4 Key Lessons for Pivoting to Subscription
Since the Pandemic first broke out we have seen more dramatic shifts in consumer behaviour than have taken place over the course of our lifetime. Included in those changes is the sharp increase in subscription services, as well as softer changes such as a requirement for brands to show compassion and care.
However, it would be wrong to assume that adding a subscription option to your existing retail or e-commerce set-up, or indeed pivoting to this model wholesale, is straightforward. Many businesses miss the opportunity to super-charge their offer by leveraging the rich but complex customer data that subscriptions bring.
So, before taking jumping on the bandwagon into subs, let’s break down four key lessons to bear in mind:
1. Get the technology right
It’s tempting to assume you can integrate your subscriptions data into your existing e-commerce and CRM suite. It might seem the most sensible ‘quick fix’ but it will invariably just lead to frustration and wasted time in the longer-term.
However, this is still what most subs businesses do – we’ve come across numerous horror stories: start dates and other key information not recorded accurately, data being overwritten on a monthly basis, and more… Given a subscription service soars or sinks on the quality of user data, it’s worth investing in a specialist system from the outset.
It’s all-important to get the set-up done correctly so there’s a chronological record of all customer interactions. If you don’t have the historical data sorted from day one it then becomes impossible to analyse emerging data trends to identify opportunities and nip churn risk in the bud.
2. Don’t overcomplicate the membership models
There’s a simple rule – too many tiers end in tears.
Successfully managing subscription services is a complicated enough proposition at the best of times, having to make sense of numerous silos will become a time sink that is usually not worth the effort – unless you have subscriber numbers akin to someone like Netflix of course!
A siloed approach to membership is usually symptomatic of poor governance and decision making. Most often this is the outcome of marketing teams setting up new membership types on the back of specific campaigns without appreciating the trouble this will cause down the line.
As such, centralised controls need to be implemented around who has admin rights to set up new membership categories. This number needs to be manageable in order to draw useful insights from the data. Ideally, the ceiling should be agreed from the outset and there should certainly be no more than 10 tiers at any given time. If there has been category-creep, it should be a strategic priority to reallocate customers to ‘official’ tiers at the first opportunity.
When it comes to defining what those categories should be, best-practice is to work backwards from your audience’s purchasing behaviours. This has been an approach used by energy companies for some time, for example building tariffs based on the times of day when different customer segments are most likely to turn the heating on.
However, this type of personalised model can be applied to all sorts of markets. Some good examples we’ve seen include: a flexible food subscription service that allows people to specify what days they want a delivery and how often, so the schedule suits the customer’s routine; in the beauty segment there are membership options that are priced in line with a specified maximum cart spend per month; and wine merchants that offer subs options in which users can bank their monthly allowance to cash in as and when they need it – for example for something special at Christmas.
While each example takes a different approach, the common denominator is that all are built around the specific needs of their audiences.
3. Read the signs
If you are serious about running a data-led subscription service, it will mean building in a whole new job function – the retention team. It’s their job to pay close attention to the behavioural data and use this to identify opportunities to build customer loyalty, whilst reducing churn.
The sheer weight of data that’s available can be daunting and makes it hard to know where to start. Especially when the team should put monitoring strategies in place built around the behaviours of new users, constant users, reactivations and so-on. So, the simple answer lies in starting with the audience of greatest strategic importance and then building out.
If you’re looking to find and nurture high-value customers, the first step is to identify what indicators you’re looking for. Other than how long they’ve been a subscriber, other factors might include return visits to a product page, or in-bound click throughs via ads.
Conversely, there’s little sense in putting too much time and effort into customers that are likely to lapse, for example those that have just signed up for a trial period. Gaining new customers is expensive, so it’s wise to do your level best to hold on to the ones you already have. In particular, pay close attention to the expiry dates on cards and give subscribers plenty of warning before they’re liable to receive a card declined message.
4. Predictive churn algorithm
Pull together a predictive churn algorithm that will alert you to signs that a user is moving towards an opt-out. Indicators to watch out for here include a lack of engagement with the website or app, logging in to check account status, viewing Ts & Cs pages etc. By pulling together the evidence, it’s possible to put strategies in place to pre-empt churn with tailored offers or similar.
No-one suggested subscriptions are easy, but they are worthwhile – otherwise we wouldn’t be seeing so many e-commerce brands looking to build these models in to their offers. Don’t let the fact it’s hard put you off though, instead think carefully about what you want to achieve – is it to build greater loyalty with existing customers, or to attract audiences away from a competitor? These considerations should dictate the pricing strategy.
Ultimately, the value a subscription creates will be defined by the data output. This in turn is dictated by how much preparation goes in at the very start. It’s not a simple bolt-on and you only get one chance to do it properly. It’s well worth putting in the extra time and investment up-front, otherwise you’ll expend even more time and effort retrofitting before you realise the benefits.