5 ways using predictive analytics in marketing can help you deliver what your customers want

73% of shoppers expect brands to understand their unique needs.

It’s clear that today’s consumers crave a more personalized online shopping experience. And in the past, ecommerce brands would have needed that elusive crystal ball to pinpoint the ideal time to share a new product line or promote a sale.

But now, thanks to predictive analytics, it’s easy to anticipate what customers want—and give it to them. These AI-driven insights help you understand what customers will do and when, so you can create a more strategic business plan and build more impactful marketing campaigns.

Brands are already using the information derived from predictive analytics to tackle a range of business goals, including:

• Improving profit margins
• Reducing customer churn
• Building customer loyalty

Predictive analytics in marketing can deliver insights that keep you one step ahead of your customers—and the competition. Here’s how.

1. Message customers when they’re most likely to buy again

You want to get in front of customers when they’re most motivated to make a purchase. It’s easier said than done, but Klaviyo predictive analytics makes it possible.

Klaviyo AI analyzes both the average time between a customer’s orders and the date they’re most likely to place another one. This information empowers you to identify customers with similar buying cycles, then target them by:

• Triggering a flow that cross-sells additional, relevant products near someone’s expected date of next order
• Branching flows based on expected date of next order to avoid sending incentives and discounts to customers who are already likely to buy
• Creating on-site forms targeting customers who are expected to order soon and presenting them with a deal designed to increase their order value, such as a bundle or “buy two, get one free” offer
• Sending infrequent customers special offers encouraging them to buy more often

Men’s grooming brand Every Man Jack uses predictive analytics to drive repeat sales by anticipating when each customer will likely make their next order. The marketing team then sends reorder flows slightly before, on, or after this predicted date.

It’s a big improvement from their previous marketing platform, where the timeline for the replenishment flow wasn’t customizable. Now, predictive analytics generates 12.4% of Klaviyo-attributed revenue for the brand.

“I trust and value Klaviyo AI because it saves me time, it helps me leverage our customer data to personalize our email timing and strategies,” says Troy Petrunoff, senior retention marketing manager at Every Man Jack. “Most importantly, I maintain complete control over how and when it’s used.”

I trust and value Klaviyo AI because it saves me time.

2. Send targeted campaigns based on spending potential

The insights derived from predictive analytics can also help you create key segments based on each customer’s spending potential, such as their average order value (AOV) and their historic, predicted, and total customer lifetime value (CLV).

Using this data, you can create marketing initiatives such as:

• Branching your flows based on AOV or CLV, then:
  • Promoting higher-ticket items to VIP customers with a high AOV or CLV
  • Creating incentives designed to encourage customers who don’t spend a lot to add more items to their orders
• Building segments based on high historic, predicted, or total CLV and using them to find new customers via lookalike audiences in Facebook Ads or similar audiences in Google Ads

In 2023, The Willow Tree Boutique grew Klaviyo-attributed revenue by 44.6% YoY. Part of their strategy involved using predictive analytics to promote luxury items to customers with proven spending power—a predicted CLV over $500, or an AOV over $150.

Within the first 6 months of using Klaviyo predictive analytics, the team saw a 53.1% HoH growth in revenue for H2 2023.

“After we started sending campaigns to segments created with Klaviyo’s predictive analytics, all our metrics improved, and our revenue improved drastically,” says Jade Richardson, email marketing strategist at Agital, The Willow Tree Boutique’s digital marketing agency. “It taught us so much about the subscriber base—when they shop, how they shop, etc.”

“It has been fundamental to nailing down best practices for the brand,” Richardson adds. “It really opened up a whole new world to us.”

After we started sending campaigns to segments created with Klaviyo’s predictive analytics, all our metrics improved.

3. Find and reward your most loyal customers

Klaviyo displays the historic number of orders for each customer. That information is valuable because you can use it to build your own loyalty framework in Klaviyo—for example, by targeting a group of your most frequent purchasers with a free gift or exclusive early access to a sale.

But Klaviyo AI takes it one step further by forecasting how many more orders a customer is likely to place in the future. Based on that information, you can build segments dividing customers who are likely to purchase again from those who aren’t, then build unique content for your campaigns, flows, and retargeting efforts across Facebook Ads or Google Ads.

4. Deliver more personalized messages based on demographics

For industries like health, personal wellness, and retail, gender demographic predictions can help brands deliver personalized recommendations and targeted campaigns.

Klaviyo AI makes gender demographic predictions by matching the first name of each customer profile with census data. (Note: Because this prediction is an approximation, it’s a good idea to include some information for both genders within your campaigns.)

Officewear brand Ministry of Supply uses Klaviyo predictive analytics in their email marketing campaigns to segment emails by predicted gender, sending two versions of each campaign every week.

“Since we started segmenting our audience using Klaviyo’s predicted gender, the content or even just the subject line is more specific to the gender that the subscriber is shopping for,” explains Colleen Maloney, senior marketing manager at Ministry of Supply.

The result? A 47.3% YoY increase in campaign revenue and a 36.15% YoY increase in overall revenue from email.

5. Prevent customer churn

Churn risk prediction is a calculation of how likely or unlikely your customers are to make another purchase. Even if most of your customers buy from your brand only once or twice, knowing the average churn risk prediction for key segments can help you better understand customer behavior—and act accordingly.

For example, since a lower churn risk percentage indicates a higher likelihood that a customer will purchase again, the average churn risk for VIP customers may be lower than the average for your entire customer base.

Note: While churn risk is useful for understanding audience behavior, segmenting audiences or triggering flows based on this metric isn’t the best option. Use expected date of next order instead.

Start using Klaviyo predictive analytics today

Using predictive analytics AI in marketing doesn’t have to be complicated—and you don’t need a team of data scientists, either.

Klaviyo AI quickly forecasts everything you need to know, making it easier than ever before to deliver the relevant, timely, and personalized experiences that make your brand stand out.

It’s time to go beyond historical data analysis—and look to the future.

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