How do you define 'tested users'?

A tested user is any visitor included in any experiment (A/B Testing, Personalization, or Survey) and visible in the reporting area. For example, if 500 users see the control page and 500 see the variation page in an A/B test, you consume 1,000 tested users.

Can the Omniconvert code be installed using Google Tag Manager?

Yes, you can install our code using GTM. However, this may slow down code deployment, causing issues like screen flickering during A/B tests or delayed triggering for popups.

Can Omniconvert be used for any type of website?

Omniconvert works for most self-hosted websites, including custom-coded sites, CMS platforms (e.g., WordPress, Joomla, Drupal), and eCommerce platforms (e.g., Shopify, Magento, BigCommerce). The main requirement is access to the source code to paste in Omniconvert's code.

Apptimize vs Optimizely vs Omniconvert

Comprehensive experimentation and personalization comparison. Scroll down on the right to view all rows.

Read other comparisons between Apptimize and Optimizely.

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Field	Apptimize	Optimizely	Omniconvert	Comparison in Detail (Info)
Website URL This row lists the official websites for Apptimize and Optimizely and does not represent a functional distinction.	apptimize.com This row lists the official websites for Apptimize and Optimizely and does not represent a functional distinction.	optimizely.com This row lists the official websites for Apptimize and Optimizely and does not represent a functional distinction.	omniconvert.com This row lists the official websites for Apptimize and Optimizely and does not represent a functional distinction.	This row lists the official websites for Apptimize and Optimizely and does not represent a functional distinction.
Category or type Apptimize focuses on mobile app experimentation, while Optimizely provides a broader digital experimentation platform across web and other channels.	Experimentation and optimization platform Apptimize focuses on mobile app experimentation, while Optimizely provides a broader digital experimentation platform across web and other channels.	Digital experience and experimentation website covering web experimentation, feature experimentation, and personalization Apptimize focuses on mobile app experimentation, while Optimizely provides a broader digital experimentation platform across web and other channels.	"Conversion rate optimization website offering A/B testing, split tests, overlays/popups, surveys, personalization, and segmentation for web/e-commerce sites " Apptimize focuses on mobile app experimentation, while Optimizely provides a broader digital experimentation platform across web and other channels.	Apptimize focuses on mobile app experimentation, while Optimizely provides a broader digital experimentation platform across web and other channels.
Primary use cases Apptimize is primarily used to test and optimize native mobile app experiences, whereas Optimizely is used to run structured experiments across websites and digital products.	"A/B testing, multivariate testing, feature flagging, mobile optimization" Apptimize is primarily used to test and optimize native mobile app experiences, whereas Optimizely is used to run structured experiments across websites and digital products.	"A/B and multivariate tests across web and apps, full-stack feature experimentation, feature flagging, rollout control, and real-time personalization" Apptimize is primarily used to test and optimize native mobile app experiences, whereas Optimizely is used to run structured experiments across websites and digital products.	"A/B and split-URL testing for page layout/pricing/UX, on-site personalization, overlays/exit-intent popups, surveys and feedback collection, segmentation-based CRO, and e-commerce optimization " Apptimize is primarily used to test and optimize native mobile app experiences, whereas Optimizely is used to run structured experiments across websites and digital products.	Apptimize is primarily used to test and optimize native mobile app experiences, whereas Optimizely is used to run structured experiments across websites and digital products.
Target business size Apptimize is often adopted by mobile product teams, while Optimizely commonly serves larger organizations running cross-channel experimentation programs.	Small to enterprise businesses Apptimize is often adopted by mobile product teams, while Optimizely commonly serves larger organizations running cross-channel experimentation programs.	"Marketing, product, and engineering teams in mid-market and enterprise organizations that run large experimentation programs" Apptimize is often adopted by mobile product teams, while Optimizely commonly serves larger organizations running cross-channel experimentation programs.	Small businesses to medium/large e-commerce and marketing teams needing CRO without heavy infrastructure Apptimize is often adopted by mobile product teams, while Optimizely commonly serves larger organizations running cross-channel experimentation programs.	Apptimize is often adopted by mobile product teams, while Optimizely commonly serves larger organizations running cross-channel experimentation programs.
