Predictive marketing automation: the new frontier of CLTV optimization

Predictive marketing automation: the new frontier of CLTV optimization

Automation represents a major innovation in what concerns the processes and management of an e-commerce business. And it should be pointed out that when we talk about marketing automation, we are not only referring to the post-purchase follow up email cycle.

In the e-commerce world, automation has taken on a very important role, as it streamlines processes and simplifies internal and external management.
This, in turn, also goes a long way toward increasing Customer Time Life Value, making the relationship between customers and the company more satisfying.

In recent months, then, automation processes have become even more valuable, as acquisition costs have risen sharply due to interventions in cookie regulation.

The role of marketing automation in e-commerce processes

Until a few years ago, when people talked about automation, they referred to the cart retrieval process or the request for post-purchase reviews. Today, the role of marketing automation has become more structured and complex, but more importantly, more useful.

For example, one of the features of automation today, is to customize the ecommerce home, based on what is most suitable for the customer. But not only that, because automation also allows you to choose the most likely time to show products to customers. The experience becomes individual in every detail.

A very helpful tool for automation processes is Klaviyo.

Let's find out what it is all about.

Klaviyo is a vertical CRM for e-commerce with machine learning that allows you to predict:

• date of the next order for each customer;
• the customer's total future spending;
• the possible risk of fraud;
• the expected CLTV;
• the average reorder time;
• the gender purchase predictivity.

Consider what these values mean in terms of data. Predicting the date of the customer's next purchase means being able to plan targeted marketing actions, such as an ad hoc nurturing email cycle where other related products and possible usage solutions are shown.

Tied immediately to this is the second value, which is the customer's total future spending. If we know the customer's buying power, we also know how to tailor the offer.

For example, if our e-commerce sells sportswear and our customer buys brand-name sneakers around September, we know that, most likely, he might want to buy sportswear such as sweatshirts, pants, or other items for playing sports during the winter towards the end of October. If she spent "X" amount on branded running shoes the first time, her purchasing power the next time will probably be the same or greater, but not less. This awareness gives us ample room to maneuver in our marketing strategies.

The other points in the list are interesting because they give us insight into how to move in the market and how to structure our strategy.But Klaviyo's capabilities are not only these listed of course. Its scope is very broad in terms of automation.

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What does this mean for an ecommerce manager?

It makes it possible to profile and segment users into homogeneous groups and send them a personalized email, at the most suitable time, thus increasing, the number of orders and the average order value.

One absolutely important thing is to define the users' customer journey a priori in order to understand, then, how to manage automations properly.

It can be useful to shorten the CJ for the first purchase to send content and information that makes it easier for the user to make a choice, supported by correct motivations. An example could be a whole series of "How To" style articles, with respect to how they can solve a possible problem with the product the customer purchased.

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Example. Purchase of a kitchen appliance.

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Content that could be shared by email to the customer: How to clean the electric whisk effectively.

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In conclusion:

Klaviyo provides really incredible tools that allow you to get to a very high degree of performance.

What certainly makes the difference is the onboarding, so the whole process of analysis (buyer persona, CJ, behavioral patterns) that needs to be there and the subsequent implementation, then, of marketing automation.

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