can be activated from the data already available in Actito. There are 2 types of APS:
" Global APS ", not linked to a specific product category
" Product APS ", corresponding to the affinity of customers for a specific group of products
Global APS
There are 3 main global APS, corresponding to different business situations:
Customer Future Lifetime Value (CFLV) : to identify high-potential customers and offer them a special deal. This algorithm predicts the future value of each customer in €.
Churn Decisive Moment : to reduce attrition by sending the “last chance offer” at the right time, just before customers become inactive. This algorithm predicts the date beyond which a customer is most likely not to come back.
Personalized Product Recommendations : to highlight in an email the products that each customer is most likely to buy, based on their purchase and visit history.
Promotional Aptitude : To target customers who are most sensitive to promotions or exclude those with a low propensity to purchase on promotion. This algorithm calculates a promotion sensitivity score for each customer.
APS Products
Product APSs help identify customers or prospects who are most likely to purchase a specific type of product. They are relevant in 2 situations:
Product affinity - upsell version : to carry out a clearance campaign on a group of products by targeting customers with the highest affinity score for these products.
Product affinity - cross-sell version : to carry out a cross-sell campaign targeting customers who have never purchased from a product range but have a high affinity score for it.
Predictive Scoring: APS Products
Key indicators of predictive scoring
Predictive scoring allows you to calculate different key indicators to assess the potential and risk of each customer. These indicators are real compasses to guide your marketing actions and optimize the allocation of your resources. Here are the main indicators to follow:
Engagement score
The engagement score is a visual indicator that allows you to check at a glance the degree of engagement of a profile towards your brand. This figure alone will allow you to distinguish the profiles that are highly engaged from the profiles that should instead be targeted by a reactivation campaign .
More than the current level of engagement of your profiles, this indicator will allow you to measure the impact of your campaigns on this engagement, by following its evolution over time. You will thus be able to identify the most effective levers to boost the engagement of your customers.
Conversion probability and customer lifetime value (LTV)
Conversion probability indicates the propensity of a prospect or customer to make a purchase or any other desired action (registration, download, store visit, etc.). This indicator allows you to prioritize your leads and customers according to their conversion potential, and thus focus your efforts on the most promising ones.
Customer Lifetime Value ( CLV) is a projection of the total value a customer will generate over the course of their relationship with your company. By cross-referencing conversion probability with CLV, you can identify your most valuable customers over the long term and tailor your retention strategies accordingly.
Attrition risk and detection of at-risk customers
Churn risk measures the likelihood that a customer will end their relationship with your business. This score is calculated by analyzing various warning signals, such as a decrease in purchase frequency, decreased engagement, repeated complaints, etc.
By segmenting your customers based on their churn score, you can implement targeted preventative actions for the customers most at risk: retention offers, reward programs, personalized communications, etc. The goal is to intervene at the right time to avoid churn and extend the customer's lifespan.
Monitoring the evolution of indicators using predictive scoring
One of the great benefits of predictive scoring is being able to track the evolution of these key indicators over time. By regularly recalculating the scores, you can measure the impact of your marketing actions and adjust your strategy accordingly.
Thanks to the Actito Predictive Scoring module, you have a complete dashboard to monitor your main indicators: customer engagement score, number of scenario executions, conversion rate, etc. You can therefore identify key moments in the customer journey and quickly detect reactivation opportunities when the customer relationship is at risk.
How are predictive scores calculated?
Predictive scoring algorithms are based on machine learning. They learn from past customer behaviors to derive predictive information and apply it to current behaviors. The more the algorithm is "fed" with a large volume of varied data, the more reliable the prediction will be.
Actito Predictive Score automatically retrieves learning data from your Actito data, without requiring intervention from your IT teams.