Pricing model Apptimize pricing typically reflects mobile app usage and experimentation scale, while Optimizely pricing aligns with broader experimentation scope and traffic volume.	Tiered pricing based on usage and features Apptimize pricing typically reflects mobile app usage and experimentation scale, while Optimizely pricing aligns with broader experimentation scope and traffic volume.	"Enterprise-oriented pricing for Web Experimentation and Feature Experimentation, driven by traffic volume and feature bundles, with request-based quotes" Apptimize pricing typically reflects mobile app usage and experimentation scale, while Optimizely pricing aligns with broader experimentation scope and traffic volume.	"Tiered SaaS pricing tied to the number of tested users/visitors and active CRO modules (testing, overlays, personalization) " Apptimize pricing typically reflects mobile app usage and experimentation scale, while Optimizely pricing aligns with broader experimentation scope and traffic volume.	Apptimize pricing typically reflects mobile app usage and experimentation scale, while Optimizely pricing aligns with broader experimentation scope and traffic volume.
Free plan available Neither Apptimize nor Optimizely centers its offering around a permanent free tier, as both focus on paid experimentation programs.	Free trial with limited features Neither Apptimize nor Optimizely centers its offering around a permanent free tier, as both focus on paid experimentation programs.	Free Feature Flagging plan for feature experimentation and a free testing plan described with a visitor cap in the independent pricing analysis Neither Apptimize nor Optimizely centers its offering around a permanent free tier, as both focus on paid experimentation programs.	"Free tier for up to a specific visitor volume (up to ~50,000 monthly visitors per Shopify listing) to allow entry-level experimentation without upfront cost" Neither Apptimize nor Optimizely centers its offering around a permanent free tier, as both focus on paid experimentation programs.	Neither Apptimize nor Optimizely centers its offering around a permanent free tier, as both focus on paid experimentation programs.
Free trial length Access to Apptimize and Optimizely generally requires sales engagement rather than unrestricted self-serve trials.	14-day free trial Access to Apptimize and Optimizely generally requires sales engagement rather than unrestricted self-serve trials.	Free plans and trials are structured around visitor limits and product type rather than a single fixed duration Access to Apptimize and Optimizely generally requires sales engagement rather than unrestricted self-serve trials.	Ongoing free-visitor allowance rather than a fixed-term trial. Base usage allowed until the tested-visitor cap is reached Access to Apptimize and Optimizely generally requires sales engagement rather than unrestricted self-serve trials.	Access to Apptimize and Optimizely generally requires sales engagement rather than unrestricted self-serve trials.
Starting price per month Both Apptimize and Optimizely typically operate through custom or enterprise pricing rather than simple entry-level plans.	Pricing based on selected plan and usage Both Apptimize and Optimizely typically operate through custom or enterprise pricing rather than simple entry-level plans.	Public site uses “request pricing” model. Third-party analysis describes tiered pricing with a free testing plan up to 75k visitors per month and discounted overages Both Apptimize and Optimizely typically operate through custom or enterprise pricing rather than simple entry-level plans.	Published starting tiers for small sites/visitors. Publicly referenced entry-level cost for basic traffic levels (though the exact number depends on traffic) Both Apptimize and Optimizely typically operate through custom or enterprise pricing rather than simple entry-level plans.	Both Apptimize and Optimizely typically operate through custom or enterprise pricing rather than simple entry-level plans.
Billing frequency Apptimize and Optimizely approach billing frequency from different experimentation contexts.	Monthly or annual billing Apptimize and Optimizely approach billing frequency from different experimentation contexts.	"Monthly or annual contracts, negotiated through sales and plan selection" Apptimize and Optimizely approach billing frequency from different experimentation contexts.	Monthly billing based on tested-visitor quota and active CRO product modules Apptimize and Optimizely approach billing frequency from different experimentation contexts.	Apptimize and Optimizely approach billing frequency from different experimentation contexts.
