Top-Tier Personalization Strategies for Subscription Brands

How To Use Personalization To Ensure Your Subscription Brand Never Falls Victim To The Monthly Purge

Subscription brands can be some of the most challenging to market. While one-time purchases can be necessary or written off as a well-deserved splurge, subscriptions face regular scrutiny. If your customers are feeling bored with their subscription or underwhelmed with the service, they are more than likely to churn and once they’ve cancelled, it can be difficult to win them back.

So, how can subscription brands use customer data to thrive in a cutthroat market? Personalization is one strategy that brands have turned to in order to differentiate their experience and offer more value to their subscribers. In this post, we’ll dive into some best practices that’ll take your subscription brand’s personalization strategy to the next level.

The Time And Place For Personalization  

Today, customers know that they’re participating in a trade-off when offering their personal data to brands. In return for data, they should receive benefits and convenience. However, the “creepy” factor is undeniable, and the payoff is often unsatisfying. As a result, customers regularly report negative attitudes towards personalized ads. So does that mean marketers should stop using them? 

The “Privacy Paradox” tells us: no. 

Messages, ads, and other personalized content almost always out-perform the alternative when it comes to engagement and open rates. Despite negative feelings about personalization, when content is personalized in a way that adds benefit or convenience for the customer, they’re more than willing to hand over their data. 

When it comes to building your personalization strategy, staying on the right side of the Privacy Paradox means that your goal should be to build a thoughtful experience that establishes a meaningful relationship with your customer. With that in mind, start by framing your strategy around your customer’s needs and challenges rather than focusing on the end-result of revenue. 

Your customer data can be a great source of inspiration for understanding your customer. For instance, you can use implicit or behavioral data to understand their psyche:

  • How many orders has a customer placed? 
  • How many times have they upgraded their subscription or changed their preferences? 
  • Have they attempted to use features unavailable within their subscription tier?
  • How often do they engage with your product, website, or app?

These details can tell you what challenges a customer is encountering, how comfortable they are with the order process, or what extra information they need to take the next best step.

If someone upgrades their subscription, you can then send them an email explaining new features of their subscription. If they’re trying to use features they don’t have access to, it calls for a message highlighting all of the membership tiers and the perks of each one. These examples aren’t super sales-y, but are timely and directly push customers towards a solution to their problem. 

Basically, put yourself in your customers’ shoes. Ask yourself “if I encountered this issue, or took this action, what would I want or need in response?” 

Data Strategy and Segmentation Best Practices

At Simon Data, we view segmentation as a form of personalization – it can be 1-to-many or 1-to-few, as opposed to 1-to-1 personalization.

Without some heavy investments in machine learning technology, it can be difficult for subscription brands to achieve the dream of a true 1-1 experience. However, segmentation can offer a low-lift strategy to ensure that every customer is receiving communication that’s helpful and relevant to them.

How to Build Your Segments

Segments are built by identifying the general sets of customers engaging with your brand and then grouping them by their behaviors, differentiators, and the data points that highlight or describe those differences. 

Some key segments for subscription brands include:

  • Leads – visitors that have converted in some way but have not yet purchased a subscription.
  • New subscribers – new subscribers to your service
  • Active subscribers – customers that have retained their subscription for a period of time 
  • Returning subscribers – customers that have resubscribed after churning
  • Inactive subscribers: subscribers who have churned. 
  • Gift or promotional subscribers: customers that were given a subscription as a gift, or customers that converted using some sort of promotion or discount.

There are additional dimensions through which you can further segment these customer groups, including:

  • Customer lifetime value – the total value of a customer to a business throughout the entirety of their relationship
  • Category affinity – subscribers who demonstrate preference for a certain type of content or product.
  • Location – geographical location can inform what products you promote.
  • Level of engagement – how frequently the customer uses the product, service, and other channels (social media, website, add-ons)

But just because you know a lot about each customer doesn’t mean all of that information is helpful. Testing your way into personalization is a great way to measure the effectiveness of the campaign, and the impact on your desired segment.  

You have to build your data foundation first to ensure your personalization strategy is relevant and useful. Starting with segments with recurring sends or journeys to optimize customer experience can be even more effective. Once you’ve experimented to pinpoint which journeys make for a better CX with segmentation, you can then lean into personalizing those segments in ways that add further value. When all of your customers are subscribed for different reasons, creating these broad segments can be the most time efficient way to personalize to their individual needs. 

Ultimately, where you start with your personalization/segmentation strategy depends on your existing data. Start with what makes sense based on where you are now, and the rest will follow. 

What Customers Really Want

Personalization done right can be a great way to build relationships through marketing. So, does that mean that all personalization is effective? 

Not exactly. 

We know that customers are willing to trade off some privacy for convenience and clear value, but it’s pretty obvious when you’re asking for information that you don’t really need. For example, if you’re looking for personalization opportunities for your subscription meal kit, you probably don’t need to know your customers’ date of birth – especially if the only thing you’re doing with it is sending a “happy birthday” message. The sentiment is nice, but if it doesn’t fit in with the existing relationship you have with your customers, there’s no real reason to do so. 

An exception here is if you’re sending them a special birthday discount, or a special meal with their shipment. Not only is it relevant for a meal kit brand, but it shows your customers that you value their business and are willing to go the extra mile. Acts of appreciation – big or small – demonstrate them the value behind providing you with personal information. 

The deciding factor when it comes to collecting data needs to be whether or not the experience the information would enable solves a customer problem, provides value, or strengthens a relationship. To identify what data you need and what you can declutter, you need to have a conversation about what problems you want to solve, and what information you would need to make it happen. Working from the problem or goal towards the solution, instead of from existing data to a conclusion, is more time-efficient, and is ultimately more impactful in heightening your customer experience. 

A Tool to Simplify the Process

All that said, it’s clear that personalization is tricky – especially for subscription brands. Overall, the best way to simplify the process is to use a Customer Data Platform, like Simon, which enables marketers to access and use all of their customer data to build and launch deeply personalized experiences and campaigns without having to rely on IT or engineering. 

To learn more about Customer Data Platforms, check out the Definitive Guide to Customer Data Platforms. Or, see how our CDP enabled pet subscription brand, Bark Box to automate data pulls and segmentation, rapidly experiment and iterate on targeted cohorts, and optimize targeting, timing, and messaging, by reading our case study.

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