This is the fourth post in our Horizon Deep Dive series. To follow along with the series (and receive exclusive content) click here.
This week, we’re looking at targeting offers and rewards in Horizon, using rule-based tags. Effectively personalising the offers you send is essential, especially for loyalty program members – 56% of customers in one survey said they’d stop participating in a program that didn’t provide relevant rewards.
Let’s take a quick look at two essential ingredients for a well-tailored offer: content and context.
Relevant content
The first thing to consider when deciding what to recommend to which customers is the content of the offer itself – what is it you’re promoting and who will it most appeal to? For example, an offer for a premium family photoshoot is unlikely to appeal to customers who don’t have children.
Similarly, a discount on a new line of women’s clothing won’t be relevant to most of your male customers. Unfortunately, it’s quite common to see highly specific offers like these broadcast to a wide-ranging group of customers – often to the entire base.
Specific offers (rather than generic discounts) are great for creating a sense of value and relevance – so long as they’re sent to the right customers. That’s why it’s key to ensure your marketing and loyalty software will allow for careful tailoring.
At the same time, it’s important to avoid going too granular in your targeting, or making too many assumptions about your customers (don’t assume, for instance, that older customers won’t be interested in tickets to a performance by a popular new band). It’s always best to use stated preferences and previous behavioural data to target offers where possible.
Relevant context
Even if the content of your offer is perfectly tailored for your customers interests and tastes, that doesn’t automatically mean it will always be the best offer to recommend. Context – that is, where they are, how they’re feeling, and what they want with regard to your brand – is key to creating a truly personalised experience.
If a customer has just purchased a product or service, the last thing they want is an offer for a discount on said item delivered a few days later (sadly, we’ve seen it happen). If they’re in the middle of resolving an issue with a product, recommending they redeem a reward is distracting at best and can potentially cause annoyance and negative sentiment.
Even the most relevant content can be delivered at the wrong time. When setting up the targeting rules for an offer or reward, consider how you can build context into the decision-making process.
Share your thoughts…
We’d love to hear about your experiences with targeting and personalising offers. Does personalisation matter? What factors do you consider when targeting rewards and offers? Share your thoughts in the comments below!
