فهم سلوك المستخدم

تحليلات المنتجات الرقمية وسلوك العملاء

نساعد مديري المنتجات على فهم كيفية تفاعل المستخدمين الفعليين مع ميزات التطبيق والموقع، وتحديد المسار نحو نمو مستدام.

بعض من أكثر من 500 علامة تجارية تعاونا معها

علامات تجارية رائدة ومتميزة تعاونا معها عبر مختلف القطاعات.

عرض جميع الشركاء والعملاء

Approved task contracts

Choose the product or customer decision to measure

Start with the product or customer decision, then define the evidence and system boundary it requires.

Decision systems

Cohort, Retention & LTV Analysis

Cohort entry and customer grain anchor the analysis. Retention, value, cost, maturity, censoring, and uncertainty stay reproducible in the cohort, retention, and LTV model.

Nothing was changed on purpose here; you are comparing customers who arrived months apart, so the curves get aligned by maturity before a younger cohort is called weaker.

Product Experimentation Measurement

The governed product experiment and decision record links the hypothesis to eligibility, assignment, exposure, outcomes, guardrails, stopping rules, and the final readout.

A specific in-product change is being tested, so the hypothesis, sample size, guardrails, and stopping rule are timestamped before the first assignment rather than after the readout.

When this owner applies

Make product and customer behavior measurable

Measure in-product behavior, experiment integrity, retention, and customer value with reproducible definitions and bounded claims.

Capability boundary

Analytics owns the readout, CRO owns the treatment

Analytics owns measurement design and readout. CRO owns treatment and programme execution.

Evidence-led delivery

Set the experiment and metric rules up front

Every engagement has named inputs, owners, human approval gates, reproducible QA, explicit limitations, and an operating handover.

We measure in-product feature usage, onboarding funnel drop-offs, user retention cohorts, and experimentation validity. Zeo specialists instrument telemetry contracts, cohort analysis, and A/B test validation, while your product managers authorize feature rollouts.

From behavior definition to a reviewable readout

A product telemetry and user retention measurement workflow built for digital product teams.

  1. Define product telemetry

    We map feature engagement, onboarding steps, user activation milestones, and lifecycle events into an explicit product tracking schema.

  2. Configure cohort tracking

    We build user cohort analyses to measure N-day retention, churn risk indicators, and customer lifetime value (LTV) models.

  3. Measure experimentation

    We instrument feature flag tracking, check sample ratio mismatch (SRM), and validate statistical confidence in product A/B tests.

  4. Enable product insights

    We construct self-serve product analytics dashboards for product managers, designers, and growth engineers.

الفريق الذي يبني أنظمة القياس الرقمي لمؤسستك

تصمم Zeo أنظمة قياس متكاملة تربط قرارات الأعمال بجمع البيانات المنظم وتقارير دقيقة يمكنك الاعتماد عليها والتحقق منها.

الأدوات التي نستخدمها

منظومة القياس والتحليلات الرقمية

جمع البيانات، والتتبع المتقدم، وتحليلات المنتجات وإعداد التقارير هي مهام متكاملة نبني منظومة قياسنا عليها.

تحليلات المنتجات وتطبيقات الهاتف المحمول

  • Mixpanel
  • Amplitude
  • PostHog
  • Heap
  • Pendo
  • Statsig
  • Userpilot

إعادة تشغيل الجلسات والخرائط الحرارية وتحليلات التجربة

  • Fullstory
  • Contentsquare
  • Contentsquare

تحسين معدل التحويل واختبارات التجربة

  • LaunchDarkly
  • Optimizely

استشارة تحليلات البيانات

ابنِ بنية تحتية لتحليلات الويب يمكنك الاعتماد عليها

تواصل مع مهندسي ومستشاري البيانات في Zeo في دبي لتنقية بياناتك وبناء قياس رقمي دقيق ومتوافق مع أعلى معايير الخصوصية.
احجز استشارة البيانات

Questions

Product & Customer questions

How does Product Analytics differ from Web Analytics?

Web Analytics focuses on traffic acquisition, session behavior, and top-of-funnel conversions. Product Analytics focuses on logged-in user engagement, feature adoption, onboarding completion, user retention, and long-term LTV.

Why is Sample Ratio Mismatch (SRM) critical in product A/B testing?

Sample Ratio Mismatch occurs when the ratio of users in variant groups deviates from the expected split (e.g. 50/50). SRM indicates underlying assignment bias or tracking bugs, invalidating test results.

Which product analytics platforms do you implement?

We implement and integrate tools like Mixpanel, Amplitude, PostHog, Heap, and custom BigQuery product data models.

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سياسة الخصوصية وحماية البيانات

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