Our Optimizely practice
We work hands-on across the whole suite: CMS on PaaS and SaaS, Web, Feature and Edge experimentation, CMP, Commerce, personalization, and Opal — with senior people who understand how the products connect, and how the business behind them runs. One team for the whole platform, not a different specialist for each part of it.
Optimizely One is a connected suite, and Opal now orchestrates across all of it. We're scoped to whichever products you run — and we hold the connections between them: a CMS change that moves an experiment, a data model that decides whether personalization fires, an agent that only helps if the content underneath is structured for it. Choose a product to see how we service it.
We treat Opal as the operating layer, not a bolt-on — scoping which agents and workflows earn their place, and wiring the guardrails so they run with governance instead of guesswork.
We build and run Optimizely CMS on both delivery models: the .NET-based PaaS line (CMS 12 and 13) and the SaaS-native CMS with Visual Builder and Graph. That means we can meet you where you are and take you where the product is heading — without stalling the site you run today.
Optimizely started as an experimentation company, and Optimizely Experimentation is still the strongest part of the suite. We run all three engines — Web for front-end tests, Feature Experimentation for server-side flags and safe rollouts, and Edge for performance-sensitive changes — and we build the program discipline that turns tests into decisions.
CMP is where campaigns get planned, produced, and governed — and where Opal now does real work. We connect CMP to the CMS and the brand so content moves from brief to published without the handoffs falling on the floor, and so AI assistance runs inside your guardrails.
For Commerce (and Commerce Connect), we bring the front-end craft and the integration discipline behind it — the catalog, checkout, and the OMS/ERP/PIM/payment connections where most commerce programs quietly lose time. Then we optimize the funnel with the same experimentation rigor.
Personalization only pays off when the data underneath it is trustworthy. We connect Optimizely’s personalization and analytics to the signals that should drive it, so experiences adapt on evidence — and so you can prove the lift instead of hoping for it.
This is the fastest-moving corner of the platform. Optimizely Opal has become an agent-orchestration layer with a growing library of specialized agents and no-code workflows; alongside it, Optimizely GEO-ready CMS is built for generative engine optimization — keeping you visible as discovery shifts to AI answer engines. We help you adopt both with intent — and governance.
Four shifts are reshaping what an Optimizely program should be doing this year. Each one is a real opportunity and a real place teams get stuck. This is how we help on each.
Opal has moved from a chat assistant to an agent-orchestration layer over all of Optimizely One — a library of specialized agents, no-code workflows, and connectors to outside tools. The upside is real; so is the risk of "agent washing" and agents running without control.
SaaS-native CMS with Visual Builder and Graph is where the product is heading, but the crossing from CMS 12/13 isn't a lift-and-shift — content types are code-defined on PaaS and don't port cleanly, and search moves from Find to Graph. It's the single biggest source of unscoped effort we see.
With traffic predicted to shift toward AI answer engines, Optimizely shipped a GEO-ready CMS built for generative engine optimization — GEO metadata, Q&A structure, schema, llms.txt, and visibility analytics. The tooling is there; using it well is a content-and-structure discipline, not a switch.
The hardest question in a mature program isn't "are we testing?" — it's "why isn't all this testing moving the business?" Velocity without the right metrics produces motion, not growth. Teams plateau on resources, vanity metrics, and stalled culture.
These are the two conversations that dominate Optimizely programs right now. Here's how we approach each, concretely.
A PaaS to SaaS migration is a genuine architecture change, not an upgrade. We treat it as a program with a business case — native experimentation and personalization inside Visual Builder, queryable through Graph — and a sequence that protects continuity.
Opal can plan, create, and orchestrate across the suite — but only pays off when the content and data underneath are structured for it, and when governance is designed in from the start. We help you move from "switched on" to genuinely operating.
None of this lands without the right team behind it. Here's how we're set up to deliver across the suite:
You work with a dedicated Pod Leader who owns the engagement, and a cross-functional team whose effort scales to each sprint's goals rather than a fixed headcount. Whether you need a build, an experimentation program, or Optimizely managed services to run it day to day, it's the same accountable team — depth across the whole suite without the overhead of coordinating a patchwork of specialists.
One team that carries knowledge of your Optimizely stack forward — utilization flexes with the sprint, the accountable people don't rotate out from under you.
Across active managed-services and CRO engagements. Figures are approximate and representative of delivery quality — not a single audited account.
Optimizely is one of the platforms we go deepest on, and it sits inside a broader team — so we can run your whole Optimizely footprint and stay aware of everything around it: the data, the channels, and the go-to-market motion it all feeds.
Digital Experience Engineering, Go-to-Market, and AI & Agentic Activation. Optimizely work draws on all three — the build, the growth motion, and the AI that now runs through both.
A cross-functional pod with a named Pod Leader who owns your engagement — direct access to the people doing the work, not layers between you and them.
Our perspective comes from active engagements, not the sidelines - the same practitioners who publish our thinking are the ones on your program.
They didn't treat our CMS, our tests, and our AI plans as three separate projects — one team held all of it, and made the migration and the experimentation program pull in the same direction.
Before any engagement, we'll give you an honest, independent read on your Optimizely setup — calibrated to your business, drawn from publicly discoverable signals plus a short conversation. No obligation.
Tell us where you are: a migration you're scoping, an experimentation program that's plateaued, Opal you want to put to real use, or a whole suite you want run properly. We'll tell you how we'd help — and where we wouldn't.