Shiprocket (Formerly Wigzo)

Problem: Cart recovery emails ignore which pricing, layout, or offer a shopper saw in an A/B test, creating jarring follow-ups that don’t match their on-site experience and depress recovery rates. Solution: Convert sends experiment and variation data to Wigzo when users enter cart and checkout tests. Wigzo uses this context to trigger cart emails that mirror the exact layout, copy, and offer each user saw. Outcome: Cart abandoners receive consistent, relevant nudges that feel like a continuation of their session, boosting email engagement, recovery rates, and revenue attributed back to specific experiments.

Problem: Lifecycle campaigns treat all browsers of a category the same, even when they’ve seen different category page tests, leading to generic messaging and missed opportunities for tailored product storytelling. Solution: Convert passes category-level experiment and variation names into Wigzo whenever users browse tested sections. Wigzo builds segments and dynamic blocks that align email content with the category layout or filters users experienced. Outcome: Subscribers receive lifecycle emails that reflect how they actually discovered products, increasing click-throughs, product discovery, and category revenue while revealing which layouts drive better downstream engagement.

Problem: Users who see different discount or incentive tests on-site often get the same generic promotional emails, causing confusion when the email doesn’t match the offer they remember. Solution: When a visitor is bucketed into an offer or incentive test in Convert, that variation is synced to Wigzo in real time. Wigzo uses this data to show matching offer language and creative in email and in-app campaigns. Outcome: Offer messaging stays consistent across site and channels, improving trust, reducing support friction, and lifting conversion and redemption rates for the winning incentive variations.

Problem: Product onboarding flows are A/B tested on-site, but follow-up emails and in-app messages ignore which onboarding experience a user had, making guidance feel disjointed and less effective. Solution: Convert sends onboarding experiment and variation data to Wigzo as soon as users are bucketed. Wigzo then triggers onboarding sequences tailored to the specific steps, UI, or copy users saw in the test. Outcome: New users receive coherent, context-aware onboarding support that reinforces their in-app experience, improving activation, feature adoption, and retention while clarifying which onboarding flows drive better lifecycle metrics.

Problem: Marketers struggle to connect on-site test performance with downstream email and in-app behavior, slowing decisions about which variations to scale and how to refine messaging. Solution: Convert experiment and variation data appears in Wigzo’s Live Activities dashboard, showing which users saw which experiences and how they respond to campaigns. Teams can quickly spot engagement patterns by variation. Outcome: Experiment winners are identified faster with richer behavioral context, enabling quicker rollouts, better-informed creative decisions, and clearer attribution of revenue and engagement to specific test experiences.

Problem: Winback campaigns often ignore how users behaved in key experiments (e.g., new navigation, search, or recommendation tests), missing signals about what failed to convert them. Solution: Convert streams experiment and variation data into Wigzo along with user actions. Wigzo segments lapsed users by the tests they experienced and triggers winback flows that address specific friction points or highlight alternative experiences. Outcome: Winback messages feel tailored to past behavior and site experiences, improving reactivation rates and helping teams understand which UX changes contribute to churn versus re-engagement.