Managed Services
Access to senior Do Good Digital experts on a schedule that works for you — administration, configuration, optimization, troubleshooting, integration strategy, training and change management support.
ExploreAdobe Target
Experimentation programs that actually ship.
We build the operating model behind Target — hypothesis intake, prioritization, QA, measurement and governance — so testing becomes a habit instead of a project.
The short answer
What we actually do here.
Target is usually installed long before a testing program exists. We create the program: where ideas come from, how they're prioritized, who builds and QAs, how results are measured, and how wins get rolled into the experience permanently.
- Digital and ecommerce leaders
- Growth and optimization teams
- Personalization owners with stalled roadmaps
- Analytics teams needing testing rigor
- Teams with Target licensed but underused
- Organizations formalizing experimentation governance
Problems this solves
The issues teams bring us most often.
No test pipeline
Hypothesis intake and a scored backlog so there's always a next test ready.
Tests take too long
Templates, QA checklists and clear ownership shorten the build-to-live cycle.
Results get argued
Pre-agreed metrics, sample sizing and readout format make outcomes decisive.
Wins never stick
A path from winning variant to permanent experience, with the right owners involved.
Personalization is guesswork
Audience strategy grounded in data you already have rather than assumptions.
Program depends on one person
Documented process, training and change management support across teams.
Capabilities
What that looks like in practice.
Senior practitioners, business process first, and documentation your team keeps. We teach as we build so the knowledge stays with you.
- Experimentation program design
- Hypothesis intake and backlog scoring
- Test design, build and QA process
- Audience and personalization strategy
- Measurement plans and statistical rigor
- Analytics and data integration strategy
- Governance, roles and approval paths
- Readout templates and reporting cadence
- Implementation of activities and offers
- Training and program enablement
- Change management support for adoption
- Ongoing optimization and program coaching
AI at Do Good Digital
AI that fills the testing backlog and reads the results.
AI shortens the slowest parts of experimentation — coming up with good hypotheses and turning results into a decision.
01
AI-generated hypothesis and variant copy drafts, reviewed by humans.
02
Claude-assisted result interpretation and readout drafting.
03
AI-supported audience discovery across existing behavioral data.
How we engage
Three ways to bring us in.
The same expertise, purchased the way that fits your situation. Engagements blend, and you can move between them as priorities change.
Implementations & New Delivery
Implementing, optimizing or expanding the tool, built around what is unique to you — a teaching-first partnership with a client-first experience end to end, through to a successful launch.
ExplorePartnership Solutions
Hire our team to work as one of your own. We follow your ways of working, often on your email, for staffing gaps, leaves of absence and surge needs.
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