Best of LinkedIn: Digital Products & Services CW 22/ 23

Product thinkers urged starting small – run frequent customer conversations and lightweight experiments instead of rolling out heavyweight discovery frameworks

eCommerce cases showed that personality-based segmentation can materially lift revenue, proving the value of granular user understanding

Authors stressed discarding rigid roadmaps and re-prioritising around the single highest-impact customer problem at any moment

Teams debated the build-versus-buy choice for AI components; the consensus is to buy for speed but build when differentiation or data moats matter

Successful AI products intentionally master one task first, rejecting “do-everything” ambition to secure early market traction

Posts highlighted AI agents that now automate requirement analysis and rapid prototyping, freeing human talent for higher-order problem-solving

Roadmaps are shifting from feature lists to strategic narratives that tie every initiative to a measurable business goal

Thought leaders framed product management as an executive function – owning vision, resource allocation, and go-to-market, not ticket triage

Fast-moving markets demand evidence-based decisions, clear success signals, and tight feedback loops to course-correct early

Practitioners advised anchoring teams on one time-bound, business-critical metric before layering on complex OKRs

AI-driven search and recommendation engines delivered notable revenue uplifts for retail players, reinforcing data-led iteration loops

Posts cautioned that rapid AI adoption must still pass the value test – automation without a metric misses the mark

Contributors warned that AI speed without deep UX research produces cluttered experiences; user testing remains non-negotiable

Streamlined, frictionless interfaces emerged as a competitive edge in crowded digital product landscapes

Designers showcased iterative feedback cycles – shipping micro-updates weekly to lock in user delight

The “Product Trio” (PM, designer, engineer) remains the benchmark for discovery sprints, now augmented by AI copilots

Cross-disciplinary empathy was called out as the hidden driver of execution velocity and launch quality

Commentary predicted a coming “1-1-1” era where micro-teams own problem, solution, and delivery end-to-end

One SaaS team reported an energised launch with strong early pre-orders, attributing success to roadmap transparency and tight stakeholder alignment

Ecosystem thinking surfaced in multiple posts: integrations with analytics, payment, and AI vendors are accelerating time-to-value while reducing build risk