A single point of contact to bring your CX vision to life with our integrated toolkit of capabilities, partners & market experience. You have an advisor & practical roadmap that is targeted to deliver measurable and sustainable benefits.
A single point of contact to bring your CX vision to life with our integrated toolkit of capabilities, partners & market experience. You have an advisor & practical roadmap that is targeted to deliver measurable and sustainable benefits.
A single point of contact to bring your CX vision to life with our integrated toolkit of capabilities, partners & market experience. You have an advisor & practical roadmap that is targeted to deliver measurable and sustainable benefits.
Genesys Xperience 2025 is just around the corner — and Customer Science is excited to be part of Australia’s premier customer experience event. Join us at the Expo Hall to see how Customer Science is helping Genesys Cloud users unlock real-time insights, drive smarter decision-making, and deliver better customer outcomes. Book a Meeting with Our…
Why did the marketplace bet on experimentation in 2025? The leadership team framed growth as a learning problem. The marketplace served two asymmetric customer groups, and the team saw faster learning as the only reliable way to improve match quality, reduce friction, and raise trust. Online controlled experiments, often called A/B tests, provide an unbiased…
Why causal impact matters for CX and service leaders? Executives run programs to change behavior. Programs only create value if they cause a change that would not otherwise happen. Causal impact measurement isolates that counterfactual and assigns credit for the lift. C-level leaders use causal impact to decide what to scale, what to stop, and…
Why audit an experiment backlog in the first place? Leaders run experiments to reduce uncertainty, but backlogs often swell with ambiguous ideas, weak hypotheses, and unclear measures of success. A disciplined audit restores focus. The audit clarifies business outcomes, reveals dependency and data gaps, and retires items that will not produce actionable evidence. Well run…
Why test governance matters to CX and service leaders Executives face a quality paradox. Teams ship faster, but customer expectations rise faster still. Test governance aligns product, engineering, data, and operations on a measurable way to prevent defects, reduce risk, and prove value. In this playbook, test governance means a lightweight system of roles, standards,…
Why experimentation programs now move the performance needle Executives face volatile demand, shifting preferences, and finite capital. An experimentation program turns uncertainty into measured learning by running online controlled experiments, often called A/B tests, to estimate causal impact before scaling change. Leaders reduce waste and lift customer outcomes because they deploy changes that the data…
What is a p-value and why do CX leaders keep tripping on it? P-values estimate how compatible observed data are with a specific statistical model that assumes there is no real effect. A small p-value indicates that the data would be unusual if the null hypothesis were true. It does not measure the probability that…
What do we actually mean by “A/B tests” and “bandits”? A leader sets the baseline by defining terms. An A/B test is a randomized controlled experiment that assigns users to variants and estimates the causal effect of a change on a metric like conversion or average handle time. The design targets unbiased effect estimation and…
Why do leading CX teams standardise experimentation? High performing CX and service teams treat experimentation as the operating system for decision making. They use controlled experiments to isolate causal impact, calibrate risk, and scale changes with confidence. A consistent checklist and a small set of guardrail metrics keep experiments fast and safe. They reduce false…
Why should CX and service leaders run geo experiments? Leaders face a measurement problem. Cookie-based tests struggle with privacy, identity resolution, and cross-device leakage. Geo experiments solve this by randomizing or matching whole regions and reading outcomes at the market level, which protects privacy while preserving causal inference.¹ Geo experiments assign non-overlapping geographic units, often…
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