Blog
July 18, 2024
Klaviyo Predictive Analytics: AI Guide & 3 Use Cases
Blog
July 18, 2024
Klaviyo Predictive Analytics: AI Guide & 3 Use Cases
Blog
July 18, 2024
Klaviyo Predictive Analytics: AI Guide & 3 Use Cases
Data is the new oil. Klaviyo's predictive analytics can help you make smarter decisions, save time, and drive more Email & SMS sales.
In the ever-evolving world of DTC e-commerce, leveraging data effectively can be the key to boosting sales and enhancing customer loyalty.
Enter… Predictive analytics.
Section 1: What are predictive analytics?
Predictive analytics uses of data, statistical algorithms, and machine learning to identify the likelihood of future outcomes.
This is how Klaviyo's predictive analytics functions, leveraging account-wide & customer-specific data to predict lifetime value, expected date of next order, churn risk & more.
Using this data can lead to more personalised flows & campaigns, which can lift revenues by 5-15% (Idomoo).
Section 2: Why Use Klaviyo’s Predictive Analytics?
Klaviyo integrates predictive analytics directly into its platform, using data from customer interactions, purchase history, and engagement metrics to generate predictions that inform marketing strategies.
Some key benefits:
1. Anticipate Buying Cycles
Predictive analytics forecasts future customer actions, allowing brands to anticipate what products customers might want next and when they are likely to buy. This enables more proactive and personalised marketing.
Example: A brand can send timely reminders and recommendations based on a customer’s purchase patterns.
2. Prevent Churn Risk
Automatically identify customers at risk of leaving your brand & send them timely winback campaigns or flows that reduce churn & re-engage customers. An effective win-back strategy can help recover lapsed customers and increase repeat purchases.
Example: Focusing email campaigns on high churn risk customers with a tailored offer & 'what's new' angle.
3. Tailor Offerings To Customer Budget
Predictive analytics allows you to understand whether a customer will become a 'high roller' or a 'budget shopper'. From there, you can tailor your marketing communications.
Example: sending sales & bundles to 'budget shoppers' in search of the best deal.
Section 3: Finding Predictive Analytics in Klaviyo
Predictive Analytics are enabled by default in Klaviyo provided you meet specific criteria. For a deep dive into how Klaviyo's analytics tools can refine your retention efforts, check out our guide on Mastering Klaviyo DTC Reporting & Analytics.
Source: Klaviyo
To see them for a profile, head to ‘profiles’ & the ‘metrics and insights’ tab.
You’ll then find the below:
Source: Klaviyo
Section 4: Which Predictive Analytics Are Available in Klaviyo?
Expected Date of Next Order
Description and Importance: The Expected Date of Next Order prediction helps brands anticipate when a customer is likely to make their next purchase. This allows businesses to send timely reminders and personalised offers, enhancing customer retention and increasing the likelihood of repeat purchases.
If you're looking for post-purchase email examples to reinforce loyalty, our article 10 Post-Purchase Email Examples to Boost Customer Loyalty and Drive Repeat Sales can help.
Churn Risk Prediction
Description and Importance: The Churn Risk Prediction model identifies customers who are at risk of becoming inactive. By understanding which customers are likely to churn, brands can take proactive steps to re-engage them through targeted campaigns, reducing customer attrition and improving overall retention rates.
Predicted Customer Lifetime Value (CLV)
Description and Importance: Predicted CLV estimates the total revenue a customer is expected to generate over their lifetime with the brand. This metric helps businesses prioritise high-value customers and tailor their marketing strategies accordingly. For example, customers with a higher CLV might receive promotions for premium products, while those with a lower CLV might be targeted with best-sellers or sale items to boost engagement and spending.
Predicted Gender
Description and Importance: Klaviyo will analyse your customer names vs census data & create a predicted gender for each of your subscribers. These can be used to tailor product suggestions & content if your previous analyses has seen different preferences.
Section 5: What are the Key Use Cases?
Expected Date Of Next Order Flow
What is it? The EDONO Flow is an automated email sequence designed to remind customers to reorder consumable products before they run out. Automating these triggers can significantly improve retention—learn more in our guide on 8 Essential Klaviyo Flows to Boost Customer Loyalty.
How does it use predictive analytics? It uses predictive analytics to analyzs past purchase behaviours and determine the optimal time to send reorder reminders. This helps in sending personalised emails to customers just when they are likely to need a refill.
How to use: create a new flow with the date property trigger 'expected date of next order'. Then, send a series of emails reminding them to stock up or re-buy that aligns with their purchasing cycle.
Predicted Gender Flow Splits
What is it? Klaviyo's prediction on the 'likely' gender of a subscriber.
