Knowing when and how to offer discounts
Let’s say you have a customer who orders every now and then on a Friday afternoon, picking the same meal every time. If you aren’t targeting that customer on the day with a specific offer for that specific meal, you’re missing an opportunity. You might even be able to turn “every now and then” into “every Friday”!
Yet if someone is consistently ordering the same meal, at the same time, why share an offer then? You won’t change that customer’s behaviour – but you could upsell another product, or target them at a different time to increase customer spend over time.
People are ordering from QSRs not just because they love the food – but because it is convenient. Having the right data allows you to target the right customers with the right offers, at the right time.
Creating a more personalised service for customer
What’s a way to immediately turn off your target customer? Perhaps it's offering them meat-based dishes when they are vegetarian. Or emailing discounts for family meals to 25-year-old bachelor. At the heart of these errors (or rather, missed opportunities) is a bad data strategy.
On the other hand, true personalisation is sending relevant offers at the right time and via the most effective channel. For example, if the data shows that customers don’t usually look at non-work emails during the daytime, a text message might be better, or an email that hits while they are checking in on the commute home.
Linking customer data and product data
Capturing customer data can then have an impact on your product data – and vice versa. For example, product data can include title, image, category and product type, description – all data that can impact your customer’s decision making. By overlaying the two data sets, you can garner more insight into your customer behaviour and product performance. For instance, let’s say one of your vegan dishes in underperforming. By combining product and customer insights, you may discover that the product description doesn’t make it obvious enough that it’s suitable for vegans. Or that you have a bigger percentage of vegetarian than vegan customers, and they want products that include real cheese, not the fake stuff.
These things can mark the vital difference between whether people are clicking on or engaging with your products or not. But the only way to tell if product data is striking the right chord is through your customer data.
