Note: This guest post comes from Joshua Neckes and Brian Thompson at Simon Data. Simon is a tool that transforms your data into clear insights that let you get more out of your marketing. Connect your data in minutes, create customized segments, deploy to existing channels, and discover what your customers want. In their last post, Brian Thompson and Joshua Neckes from Simon Data described the importance of building sophisticated lifecycle campaigns around specific, well-defined transitions in the customer journey. Optimizing around these critical lifecycle milestones yields meaningful increases in customer lifetime value (LTV). They’ve determined there are multiple transition points in the customer journey. For a refresher on the first 4 transitions, you can check out the first part of this post, Mapping Customer Lifecycle Transitions. Below, they’re covering the transitions that they feel are most critical: numbers 5 through 11 and also share how to best harness the data you should be collecting about your customers. 5. Initial Category -> New Category Outside of single-product subscription companies, almost all e-commerce businesses have at least two different products. Automating cross-sell into different and/or related product sets is a very sophisticated data challenge, but a highly beneficial endeavor if done well. For marketing teams, users moving between products or categories of products can be critical for an array of reasons: customers who purchase in multiple categories typically have higher lifetime value; multi-product purchasers are more likely to become brand advocates; etc. Tracking customer behavior (e.g demo, purchase history, browsing behavior, priority categories, etc.) is essential for accomplishing this. 6. Low Average Order Value -> High Average Order Value Average Order Value (AOV) is a critical e-commerce health metric. A high AOV is almost always more desirable, and for many businesses with lower price points, it’s actually common to lose money on a portion of orders if AOV is too low. Businesses need to think critically about how to transition low AOV users into higher AOV brackets. Common targeted automations can be dynamic product bundles based on engagement and past purchase history, or free shipping with orders over a certain amount. Companies with strong marketing teams and supporting product lines often also push “recurring purchase stories” (e.g. You need five pairs of underwear for summer; skip the headache and buy them now!). 7. Buy With Discount -> Buy Without Discount For many maturing e-commerce businesses, “discount training” has become a torturous reality. Customers have become accustomed to getting a discount on nearly everything. When discounts become expected with a specific brand, it’s incredibly hard to untangle. Tactics to change customer expectations can include aspirational brand messaging, emphasizing scarcity, and product diversification where some products are never discounted. 8. Has Not Referred -> First Referral Driving that first customer referral is a huge victory for any marketer because it’s often much cheaper than traditional acquisition mechanisms, and typically yields customers with higher LTV. Referrals also imply a high level of brand engagement and advocacy on the part of the referrer. Unlike some of the more “classic” lifecycle transitions, a referral often requires its own specific tooling to be effective. Challenges for catalyzing referrals include managing email opt-ins for “referred” customers, attribution modeling for the referred customer, and tracking/giving referral rewards. We typically see most larger entities manage these programs through homebuilt tooling. 9. Has Abandoned -> Has Converted Abandoning actions are well-known to most marketers. A customer comes to the site with high intent, views an expensive product, and departs. This situation is known as an “abandoned product detail page.” Similarly, that same user might search for a product and then leave. This is known as an “abandoned search.” Finally, arguably the most commonly cited abandonment stage is the “abandoned cart.” A customer puts a product in their cart, and then closes their tab or leaves the site. Savvy marketers will make sure it shows up in your inbox within the next few hours or the next day (depending on item type, price, and other factors). More advanced marketing teams will run multi-stage abandoned cart emails, showing similar items alongside the original abandoned item, and supporting that effort with retargeting on other channels. 10. 90-Day Inactive (Channel or Purchase) -> Active In order to get ahead of customers who seem likely to churn, most savvy businesses look at the 90-day inactive mark as an early warning. If a customer isn’t opening emails or making purchases 90-days after their last purchase, it’s critical to look at paths to re-engagement. Just remember: once a customer has churned, it’s often more difficult (read: expensive) to reacquire them than it is to simply acquire a new one. 11. Inactive (9-12 months) -> Active Every business has its own definition of “active” or “inactive” customers. Product, market pressure, and customer base are all important considerations. Almost all e-commerce businesses consider a customer “churned” after 9-12 months of inactivity. It’s important to cut down on non-strategic sends and deliver only your best content leading up to this critical period. Some businesses will target customers based on purchase categories and creative product bundling; others rely heavily on seasonality and leading trends to push reactivation. Testing and optimization by customer cohort is critical to understanding the unique elements at play in your business. Conclusion One of the most important aspects of successful marketing is to employ tactics that catalyze crucial transitions: users passing from less valuable cohorts into more valuable ones. The key to uncovering these points and acting on them is harnessing and making sense of the data you collect on users in their journeys. Effective use of data in marketing can be the difference between creating repeat customers and losing them forever. Unfortunately, collecting (and using) all the data across your various touch points is both challenging and error-prone. Pairing an intelligence platform like Simon Data with SendGrid provides an indispensable platform for making efficient and effective use of your data. These tools help you identify and respond to transition opportunities by unifying your data sources, connecting to your marketing channels, running rigorous tests, and tracking results downstream. Ultimately, harnessing the valuable data you collect by using Simon Data and SendGrid helps you construct smart, automated workflows that connect these segments to all of your marketing channels, all with a built-in suite of testing and reporting tools to help you optimize every aspect of your lifecycle marketing.