Your last migration crashed and burned. What if you could eliminate the technical bottlenecks that derailed it?
Six months into your DXP migration, the project was scrapped — budgets blown, timelines missed and loads of technical complexity nobody saw coming. Now you’re stuck paying for a platform that isn’t delivering as your marketing backlog grows.
Product sites wait months to launch, campaigns stall and regional teams plead for localized content that won’t ship until next quarter. Meanwhile, your developers spend 78% of their time maintaining systems instead of improving them. You’re afraid to try again — and that fear costs you every quarter.
Why your last migration failed
Most migrations don’t fail because of bad intentions. They fail during execution, when complexity compounds faster than your budget and timeline can absorb it.
Scope creep strikes first. You start documenting requirements and discover technical debt you didn’t know existed. Every conversation with developers reveals another custom integration, another workaround, another “we built that five years ago and nobody remembers why.” Your clean migration plan becomes an archaeological dig through legacy decisions.
The template rebuild phase is where most projects actually fail. You spend months reverse-engineering how your current pages work. Developers translate old templates into new platform components. Each page variation needs documentation, each custom component needs rebuilding. Integration complexity can add up to 30% to project costs and you’re drowning in it.
Budget overruns follow inevitably. What looked like a six-month project stretches to 12, then 18. Leadership loses patience. Your team burns out from constant firefighting. By the time you’re halfway through, leadership pulls the plug.
BCG research shows that over 50% of large-scale migrations fail within three years, with typical large companies losing hundreds of millions on failed transformation projects. Your migration probably wasn’t an outlier. It hit the same execution bottlenecks that derail most migrations.
What if migration didn’t have these bottlenecks?
Imagine eliminating the technical archaeology that bogs down migrations. Picture automating the repetitive, time-intensive work that burns budgets and derails timelines — not by making strategy decisions for you, but by handling the execution that currently takes months.
Screenshots to templates in days
Picture taking screenshots of your current pages and having AI analyze the layouts to generate templates for your new platform. What used to require weeks of developer time and technical documentation could happen in days.
You wouldn’t be recreating every page manually. Marketers could show what they want without needing to understand how the legacy platform’s code works. Developers could focus on architecture and complex integrations instead of template reconstruction. The phase that typically derails projects could become the phase you move through fastest.
Content migration without the manual work
Consider automated data mapping and transformation rules replacing manual work. Your content structures won’t match between platforms perfectly, but what if AI could figure out how to map old fields to new ones and flag inconsistencies before they become problems?
Content transfer could take days instead of months. Automated validation could catch broken links, missing images and formatting issues during migration instead of after launch. You wouldn’t be discovering problems when users complain. You’d be fixing them before anyone sees them.
Preserving SEO value during URL restructuring
Your old URL structure probably needs fixing. Imagine AI mapping existing URLs to new patterns while preserving SEO value and maintaining user experience. It could suggest improvements based on what works today and flag potential redirect chains that would hurt performance.
Human validation would stay critical. AI proposes mappings, you confirm they make strategic sense. But the tedious work of documenting thousands of URLs and testing redirect rules could be automated instead of manual.
Continuous testing that catches issues early
Picture automated QA running continuously during migration. AI validating that migrated content matches source content, testing that links work, checking that images load, verifying that forms function correctly.
You wouldn’t be doing big-bang testing at the end when fixing problems means starting over. You’d be validating continuously throughout the process, catching and fixing issues while they’re still small. The “we have to rebuild everything” moments that derail migrations could become “we caught that early” moments instead.
Iterative launch instead of big-bang deployment
Imagine deploying iteratively instead of switching everything at once. Migrate one section, validate that it works, then move on to the next. Lower risk at each step. Faster time to value because you’re launching pieces as they’re ready instead of waiting for everything to be perfect.
Your team could learn the new platform gradually. Users would experience improvements incrementally. IT would support a phased rollout instead of a massive cutover weekend. The organizational stress that leads to migration failures can be distributed across manageable chunks.
The multi-brand scaling payoff
Picture your core migration complete. Now imagine spinning up new sites rapidly instead of waiting in developer queues.
Consider a pharmaceutical company with dozens of product sites. Current reality: each new site waits six months in the developer queue. Imagine “We need four new product sites for these launches” becoming a week of work instead of a half-year roadblock.
Marketing could move at business speed instead of IT capacity constraints. Your competitive advantage wouldn’t be a better platform. It would be the ability to execute when opportunities emerge.
Where you still need strategy
You still need clear migration strategy driving every decision. Which content migrates and which gets retired? What’s your new information architecture? Which integrations matter most? How do workflows change? These decisions require human judgment about business priorities, not automated recommendations.
Vendor accountability remains critical. When vendors promise AI-powered migration capabilities, demand proof through pilot projects that match your specific environment. Test their claims against your reality. Measure actual results, not projected timelines. Focus on what their platform delivers today, not next quarter’s roadmap commitments.
Your team needs process changes alongside technology changes. The same team training principles that apply to AI content creation apply to migration: train people to drive outcomes, not just operate tools. How does content creation work in the new platform? Who approves what? How do you measure success? While AI manages technical execution, you’re responsible for organizational readiness.
AI handles the technical heavy lifting, but orchestration requires the same strategic rigor whether you’re creating content or migrating platforms. The bottlenecks that derail migrations could be eliminated while you handle the strategy that makes migrations succeed.
Test the possibilities or stay stuck
If these capabilities work as described, the migration equation changes completely. Template reconstruction that previously took months could now take just days. Content validation that required manual checking could run continuously. Multi-brand scaling that waits in developer queues can take days or weeks for extremely complex initiatives.
Your last migration failed. That creates justified caution. But caution has turned into paralysis and paralysis costs you every quarter your platform underdelivers.
You don’t need to bet the company on untested technology. You need to run pilots. Pick the biggest bottleneck from your last migration — template rebuild, content mapping, validation testing — and test whether AI can actually compress that timeline. Measure the results. If it works, scale it. If it doesn’t, you’ve lost weeks instead of months.
The crest of change is approaching. Jump on your board and catch a ride.
The post How AI could make your next DXP migration actually work appeared first on MarTech.
About the author
Gene has been a Martech Healer for over three decades, inventing the future while helping organizations and leaders ‘Ride the Crest of Change.’ A serial entrepreneur since his first newspaper delivery start-up, Gene developed early innovations in social media networks, digital-out-of-home narrowcasting, and SMS mobile marketing. As the principal at Digital Mindshare LLC, a New York-based strategy and marketing technology consultancy, Gene helps clients optimize their martech investments, ensuring maximum returns and strategic alignment.
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