AI is everywhere now. We do not know many brands that do not use it in one way or another, whether it is writing copy, generating graphics or reporting. It is speeding up business, making marketing more efficient and helping brands beat their KPIs year after year.

Did you know that Klaviyo also has its own built-in AI? That is right. It can help you generate content for your emails to add that professional touch, even if you are just an amateur marketer. But we are not here to discuss images and copy today. We want to bring your attention to another incredible AI feature: Klaviyo's predictive analytics.

What Is Predictive Analytics?

Predictive analytics is essentially Klaviyo's way of connecting the dots between the information you have provided and any gaps in your database. While not always 100% accurate, it can help you better understand the types of people in your database, how much they are likely to spend, when they are likely to purchase again and what types of products they are most interested in, to name a few.

Using Gender Prediction to Refine Segmentation

One feature within Klaviyo's Predictive Analytics is gender prediction. Klaviyo can scan customer names, browsing behaviour and purchase data (via Shopify integrations) to form an assumption about preferred gender.

While not always perfectly accurate, this predictive data can be incredibly helpful for brands with gender-specific products. For example, a hosiery brand can segment flows into two categories without directly asking customers for gender information. You can also use show/hide blocks within campaigns to dynamically personalise product recommendations based on Klaviyo's predicted insights. This lets you leverage predictive segmentation without adding friction to your sign-up forms.

Estimating Customer Lifetime Value

Customer spending patterns are more predictable than you may think. Once Klaviyo catches wind of the average order time, value and return rate of your database, it can help predict how much a customer will purchase over time. Say you are a department store selling a range of products at different prices. Those who purchase smaller goods for their first order may cap around $1,000 AUD in total lifetime spend, while those who purchase larger goods for their first order may be willing to spend $10,000 or more.

While these are just estimates, they let you comprehend who your predicted low, mid and high-value customers are. From here, you can send targeted campaigns each featuring products within their price ranges to help elevate sales, boost relationships, and potentially push their predicted value higher than initially gauged.

Predictive Analytics: Next Order Date

Like lifetime value, Klaviyo can estimate when a customer is likely to purchase again based on previous orders and browsing activity. This allows you to send customers emails at the right time to inspire purchase intent.

Similar to a replenishment flow, you can use the next order date as a flow trigger to meet customers at a time when they are likely to spend, or when their need for your product has developed once more. You can even use this trigger as a supplement to a regular winback trigger, meaning each customer will receive your "I miss you" email at a slightly different interval based on their perceived shopping patterns. We recommend testing this trigger against a traditional winback or replenishment and comparing results to make the most of your database.

Predictive Analytics Can Help Your Brand Grow

Without the need for excessive data processing or reporting, using predictive analytics in email marketing helps you take advantage of common shopping patterns and trends in your database to improve ROI, and this is only the beginning.

Klaviyo can also predict age, total number of orders, churn rates, time between orders and next order values to help you build a strategy that reflects your customers' needs and wants. Email by Design has got you.