Contract term required Apptimize and Optimizely approach contract term required from different experimentation contexts.	Subscription commitment based on chosen plan Apptimize and Optimizely approach contract term required from different experimentation contexts.	"Contract-based arrangements are common for experimentation websites, with enterprise terms defined through sales" Apptimize and Optimizely approach contract term required from different experimentation contexts.	"Subscription-based model with flexibility. Not strictly long-term by default, it depends on the plan and usage levels " Apptimize and Optimizely approach contract term required from different experimentation contexts.	Apptimize and Optimizely approach contract term required from different experimentation contexts.
Additional or hidden costs Apptimize and Optimizely approach additional or hidden costs from different experimentation contexts.	Additional charges for high usage or advanced features Apptimize and Optimizely approach additional or hidden costs from different experimentation contexts.	"Additional cost impact from traffic increases, more environments, advanced analytics, and feature management scale" Apptimize and Optimizely approach additional or hidden costs from different experimentation contexts.	Additional cost increments when visitor/tested-user volume exceeds plan limits or when adding multiple CRO modules (testing + overlays + personalization) Apptimize and Optimizely approach additional or hidden costs from different experimentation contexts.	Apptimize and Optimizely approach additional or hidden costs from different experimentation contexts.
Types of tests supported Both Apptimize and Optimizely support A/B testing, though Apptimize emphasizes mobile app experiments while Optimizely covers web and broader digital testing formats.	"A/B testing, multivariate testing, feature flagging" Both Apptimize and Optimizely support A/B testing, though Apptimize emphasizes mobile app experiments while Optimizely covers web and broader digital testing formats.	"A/B tests, multivariate tests, multi-page experiments, server-side tests, and feature experiments controlled by flags" Both Apptimize and Optimizely support A/B testing, though Apptimize emphasizes mobile app experiments while Optimizely covers web and broader digital testing formats.	"A/B tests, split URL tests, overlay/pop-up experiments, personalization experiments, survey-backed UX tests, segmentation-based variants " Both Apptimize and Optimizely support A/B testing, though Apptimize emphasizes mobile app experiments while Optimizely covers web and broader digital testing formats.	Both Apptimize and Optimizely support A/B testing, though Apptimize emphasizes mobile app experiments while Optimizely covers web and broader digital testing formats.
Client-side testing support Optimizely enables client-side experimentation for web experiences, while Apptimize focuses on SDK-based experimentation within mobile apps.	"Client-side testing for mobile apps (Android, iOS)" Optimizely enables client-side experimentation for web experiences, while Apptimize focuses on SDK-based experimentation within mobile apps.	Web experimentation delivered through a page snippet for browser-based A/B and multivariate tests Optimizely enables client-side experimentation for web experiences, while Apptimize focuses on SDK-based experimentation within mobile apps.	"Client-side experiments and personalization via JavaScript snippet or no-code visual editor, suitable for marketers without deep dev resources " Optimizely enables client-side experimentation for web experiences, while Apptimize focuses on SDK-based experimentation within mobile apps.	Optimizely enables client-side experimentation for web experiences, while Apptimize focuses on SDK-based experimentation within mobile apps.
Server-side testing support Optimizely supports server-side experimentation across web environments, whereas Apptimize centers more on app-level SDK implementations.	Server-side support for feature flagging and optimization Optimizely supports server-side experimentation across web environments, whereas Apptimize centers more on app-level SDK implementations.	Feature Experimentation product positioned as full-stack experimentation across frontend, backend, mobile, and edge Optimizely supports server-side experimentation across web environments, whereas Apptimize centers more on app-level SDK implementations.	Focus remains on front-end and user journey testing. Server-side experimentation is not emphasized in the main public materials Optimizely supports server-side experimentation across web environments, whereas Apptimize centers more on app-level SDK implementations.	Optimizely supports server-side experimentation across web environments, whereas Apptimize centers more on app-level SDK implementations.
