Bloomreach (Formerly Exponea)

Problem: VIP and high-LTV customers are lumped into broad A/B tests, making it hard to understand how premium users respond to new pricing or offers without diluting results with lower-value traffic. Solution: Use Exponea to define a VIP or high-LTV campaign segment and set a JS flag only for those users. Convert then activates a pricing or offer experiment exclusively for visitors in that Exponea campaign. Outcome: You learn exactly how top-value customers react to new pricing, without noise from the general population. This supports confident decisions on premium offers that maximize revenue and retention for your most important audience.

Problem: New, returning, and churn-risk users all see the same onboarding and guidance, making it difficult to improve activation and reactivation rates for each lifecycle stage with targeted experiments. Solution: Create lifecycle-based segments in Exponea (new signups, returning, churn-risk) and trigger different Convert experiments per campaign via JS conditions. Each stage gets its own tailored onboarding or guidance test. Outcome: Onboarding and reactivation experiences are optimized per lifecycle stage, boosting activation, feature adoption, and win-back rates. Experiment data stays clean because only the intended Exponea segment enters each test.

Problem: Always-on Exponea campaigns and web layers can clash with A/B tests, causing overlapping messages, double counting, and unreliable experiment results that teams don’t fully trust. Solution: Coordinate activation by letting Exponea campaigns set a JS variable that gates Convert experiments. Only visitors who qualify for a specific campaign and meet Convert’s conditions are exposed to the test variation. Outcome: Campaigns and experiments run in harmony, with no audience contamination or double counting. You get trustworthy experiment readouts and can safely scale both personalization and testing without second-guessing the data.

Problem: Product recommendation layouts and placements are tested on all traffic, even though only certain behavioral or interest-based segments are likely to respond, slowing down learning and diluting impact. Solution: Use Exponea to build behavior-based segments (e.g., frequent browsers, category loyalists) and trigger Convert experiments that swap recommendation modules, layouts, or messaging only for those campaigns. Outcome: You quickly identify the best recommendation experiences for the users most likely to engage, increasing CTR and AOV. Because only Exponea-qualified visitors enter the test, results are faster, clearer, and easier to act on.

Problem: Traffic from email, push, or paid campaigns lands on generic pages, and broad A/B tests can’t distinguish how these campaign visitors respond to different promo banners or landing layouts. Solution: Have Exponea mark visitors from specific campaigns and set a JS flag in the web layer. Convert then runs targeted experiments on banners, hero copy, or landing page layouts only for those campaign-tagged users. Outcome: You optimize experiences precisely for each campaign audience, improving conversion and revenue per session. Centralized reporting in Convert shows which creatives and layouts work best for each Exponea campaign segment.

Problem: Certain audiences (e.g., in specific regions or with consent constraints) must see controlled experiences, but standard A/B testing tools make it hard to exclude or tightly manage these groups without complex setups. Solution: Let Exponea define and manage sensitive or regulated segments, then use its campaign web layer to selectively set the experiment flag. Convert only activates tests for visitors who are safe and approved to include. Outcome: You stay compliant and avoid exposing restricted users to unintended variations, while still running robust experiments on eligible traffic. Data integrity improves because only fully qualified, policy-safe visitors are counted.