Anticipate your customers' needs
Did you know that 73% of shoppers expect brands to understand their unique needs? Predictive analytics can help you anticipate these needs and deliver on them. Let’s take a look at how four brands use predictive analytics to refine their marketing, increase engagement, and drive more conversions.
SWAK CosmeticsTarget customers based on predicted CLV
SWAK Cosmetics is releasing a brand new product, the On-The-Go-Glam travel kit, which includes travel-sized versions of all their best sellers in a chic, compact, and personalized travel bag. They’re selling the kit for $125.
Define the business goal
SWAK wants to drive sales of their On-The-Go-Glam travel kit. They don’t want to spend too much on discounting, but understand that the price point may be too high for some interested customers. They want to promote the kit to any customer who may be interested in the product.
Design the promotion strategy
SWAK launches coordinated sign-up forms and email campaigns to announce the new kit. They’re going to target all customers who have previously purchased any bestsellers. They will only provide a discount for customers unlikely to spend $125.
Use predictive analytics for refined targeting
SWAK uses predicted CLV insights in Klaviyo to create two segments of interested customers:
- Purchased bestsellers and have a predicted CLV of at least 125
- Purchased bestsellers and have a predicted CLV of less than 125
SWAK created a tailored sign-up form and campaign for each segment, which allows them to better personalize their messages and optimize their marketing spend.
Reduce discounting with purchase history and expected date of next order insights
Beantown Coffee has noticed that they’re losing a lot of money on discounting. The main example of this is that every profile who enters their abandoned cart flow receives a discount to complete their purchase.
Define the business goal
Beantown Coffee wants to improve profit margins by reducing their spend on discounts. Specifically, they want to better personalize their abandoned cart flow so they only send discounts to recipients who are only likely to purchase with an incentive.
Design the promotion strategy
Beantown enhances their abandoned cart flow by branching it into distinct paths based on purchase history and when they’re likely to purchase next. They only include a discount for recipients who haven’t purchased from them in the past, and are unlikely to make a purchase anytime soon.
Use predictive analytics for refined targeting
Beantown splits the flow for whether or not the profile has made a purchase in the past. For profiles who have not made a purchase in the past, they add another conditional split for expected date of next order. They only add a discount for customers who have not made a purchase in the past, and are unlikely to purchase in the next 14 days.
Identify and mitigate churn with expected date of next order
Nani Health has observed a lot of customer churn in the past year. They want to shift to a more proactive strategy, where they identify churn risk customers early and act quickly to increase their retention rate.
Define the business goal
Nani Health knows that retaining customers is more cost-effective than acquiring new customers. They want to be more proactive about identifying churn risks early, so they can re-engage them before they completely fall off.
Design the promotion strategy
Nani Health creates a segment of churn risk profiles, and send them a targeted re-engagement campaign to help encourage re-investment in their brand. This campaign offers them an exclusive discount, as well as features some user-generated content to show real customer feedback on their products.
Use predictive analytics for refined targeting
Nani Health uses expected date of next order and churn risk prediction insights to create a segment of customers who are unlikely to purchase from them in the next year, indicating they are at risk for churning.
Increase the CLV of their overall customer base
Bola’s Baked Goods wants to increase the overall customer lifetime value of their customers. They have a loyal subset of repeat purchasers, but they have a large number of customers that have only interacted with their brand once or twice.
Define the business goal
Bola’s Baked Goods wants to nurture more loyal customers and increase the customer lifetime value of their subscribers.
Design the promotion strategy
Bola’s Baked Goods creates a repeat purchase flow that messages customers when they’re most likely to purchase again. The flow will have tailored messages depending on the amount each person is predicted to spend in the upcoming year, so the appropriate content is promoted to the right people.
Use predictive analytics for refined targeting
Bola’s Baked Goods triggers their repeat purchase flow by the expected date of next order. They branch the flow by predicted CLV, so they can send targeted messages to each group based on their spending potential.