Feature flagging support Both Apptimize and Optimizely include feature management capabilities within their experimentation workflows.	Comprehensive feature flagging for mobile apps Both Apptimize and Optimizely include feature management capabilities within their experimentation workflows.	Dedicated feature flagging and experimentation website with percentage rollout, audience targeting, and kill switches Both Apptimize and Optimizely include feature management capabilities within their experimentation workflows.	"Primary focus on CRO, testing, personalization, and overlays. Feature-flagging is not prominently described as core in public material " Both Apptimize and Optimizely include feature management capabilities within their experimentation workflows.	Both Apptimize and Optimizely include feature management capabilities within their experimentation workflows.
Traffic allocation methods Apptimize and Optimizely approach traffic allocation methods from different experimentation contexts.	"Traffic split for A/B tests, targeting based on user attributes" Apptimize and Optimizely approach traffic allocation methods from different experimentation contexts.	Traffic allocation through Stats Engine, flexible audience targeting, and percentage-based rollout across variations and features Apptimize and Optimizely approach traffic allocation methods from different experimentation contexts.	"Traffic/visitor distribution configurable per experiment/variation via visual editor or code, with segmentation and targeting to allocate traffic appropriately " Apptimize and Optimizely approach traffic allocation methods from different experimentation contexts.	Apptimize and Optimizely approach traffic allocation methods from different experimentation contexts.
Targeting and segmentation options Apptimize segments users within mobile apps, while Optimizely applies segmentation rules across web and digital audiences.	Segmentation by demographics, behavior, and device Apptimize segments users within mobile apps, while Optimizely applies segmentation rules across web and digital audiences.	Targeting based on audiences, user attributes, events, environments, and complex rules across channels Apptimize segments users within mobile apps, while Optimizely applies segmentation rules across web and digital audiences.	"Segmentation by geolocation, device type, traffic source, session behavior, user attributes, and e-commerce signals for personalization or test targeting " Apptimize segments users within mobile apps, while Optimizely applies segmentation rules across web and digital audiences.	Apptimize segments users within mobile apps, while Optimizely applies segmentation rules across web and digital audiences.
Personalization rules engine Optimizely delivers personalization across digital channels, whereas Apptimize personalizes in-app experiences within mobile environments.	Built-in personalization for app content delivery Optimizely delivers personalization across digital channels, whereas Apptimize personalizes in-app experiences within mobile environments.	Real-time personalization layer combining audience targeting, AI-driven audiences, and experiment results Optimizely delivers personalization across digital channels, whereas Apptimize personalizes in-app experiences within mobile environments.	"Personalization through rule-based adjustments (content, overlays, messaging) governed by segmentation and visitor behavior conditions, with a marketer-friendly control panel " Optimizely delivers personalization across digital channels, whereas Apptimize personalizes in-app experiences within mobile environments.	Optimizely delivers personalization across digital channels, whereas Apptimize personalizes in-app experiences within mobile environments.
Recommendation engine available Apptimize and Optimizely approach recommendation engine available from different experimentation contexts.	"Limited, focuses on app content optimization" Apptimize and Optimizely approach recommendation engine available from different experimentation contexts.	Personalization and AI predictive audiences highlighted, with product detail on collaborative recommendation algorithms not explicit in public overviews Apptimize and Optimizely approach recommendation engine available from different experimentation contexts.	"Core focus on CRO and UX experimentation. The recommendation engine is not emphasized as an explicit feature in the available material. Personalization is limited to content and layout, not full recommendation system " Apptimize and Optimizely approach recommendation engine available from different experimentation contexts.	Apptimize and Optimizely approach recommendation engine available from different experimentation contexts.
Number of concurrent experiments allowed Apptimize and Optimizely approach number of concurrent experiments allowed from different experimentation contexts.	Unlimited, depending on selected plan Apptimize and Optimizely approach number of concurrent experiments allowed from different experimentation contexts.	An enterprise-grade experimentation website designed for many concurrent tests managed through Stats Engine and program management features Apptimize and Optimizely approach number of concurrent experiments allowed from different experimentation contexts.	The visitor/tested-user quota governs experiment concurrency. Small and midsize sites run multiple experiments simultaneously within plan limits Apptimize and Optimizely approach number of concurrent experiments allowed from different experimentation contexts.	Apptimize and Optimizely approach number of concurrent experiments allowed from different experimentation contexts.
