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Calculate and predict customer lifetime value

Keep your marketing spend optimized by monitoring current and predicted value of your customers.

Customer LTV—the primary marketing metric

Customer lifetime value (LTV) is a way to measure how strong is your customer base. It indicates the amount of money your customers spend over the time they purchase at yours.

LTV is your primary marketing metric when you try to grow your business. It shows you what customers to prioritize and how to adapt your marketing strategy to maximize profits. Eventually, LTV helps to boost sales and revenue while keeping marketing spend optimized.

Verfacto provides a hassle-free method to monitor, predict, and increase your customer lifetime value. Try it now for free!

Higher LTV is...

  • increased business revenue
  • improved customer retention rate
  • reduced operational costs
  • Did you know? Customer lifetime value is sometimes also referred to as CLV, CLTV, or even LCV.
    Don’t worry, they mean absolutely the same thing. For consistency, we at Verfacto stick to the LTV acronym.

    How do we predict LTV?

    Verfacto automatically calculates and predicts the lifetime value of customers depending on:
  • how they behave on your website,
  • what products they interacted with,
  • other individual characteristics of customers.
  • How to use customer LTV in marketing

    Knowing customer lifetime value is vital. However, this knowledge would lead you nowhere if you don’t know how to incorporate LTV into your marketing. We have collected several use case examples to demonstrate what you can do when you know which customers spend more and why.

    1

    Findings

    LTV analysis showed that customers who buy sample packs have a 70% lower customer LTV and a low second purchase rate.

    Actions

    Set up A/B test to hide sample packs from customers.

    A/B testing proved that customers spend more if they don't see sample packs. Removing samples from the shop lead to an 8% revenue increase.

    2

    Findings

    LTV Smart Segments (customer segments generated by Verfacto Machine Learning algorithms) identified 16 distinctive groups of customers with demographic, purchasing, and behavioral characteristics that significantly affect their lifetime value.

    Actions

    Exported TOP 5 LTV-driven segments and created a Facebook lookalike audience for the biggest spenders.

    Lookalike audience for the biggest spenders brought customers with a 13% higher average LTV within the first month (money they spent in the short term) and 19% higher predicted LTV (money they are expected to spend within a year).

    1

    Findings

    LTV analysis showed that customers who buy sample packs have a 70% lower customer LTV and a low second purchase rate.

    2

    Findings

    LTV Smart Segments (customer segments generated by Verfacto Machine Learning algorithms) identified 16 distinctive groups of customers with demographic, purchasing, and behavioral characteristics that significantly affect their lifetime value.

    Actions

    Set up A/B test to hide sample packs from customers.

    Actions

    Exported TOP 5 LTV-driven segments and created a Facebook lookalike audience for the biggest spenders.

    A/B testing proved that customers spend more if they don't see sample packs. Removing samples from the shop lead to an 8% revenue increase.

    Lookalike audience for the biggest spenders brought customers with a 13% higher average LTV within the first month (money they spent in the short term) and 19% higher predicted LTV (money they are expected to spend within a year).

    Have a question? Ask the Verfacto team and see the platform in action!