How does it use predictive analytics? Klaviyo's gender prediction algorithm uses a customer's first name and census data to predict their gender as likely male, likely female, or uncertain. This is an educated guess, and the prediction is still an approximation.
How To Use: in flows, create a series of conditional splits based on gender, like the below. Please be aware that this is an approximation not a definite prediction, therefore it's advised to include product information for both sets of customers in each email. However, it's worth testing, whether a female 'hero' image results in an order uptick for predicted female subscribers & the same for 'likely male'.
CLV Segments
What is it? CLV Segments are customer groups segmented based on their predicted Customer Lifetime Value (CLV). By leveraging predictive analytics, brands can build smarter segmentation strategies—our article on 3 Klaviyo Segmentation Strategies to Boost DTC Sales explores how to structure them for maximum impact.
How does it use predictive analytics? It uses predictive CLV models to estimate the total revenue a customer is expected to generate over their lifetime, based on past behaviours and engagement, and patterns from the wider customer set.
How to use: Create segments for low predicted CLV and high predicted CLV customers such as the below. Ensure the high & low CLV segments represent the top & bottom 20% respectively. Then, send campaigns to the relevant segments. Does a customer have a higher CLV? Push items of higher value or more frequent purchases. Lower CLV? Drive your tried-and-true best sellers and some sale items from time to time.
Conclusion
Leveraging Klaviyo's predictive analytics enhances e-commerce marketing by providing valuable insights into customer behaviour.
DTC brands that can use these insights to improve targeting, reduce churn risk, & make predictions about their customers can generate more personalised marketing strategies that boost sales as a result. To further refine your approach, check out our insights on 8 Strategies to Boost Your Open Rates and maximise engagement with every email you send.
Want to learn more about Klaviyo AI?
Book your free Klaviyo audit today, and we'll show you how to use Klaviyo's AI to save time and money and make more personalised decisions that boost your sales.
In the ever-evolving world of DTC e-commerce, leveraging data effectively can be the key to boosting sales and enhancing customer loyalty.
Enter… Predictive analytics.
Section 1: What are predictive analytics?
Predictive analytics uses of data, statistical algorithms, and machine learning to identify the likelihood of future outcomes.
This is how Klaviyo's predictive analytics functions, leveraging account-wide & customer-specific data to predict lifetime value, expected date of next order, churn risk & more.
Using this data can lead to more personalised flows & campaigns, which can lift revenues by 5-15% (Idomoo).
Section 2: Why Use Klaviyo’s Predictive Analytics?
Klaviyo integrates predictive analytics directly into its platform, using data from customer interactions, purchase history, and engagement metrics to generate predictions that inform marketing strategies.
Some key benefits:
1. Anticipate Buying Cycles
Predictive analytics forecasts future customer actions, allowing brands to anticipate what products customers might want next and when they are likely to buy. This enables more proactive and personalised marketing.
Example: A brand can send timely reminders and recommendations based on a customer’s purchase patterns.
2. Prevent Churn Risk
Automatically identify customers at risk of leaving your brand & send them timely winback campaigns or flows that reduce churn & re-engage customers. An effective win-back strategy can help recover lapsed customers and increase repeat purchases.
Example: Focusing email campaigns on high churn risk customers with a tailored offer & 'what's new' angle.
3. Tailor Offerings To Customer Budget
Predictive analytics allows you to understand whether a customer will become a 'high roller' or a 'budget shopper'. From there, you can tailor your marketing communications.
Example: sending sales & bundles to 'budget shoppers' in search of the best deal.
Section 3: Finding Predictive Analytics in Klaviyo
Predictive Analytics are enabled by default in Klaviyo provided you meet specific criteria. For a deep dive into how Klaviyo's analytics tools can refine your retention efforts, check out our guide on Mastering Klaviyo DTC Reporting & Analytics.
Source: Klaviyo
To see them for a profile, head to ‘profiles’ & the ‘metrics and insights’ tab.
You’ll then find the below:
Source: Klaviyo
Section 4: Which Predictive Analytics Are Available in Klaviyo?
Expected Date of Next Order
Description and Importance: The Expected Date of Next Order prediction helps brands anticipate when a customer is likely to make their next purchase. This allows businesses to send timely reminders and personalised offers, enhancing customer retention and increasing the likelihood of repeat purchases.
If you're looking for post-purchase email examples to reinforce loyalty, our article 10 Post-Purchase Email Examples to Boost Customer Loyalty and Drive Repeat Sales can help.
Churn Risk Prediction
Description and Importance: The Churn Risk Prediction model identifies customers who are at risk of becoming inactive. By understanding which customers are likely to churn, brands can take proactive steps to re-engage them through targeted campaigns, reducing customer attrition and improving overall retention rates.