Built-in reporting depth Optimizely provides structured experiment reporting across channels, while Apptimize reports primarily on mobile app experiment performance.	Detailed reporting with real-time experiment tracking Optimizely provides structured experiment reporting across channels, while Apptimize reports primarily on mobile app experiment performance.	Rich reporting with Stats Engine, lift charts, significance, experiment dashboards, feature metrics, and real-time analytics integrations Optimizely provides structured experiment reporting across channels, while Apptimize reports primarily on mobile app experiment performance.	"Reporting around test results, conversion metrics, personalization effectiveness, overlay/survey performance, and segmentation-based outcome tracking " Optimizely provides structured experiment reporting across channels, while Apptimize reports primarily on mobile app experiment performance.	Optimizely provides structured experiment reporting across channels, while Apptimize reports primarily on mobile app experiment performance.
Funnel and journey analysis Apptimize and Optimizely approach funnel and journey analysis from different experimentation contexts.	Funnel analysis for conversion and behavior tracking Apptimize and Optimizely approach funnel and journey analysis from different experimentation contexts.	Experiment-focused funnel and journey analysis supported through Optimizely Analytics and integrations with warehouse native analytics Apptimize and Optimizely approach funnel and journey analysis from different experimentation contexts.	"Funnel and checkout-flow optimization supported for e-commerce, with analytics tied to tests and overlays to improve conversion paths " Apptimize and Optimizely approach funnel and journey analysis from different experimentation contexts.	Apptimize and Optimizely approach funnel and journey analysis from different experimentation contexts.
Revenue attribution capabilities Apptimize and Optimizely approach revenue attribution capabilities from different experimentation contexts.	Revenue attribution integrated with app optimization Apptimize and Optimizely approach revenue attribution capabilities from different experimentation contexts.	Revenue impact analysis powered through experiment goals, analytics connectors, and a digital experience optimization stack Apptimize and Optimizely approach revenue attribution capabilities from different experimentation contexts.	"Conversion tracking, revenue per visitor, average order value, and e-commerce metrics are part of CRO results reporting when tests affect checkout or purchase flows" Apptimize and Optimizely approach revenue attribution capabilities from different experimentation contexts.	Apptimize and Optimizely approach revenue attribution capabilities from different experimentation contexts.
Session replay available Session replay is not a defining capability for either Apptimize or Optimizely in this comparison.	Session replay functionality for mobile apps Session replay is not a defining capability for either Apptimize or Optimizely in this comparison.	Session replay is available through the Optimizely Data website and partner stack from the Contentsquare ecosystem. Core experimentation pages focus more on experiments than replay details Session replay is not a defining capability for either Apptimize or Optimizely in this comparison.	"Not emphasized. Omniconvert focuses on experiments, personalization, overlays, and CRO rather than deep session recording or replay analytics in core feature lists " Session replay is not a defining capability for either Apptimize or Optimizely in this comparison.	Session replay is not a defining capability for either Apptimize or Optimizely in this comparison.
Heatmaps available Heatmaps are not central to either Apptimize or Optimizely, as both focus more on experimentation than visual analytics.	"Heatmaps for click, scroll, and user interaction tracking" Heatmaps are not central to either Apptimize or Optimizely, as both focus more on experimentation than visual analytics.	Heatmap functionality is provided through integrations with experience analytics partners rather than as a flagship feature on experimentation product pages Heatmaps are not central to either Apptimize or Optimizely, as both focus more on experimentation than visual analytics.	Heatmaps and scroll maps are mentioned among CRO tools that integrate analytics and user-behavior visualization to help understand conversion bottlenecks and UX friction Heatmaps are not central to either Apptimize or Optimizely, as both focus more on experimentation than visual analytics.	Heatmaps are not central to either Apptimize or Optimizely, as both focus more on experimentation than visual analytics.
