06 Jun Using predictions to get your customers to buy again
If you sell a consumable product, you want your customers to buy again and again. When a product gets used up or wears out, it makes sense to send a reminder to customers to refill, replace, or repurchase that product or a similar product. We refer to this as a “replenishment” or “repurchase” campaign.
We’ve all read “best practices” blogs about how replenishment campaigns should be executed. If you’ve read as many articles as we have, you’ll notice they often make common recommendations:
– Identify an item that should be replenished
– Calculate the average repurchase time for that item
– Track if users make the purchase as expected
– Repeat for every user-item replenish-able pair
If you follow these recommendations, you will likely begin manually segmenting customers and setting up static item reminders to go out 21, 30, or 60 days after a customer’s purchase. But is this the smartest solution?
Consider how much time and effort this requires to build out and maintain these triggers, while measuring their ultimate effectiveness.
Are all of your customers using these products within the same time interval? If not, you risk a series of mistimed emails that could seem intrusive, pushy, or possibly redundant. This blunder defeats the point of a repurchase campaign entirely.
The marketing experts at Natural Healthy Concepts have discovered a more robust and scalable replenishment solution with ReSci’s Artificial Intelligence platform. Predictions are automatically made on brands’ already existing data, and timely, relevant and accurate reminder emails are sent with little additional work from the marketer. But the question remains—is this solution effective?
The power of data science
The Buy Again stage is powered by an algorithm that automatically assigns the correct replenishment interval for each product, down to each individual user. The stage scans the entire product catalog and finds items that are frequently repurchased by customers, with no effort required from the marketer.
The algorithm then identifies if a customer on any given day qualifies for a replenishment event. Then, each day, a subset of users will be targeted with a personalized email, sent during their best predicted qualification interval and their best predicted time of day. All the marketer needs to do is feed the machine content, and the AI will do the rest.
Check out this real life example below, sent by ReSci’s AI:
On average ReSci’s partners have seen ~50% conversion rate for these replenishment campaigns, with the maximum rate a staggering 85%.
This automated data-driven approach to your repurchase campaigns is easier to set up and much more powerful and scalable than any manual campaign.
Ultimately, emailing customers to remind them to repurchase an item, or buy a related item, is a great way to improve repeat purchases, customer retention and drive sales.
The old method of manually setting up repurchase reminders that go out at human-defined intervals has become dated, and many marketers are realizing the inefficiencies in these campaigns.
The smarter, more profitable way to engage customers is by utilizing predictive intelligence and automation, as shown by ReSci’s platform and its Buy Again stage. The AI takes care of all of your A/B testing needs and saves you time and wasted experiments, and cross-prioritizes these emails with other stages to ensure the highest statistical likelihood of a conversion.
What would it mean for your marketing team and your company if you could do all of this and more for the complete customer lifecycle, across 19 different stages? What would an AI-driven conversion rate of 50%- 85% for your repurchase campaigns do for your bottom line?
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ReSci is a team of marketers and data scientists on a mission to democratize AI. We make powerful recommendations and predictions accessible to brands. Find out how we can help you connect with your customers.
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