Predicted Customer Lifetime Value (CLV)
Description and Importance: Predicted CLV estimates the total revenue a customer is expected to generate over their lifetime with the brand. This metric helps businesses prioritise high-value customers and tailor their marketing strategies accordingly. For example, customers with a higher CLV might receive promotions for premium products, while those with a lower CLV might be targeted with best-sellers or sale items to boost engagement and spending.
Predicted Gender
Description and Importance: Klaviyo will analyse your customer names vs census data & create a predicted gender for each of your subscribers. These can be used to tailor product suggestions & content if your previous analyses has seen different preferences.
Section 5: What are the Key Use Cases?
Expected Date Of Next Order Flow
What is it? The EDONO Flow is an automated email sequence designed to remind customers to reorder consumable products before they run out. Automating these triggers can significantly improve retention—learn more in our guide on 8 Essential Klaviyo Flows to Boost Customer Loyalty.
How does it use predictive analytics? It uses predictive analytics to analyzs past purchase behaviours and determine the optimal time to send reorder reminders. This helps in sending personalised emails to customers just when they are likely to need a refill.
How to use: create a new flow with the date property trigger 'expected date of next order'. Then, send a series of emails reminding them to stock up or re-buy that aligns with their purchasing cycle.
Predicted Gender Flow Splits
What is it? Klaviyo's prediction on the 'likely' gender of a subscriber.
How does it use predictive analytics? Klaviyo's gender prediction algorithm uses a customer's first name and census data to predict their gender as likely male, likely female, or uncertain. This is an educated guess, and the prediction is still an approximation.
How To Use: in flows, create a series of conditional splits based on gender, like the below. Please be aware that this is an approximation not a definite prediction, therefore it's advised to include product information for both sets of customers in each email. However, it's worth testing, whether a female 'hero' image results in an order uptick for predicted female subscribers & the same for 'likely male'.
CLV Segments
What is it? CLV Segments are customer groups segmented based on their predicted Customer Lifetime Value (CLV). By leveraging predictive analytics, brands can build smarter segmentation strategies—our article on 3 Klaviyo Segmentation Strategies to Boost DTC Sales explores how to structure them for maximum impact.
How does it use predictive analytics? It uses predictive CLV models to estimate the total revenue a customer is expected to generate over their lifetime, based on past behaviours and engagement, and patterns from the wider customer set.
How to use: Create segments for low predicted CLV and high predicted CLV customers such as the below. Ensure the high & low CLV segments represent the top & bottom 20% respectively. Then, send campaigns to the relevant segments. Does a customer have a higher CLV? Push items of higher value or more frequent purchases. Lower CLV? Drive your tried-and-true best sellers and some sale items from time to time.
Conclusion
Leveraging Klaviyo's predictive analytics enhances e-commerce marketing by providing valuable insights into customer behaviour.
DTC brands that can use these insights to improve targeting, reduce churn risk, & make predictions about their customers can generate more personalised marketing strategies that boost sales as a result. To further refine your approach, check out our insights on 8 Strategies to Boost Your Open Rates and maximise engagement with every email you send.
Want to learn more about Klaviyo AI?
Book your free Klaviyo audit today, and we'll show you how to use Klaviyo's AI to save time and money and make more personalised decisions that boost your sales.
Data is the new oil. Klaviyo's predictive analytics can help you make smarter decisions, save time, and drive more Email & SMS sales.
In the ever-evolving world of DTC e-commerce, leveraging data effectively can be the key to boosting sales and enhancing customer loyalty.
Enter… Predictive analytics.
Section 1: What are predictive analytics?
Predictive analytics uses of data, statistical algorithms, and machine learning to identify the likelihood of future outcomes.
This is how Klaviyo's predictive analytics functions, leveraging account-wide & customer-specific data to predict lifetime value, expected date of next order, churn risk & more.
Using this data can lead to more personalised flows & campaigns, which can lift revenues by 5-15% (Idomoo).
Section 2: Why Use Klaviyo’s Predictive Analytics?
Klaviyo integrates predictive analytics directly into its platform, using data from customer interactions, purchase history, and engagement metrics to generate predictions that inform marketing strategies.
Some key benefits:
1. Anticipate Buying Cycles
Predictive analytics forecasts future customer actions, allowing brands to anticipate what products customers might want next and when they are likely to buy. This enables more proactive and personalised marketing.
Example: A brand can send timely reminders and recommendations based on a customer’s purchase patterns.
2. Prevent Churn Risk
Automatically identify customers at risk of leaving your brand & send them timely winback campaigns or flows that reduce churn & re-engage customers. An effective win-back strategy can help recover lapsed customers and increase repeat purchases.
Example: Focusing email campaigns on high churn risk customers with a tailored offer & 'what's new' angle.
3. Tailor Offerings To Customer Budget
Predictive analytics allows you to understand whether a customer will become a 'high roller' or a 'budget shopper'. From there, you can tailor your marketing communications.
