Nathan Snell

A common challenge brands run into with personalized marketing failing is not sending the right kind of message to the right customer. Running a survey with a tool like Octane.AI is a great way to get customer feedback and better understand what kind of customer personas you have. Once that's understood, you can group them better, and should begin to see better results.

Consistency in personalized marketing across platforms defeats the purpose of personalized marketing. Yes, you want the general brand feel to be the same but that's a relatively straight forward effort. Outside of that, the whole point of personalized marketing is for it to feel tailored to the customer. Even more so when you talk about different platforms, it should feel tailored to what the customer would expect on that platform. Be very careful trying to be overly consistent across platforms. It's likely to water down the benefit of using the platform and being personalized, reducing the impact of the actual efforts.

Personalization isn't magic. It still requires you understand your customers so you're sending them things they care about. If your personalization efforts don't seem to be driving much incremental lift, it's worth digging into the data. Usually it's the result of 3 potential issues: 1. Your segments or targeting needs to be refined 2. Your content is not aligned with the customers you're sending it to 3. Your incentives are not aligned to the customers you're sharing them with

Before doing deeper discounts, it's vital to ensure you understand what impacts the discounts you're already running actually have. We use AI to do this, and the process often leads to the fact that there's different segments of customers that want different kinds of incentives. Where the customer is in the buying journey is also very important. As opposed to "deep" discounts up front, often times creating a bundled offer where the discount is present is more effective.

Before getting into deeper discounts, it's important to first understand what kind of customers are buying and with what incentives. Segmentation helps with this a lot. What we often find is that deeper discounts are not usually the problem. Usually it's a segmentation issue because most brands are broadly sending the same offers out to everyone, as opposed to personalizing it to each customer. By matching the offers more specifically to the customers most likely to buy with them, you can use deeper discounts if needed, but you can also preserve that margin on customers that don't.

Part of boosting email/SMS effectiveness is hitting the right person at the right time. That means segments that are not so big they aren't useful and aren't so small they wont scale. The other part is then putting the right promotions in front of them. If you've made your segments right, and you're using AI, you can really tailor each communication to what that customer is most interested in. This usually means understanding on a per customer basis details like their likely next purchase timing, whether they're more inclined to convert with an incentive like free shipping, and so on. The great thing is, with the right platforms, you can automate this to drive great LTV lift.