Increasing your brand loyalty is the name of the game. It results in increased engagement, brand advocacy, and more revenue. But consumers are inundated with emails, notifications, and texts from brands every day, sometimes multiple times a day. And the majority of them are generalized, mass messages or offers - they’re not personalized or not action-provoking.
Most marketers are familiar with creating campaign briefs - and we believe applying the same tried and true framework is the right approach for offer campaigns. However, we have 5 key recommendations to ensure success when launching any offer campaign.
Yes, singular, not plural. Each campaign should have one primary objective. Are you interested in driving incremental spend? Are you looking to increase engagement? Do you want to promote a specific brand or product line? Is the aim to have customers purchase or visit more often? While not mutually exclusive, selecting either one will impact the structure of your campaign. These ultimately boil down to revenue or engagement, but getting more specific about the goal will help define the details I’ll lay out below. For example, if you want to increase engagement, offers with richer rewards are the easy way to achieve that goal, but could impact the bottom line.
Selecting an objective will also help you determine which offer type to use. If your goal is engagement, a digital action offer (e.g. download the app) is a simple way to win. But, potentially at the cost of not generating revenue.
Now that you have your objective selected, let’s think about the right audience(s) to receive this offer configuration. If your objective is to increase the number of times consumers visit your store (frequency), then you may want to define an active/highly engaged audience for one configuration and a lapsed/inactive audience for another. For the engaged folks, you’ll set more challenging parameters and do the opposite for the less engaged consumers. It is also critical to set aside a control group. This group should receive no other offer during the same period.
This sounds like a no-brainer, but it’s critical to consider. You know your consumer better than anyone -- how often do they purchase, visit or interact? Ensure your campaign timeframe is long enough for consumers to reasonably achieve the asks you’re making. QSRs can consider running short 2 to 3 day campaigns, but that may not be ideal for big box retailers, and certainly not for travel or hospitality brands.
As you continue to build out your brief, the next step is to determine your guardrails for the campaign configuration. First and foremost, think through your incentive cost budget (this may require approval within your organization). You’ll need to set a min and a max. The way to think about this is I want my rewards to be between 10% and 15% of the spend requirement, but never give away fewer than 10 points or more than 1,000 points. Same goes for spend requirements. A spend multiplier stipulates that an offer should ask a consumer to spend 110% to 120% of their usual spend and the spend limits are the boundaries. The min and max then truly serve as guardrails for your campaign. For visit based offers, your inputs will be around the frequency min and max and for multi-action offers, and you’ll want to determine which tasks to include.
Define success metrics before you ever launch the offer campaign. Determine who from your organization needs to provide input, and who will be a stakeholder. You will want to align all levels of stakeholders on what success looks like. How will you measure operational value and speed to market, in addition to any engagement and revenue metrics? Importantly, make sure you capture data about your current performance metrics for comparison. This will serve as the North Star, and can be used as a baseline for setting targets. Targets may not be achieved in the first launch, but when you’re using a Dynamic Offer Optimization platform to manage your campaigns, we recommend rerunning campaign configurations in a series over time to allow the machine-learning models to fine tune and improve, so you’ll hit those targets.
If you can rally around your business objective and follow this framework to define a sound campaign brief, your offer campaigns will be set up for success. And remember, that even with the best-laid plans, adjustments sometimes need to be made. Expect results across several measures, but know that results take time and experimental design is crucial to ensure you’re accurately testing all possible outcomes. When you’re using a dynamic offer optimization platform, the machine-learning capabilities will learn from those iterative campaigns, and you’ll see iterative improvements with each offer launch.