Example: sending sales & bundles to 'budget shoppers' in search of the best deal.
Section 3: Finding Predictive Analytics in Klaviyo
Predictive Analytics are enabled by default in Klaviyo provided you meet specific criteria. For a deep dive into how Klaviyo's analytics tools can refine your retention efforts, check out our guide on Mastering Klaviyo DTC Reporting & Analytics.
Source: Klaviyo
To see them for a profile, head to ‘profiles’ & the ‘metrics and insights’ tab.
You’ll then find the below:
Source: Klaviyo
Section 4: Which Predictive Analytics Are Available in Klaviyo?
Expected Date of Next Order
Description and Importance: The Expected Date of Next Order prediction helps brands anticipate when a customer is likely to make their next purchase. This allows businesses to send timely reminders and personalised offers, enhancing customer retention and increasing the likelihood of repeat purchases.
If you're looking for post-purchase email examples to reinforce loyalty, our article 10 Post-Purchase Email Examples to Boost Customer Loyalty and Drive Repeat Sales can help.
Churn Risk Prediction
Description and Importance: The Churn Risk Prediction model identifies customers who are at risk of becoming inactive. By understanding which customers are likely to churn, brands can take proactive steps to re-engage them through targeted campaigns, reducing customer attrition and improving overall retention rates.
Predicted Customer Lifetime Value (CLV)
Description and Importance: Predicted CLV estimates the total revenue a customer is expected to generate over their lifetime with the brand. This metric helps businesses prioritise high-value customers and tailor their marketing strategies accordingly. For example, customers with a higher CLV might receive promotions for premium products, while those with a lower CLV might be targeted with best-sellers or sale items to boost engagement and spending.
Predicted Gender
Description and Importance: Klaviyo will analyse your customer names vs census data & create a predicted gender for each of your subscribers. These can be used to tailor product suggestions & content if your previous analyses has seen different preferences.
Section 5: What are the Key Use Cases?
Expected Date Of Next Order Flow
What is it? The EDONO Flow is an automated email sequence designed to remind customers to reorder consumable products before they run out. Automating these triggers can significantly improve retention—learn more in our guide on 8 Essential Klaviyo Flows to Boost Customer Loyalty.
How does it use predictive analytics? It uses predictive analytics to analyzs past purchase behaviours and determine the optimal time to send reorder reminders. This helps in sending personalised emails to customers just when they are likely to need a refill.
How to use: create a new flow with the date property trigger 'expected date of next order'. Then, send a series of emails reminding them to stock up or re-buy that aligns with their purchasing cycle.
Predicted Gender Flow Splits
What is it? Klaviyo's prediction on the 'likely' gender of a subscriber.
How does it use predictive analytics? Klaviyo's gender prediction algorithm uses a customer's first name and census data to predict their gender as likely male, likely female, or uncertain. This is an educated guess, and the prediction is still an approximation.
How To Use: in flows, create a series of conditional splits based on gender, like the below. Please be aware that this is an approximation not a definite prediction, therefore it's advised to include product information for both sets of customers in each email. However, it's worth testing, whether a female 'hero' image results in an order uptick for predicted female subscribers & the same for 'likely male'.
CLV Segments
What is it? CLV Segments are customer groups segmented based on their predicted Customer Lifetime Value (CLV). By leveraging predictive analytics, brands can build smarter segmentation strategies—our article on 3 Klaviyo Segmentation Strategies to Boost DTC Sales explores how to structure them for maximum impact.
How does it use predictive analytics? It uses predictive CLV models to estimate the total revenue a customer is expected to generate over their lifetime, based on past behaviours and engagement, and patterns from the wider customer set.
How to use: Create segments for low predicted CLV and high predicted CLV customers such as the below. Ensure the high & low CLV segments represent the top & bottom 20% respectively. Then, send campaigns to the relevant segments. Does a customer have a higher CLV? Push items of higher value or more frequent purchases. Lower CLV? Drive your tried-and-true best sellers and some sale items from time to time.
Conclusion
Leveraging Klaviyo's predictive analytics enhances e-commerce marketing by providing valuable insights into customer behaviour.
DTC brands that can use these insights to improve targeting, reduce churn risk, & make predictions about their customers can generate more personalised marketing strategies that boost sales as a result. To further refine your approach, check out our insights on 8 Strategies to Boost Your Open Rates and maximise engagement with every email you send.
Want to learn more about Klaviyo AI?
Book your free Klaviyo audit today, and we'll show you how to use Klaviyo's AI to save time and money and make more personalised decisions that boost your sales.
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Other Blogs
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Check our other project Blogs with useful insight and information for your businesses
Other Blogs
Other Blogs
Check our other project Blogs with useful insight and information for your businesses