1 - Loyalty programs

Loyalty programs exist in all shapes and sizes. Take the coupons from supermarkets, for example, or VIP cards from stores or casinos. All these solutions have the purpose to make you return as a customer and save for prizes or some other form of reward. Loyalty programs have been proven to be successful, but can sometimes still backfire. The biggest drawback of a conventional loyalty program is the lack of interaction with the customer. Usually, the reward is predetermined. Loyalty programs however, can be a connection between your online and your offline store. You can, for instance, try to stimulate repeat purchases online after your customers have been saving up loyalty points in your physical store. Try to integrate your loyalty program into your whole customer journey as best as you can.

There's already a plethora of apps available on the Shopify Marketplace for this purpose, so there's a solution for every use case. Do you want to know what kind of loyalty program fits best with your (online) store? We would love to brainstorm with you for the best possible solution for your company!

2 - Email, SMS or chat marketing

Next to the conventional loyalty programs, email marketing has also been proven to be successful. For most companies, it's an easy and cheap way to reach loads of existing customers in a short time. Lots of online stores also give you some time of reward or extra discount whenever you subscribe to their newsletter. However, email marketing is not always the perfect solution for every target audience. Especially the younger audience tends to use email less and less, but can be reached through other means like SMS, WhatsApp or Facebook Messenger. These platforms can be a solution to keep in touh with your customer and offer them special rewards or discounts. Examples for this are things like a marketing chatbot that is able to send your existing customers relevant offers.

3 - Machine Learning & Artificial Intelligence

Lots of online stores have collected huge amounts of customer data over the years. This information can in most cases be used to stimulate repeat purchases. By making use of machine learning models, this raw data can be processed and translated to valuable information you can use for specific purposes. With this, it is, to a certain extent, possible to predict what the next date of purchase will be of a specific customer and which product they are most likely to order. With this information, you are able to send the perfect offer on the best moment to a specific customer.

Next to using existing data efficiently, it is also possible to enhance it with existing data from third parties. For example, you are able to analyse the Facebook profile pictures of customers of an online store that sells haircare products by using Computer Vision (artificial intelligence for images) and send customers with long hair an offer for shampoo more often, than customers with short hair. In this example we assume that people with short hair run out of shampoo less often.

Have I made you curious and do you want to know how we are able to enhance the customer lifetime value of your company? Don't hesitate and contact us, so we are able to brainstorm with you about the possibilities without any obligations!