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Multi-product bundles get designed at packaging review and stay fixed for quarters. A Multi-Product Bundle Optimization Playbook reads close-rate and discount patterns across bundle configurations to identify which bundles produce material lift and which exist as packaging convenience without measurable buyer pull.
The Challenge
Packaging teams design bundles to make sense for the product portfolio. The buyer response to specific bundle structures rarely gets measured per bundle. Some bundles produce real lift; others sit as packaging convenience that buyers ignore in favor of à la carte.
When a bundle launches, the bundle discount gets set on assumptions. Whether the discount level actually drives bundle adoption (vs identical product mix bought à la carte) rarely gets measured. The discount transfers margin to deals that would have happened anyway.
A bundle that wins in enterprise may flop in mid-market because the segments value the included products differently. Without segment-level bundle performance data, the company-wide bundle catalog over-includes products that hurt mid-market adoption.
How eyko Solves It
A Multi-Product Bundle Optimization Playbook reads paired bundle-and-outcome data across segments, deal contexts, and discount levels to measure each bundle's actual close-rate lift and incremental margin impact. It surfaces bundles producing material buyer pull, bundles operating as packaging convenience without lift, and segment-specific redesign opportunities.
The Playbook analyzed 18 months of bundle deals across 1,240 closed transactions. 3 of 8 active bundles produce material close-rate lift over the equivalent à la carte mix (positive ROI). 2 bundles show no measurable lift, representing $1.4M in annualized discount paid without behavior change. 3 bundles are segment-specific (work in enterprise, flop in mid-market). Redesigning the bundle catalog projects $1.4M in margin capture and modest close-rate lift.
| Metric | Current | Benchmark | Status |
|---|---|---|---|
| Primary indicator | Flagged | Target | Action needed |
| Secondary indicator | Monitoring | Within range | On track |
| Trend direction | Declining | Stable | Review required |
Multi-Product Bundle Optimization measures each bundle's actual close-rate lift and incremental margin impact using paired bundle-and-outcome data across segments, deal contexts, and discount levels. The Playbook surfaces bundles producing material buyer pull, bundles operating as packaging convenience without lift, and segment-specific redesign opportunities so the bundle catalog runs on measured buyer response rather than packaging logic alone.
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FAQ
Everything you need to know about Bundle ROI Map.
Multi-Product Bundle Optimization is an AI-driven analysis that measures each bundle's actual close-rate lift and incremental margin impact using paired bundle-and-outcome data across segments, deal contexts, and discount levels. The Playbook surfaces bundles producing material buyer pull, bundles operating as packaging convenience without lift, and segment-specific redesign opportunities.
The Playbook reads from your CRM (deal records, bundle attachment, segment metadata), pricing system (bundle configurations, discount history), product analytics (attach rates within bundles, usage patterns), and historical close-rate data both for bundle deals and for equivalent à la carte mixes (the comparison set). At least 18 months of paired bundle-and-outcome data anchors the ROI measurement.
Bundle revenue reports describe how much revenue came through bundles. Bundle Optimization measures whether the bundle produced incremental lift over the equivalent à la carte mix. The two are complementary, but ROI measurement is what distinguishes lift-producing bundles from packaging convenience that transfers margin without changing buyer behavior.
Yes. For each bundle the Playbook recommends a specific action: retain where ROI is positive, retire where lift is absent, split into segment-tagged variants where performance differs by segment, or redesign where the product-mix fit is wrong for the target segment. Each recommendation projects margin capture and close-rate impact.
Join the enterprises replacing weeks of manual analysis with a single prompt. See what eyko Playbooks can do with your data.
