You’ve run out of your favourite high-sugar fruit drink. You rush over to the cornershop to get a re-up; you buy the drink and you leave. Now let’s think about this customer journey in the same way we’ve discussed this shop run.
Automation – in its reactive current state – is the realisation you’re low on the drink. This customer journey to the cornershop heavily relies on this realisation. Still with us? Great.
As a marketer you’ve seen all the messages, (a lot of it from us), about creating amazing experiences that make sense in context with the customers’ current lifecycle stage with you; but the most commonly-used campaigns may not be enough to truly do that. Let’s take marketing staples like cart and browse abandonment, for example. While they can help to drive revenue, ultimately, they’re reactive. They simply respond to customer behaviour – just like the shopkeeper ringing up the drink after you make your way to them.
We’ve asked ourselves – is there a possibility for more? Is there an opportunity to create a more proactive and personalised experience; and in doing so, can we better how we harness predictive technology?
We believe so, and in this post we’ll explore how the currently favoured form of automation can make room for something more future-ready.
Before we start, it’s worth acknowledging that reactive campaigns – such as cart and browse abandonment, welcome series and more – can and do drive serious revenue for retailers, and provide a helpful, contextual experience for customers – there is and should be space for them in any good retention marketing strategy in 2019.
But while it’s great that marketers across the board are working to engage with customer behaviour, this is not the summit of Marketing’s Everest. ‘Automation’, unfortunately, has become a set of linear actions based on repetition – a ‘trigger’.
Reactive actions don’t get to the core issue of customer lifecycle marketing. When a customer visits your site to do something, half the battle is won. They remembered you and decided to see if you could add value. But the final frontier, as it were, is with those who aren’t coming to the site anymore or their frequency has declined.
This means we need to rethink how marketing automation will look. We need to reach customers before they reach us. We need to create more opportunities to send highly relevant and timely messages to people. This is where the proactive automation element comes in.
What is the difference between reactive and proactive marketing? As illustrated in our introduction, reactive marketing is a campaign that is triggered by customers’ behaviour but is limited to this.
Proactive automation means marketing messages that use customer intelligence to pre-empt the best possible message to send in any given moment. Within the context of our example, this would be the shopkeeper taking into account the size of the drink purchases and your usual time gap between purchasing another. Using this information about you, they’ll know when you’re going to run out.
So you’re running low on of your favourite drink again. Just as you’re about to rush to the shop, you hear a knock at the door and there on the doorstep is the drink, kindly left for you by your friendly shopkeeper, who has figured out you haven’t been back to restock on your drink in the expected time and dropped it round for you – this is like predictive marketing. It preempts the needs of the customer based on their previous behaviour or purchase.
However, the key concern for most retention marketers is how to get the customer to come back and engage with their site in the first instance. Why should you continue to get the juice from the cornershop, when you can get it from another across the road from it? This is where predictive makes a standout difference. Ultimately, it creates a beneficial experience without their asking.
So far we’ve talked a lot about sugary drinks, and not a lot about marketing campaigns. ‘Proactive’ marketing campaigns can be roughly grouped into two categories:
Here are some examples of proactive automation campaigns in practice:
Predictive replenishment: alerting a customer, based on their predicted usage patterns and the quantity of the product purchased, that it might be time to think about re-purchasing.
Predictive anti-lapse campaigns: identifying ‘at-risk’ shoppers and engaging with them long before they start to distance themselves from the brand. Instead of being triggered by a lack of interaction over an extended period of time, this campaign sends a marketing message at the time the customer first begins to lessen their engagement based on their individual engagement patterns.
Product-based campaigns: targeting customers based on items they’ll likely want to buy based on their individual brand and product affinity when new products are added to a site or significantly change in price. For more on this, check out our Ometria Labs case study with Feelunique.
Customer expectations are only set to grow, which means that to truly be ahead of the game, the only way is to innovate.
Proactive marketing has clear technology implications, and relies firstly on having a full picture of the customer and all their interactions with you as a brand; but also the ability to deliver your personalised proactive messages at scale, namely, AI analysing customer behaviour and making decisions on how and when to contact them – with this in place you can truly tap into the next rocky ledge on the journey to the marketing peak.
Of course, it’s essential that any AI-based platform, while making campaigns more efficient and timely, provides visibility and transparency into why things are sent – that it doesn’t become a ‘black box’ replacing the marketer, but instead an assistant that augments the marketer.