Form analytics available Optimizely evaluates form changes within web experiments, while Apptimize centers its analytics on mobile interaction flows.	Available for form-based interactions in mobile apps Optimizely evaluates form changes within web experiments, while Apptimize centers its analytics on mobile interaction flows.	Form performance analysis is handled through experiment goals and external analytics connectors rather than a labeled standalone form analytics module Optimizely evaluates form changes within web experiments, while Apptimize centers its analytics on mobile interaction flows.	Form performance is influenced and tracked through experiments and overlays. Form analytics is not separated as a distinct module in the core documentation Optimizely evaluates form changes within web experiments, while Apptimize centers its analytics on mobile interaction flows.	Optimizely evaluates form changes within web experiments, while Apptimize centers its analytics on mobile interaction flows.
Statistical approach Both Apptimize and Optimizely apply statistical validation to experiment outcomes, though Optimizely positions this across a wider range of digital environments.	Statistical analysis for A/B testing and optimization Both Apptimize and Optimizely apply statistical validation to experiment outcomes, though Optimizely positions this across a wider range of digital environments.	Proprietary Stats Engine offering false discovery rate control, sample size planning, and guardrails against p-hacking Both Apptimize and Optimizely apply statistical validation to experiment outcomes, though Optimizely positions this across a wider range of digital environments.	"A/B testing and split testing evaluation are integrated into the website. Statistical significance is handled by the tool’s analysis engine, built into the CRO suite " Both Apptimize and Optimizely apply statistical validation to experiment outcomes, though Optimizely positions this across a wider range of digital environments.	Both Apptimize and Optimizely apply statistical validation to experiment outcomes, though Optimizely positions this across a wider range of digital environments.
Sample size calculator available Optimizely provides experiment planning tools such as sample size estimation, while Apptimize focuses more on execution within mobile contexts.	"Yes, available to estimate sample sizes for experiments" Optimizely provides experiment planning tools such as sample size estimation, while Apptimize focuses more on execution within mobile contexts.	The sample size calculator is described as part of the Stats Engine toolkit for feature experimentation Optimizely provides experiment planning tools such as sample size estimation, while Apptimize focuses more on execution within mobile contexts.	"Experiment setup guided by visitor quotas, while an explicit sample size calculator is not highlighted, segmentation and traffic data help approximate test size needs " Optimizely provides experiment planning tools such as sample size estimation, while Apptimize focuses more on execution within mobile contexts.	Optimizely provides experiment planning tools such as sample size estimation, while Apptimize focuses more on execution within mobile contexts.
Experiment duration estimator Apptimize and Optimizely approach experiment duration estimator from different experimentation contexts.	Available for estimating test duration and significance Apptimize and Optimizely approach experiment duration estimator from different experimentation contexts.	Experiment duration planning supported through Stats Engine guidance and sample size tools Apptimize and Optimizely approach experiment duration estimator from different experimentation contexts.	Duration and traffic-driven experiment timelines managed via tested-user quotas and result tracking rather than an explicit duration estimator UI in public marketing pages Apptimize and Optimizely approach experiment duration estimator from different experimentation contexts.	Apptimize and Optimizely approach experiment duration estimator from different experimentation contexts.
Automatic stopping rules Both Apptimize and Optimizely include controls for managing experiment duration and rollout decisions.	Automatic stopping based on statistical significance or user-defined criteria Both Apptimize and Optimizely include controls for managing experiment duration and rollout decisions.	Automatic decision support in Stats Engine through error rate control and significance rules that guide conclusion timing Both Apptimize and Optimizely include controls for managing experiment duration and rollout decisions.	"Statistical results and traffic thresholds determined the experiment conclusion. The tool requires a manual end-of-test decision after results are reviewed, rather than automated stop logic (as per public feature description) " Both Apptimize and Optimizely include controls for managing experiment duration and rollout decisions.	Both Apptimize and Optimizely include controls for managing experiment duration and rollout decisions.
Support for holdout groups Apptimize and Optimizely approach support for holdout groups from different experimentation contexts.	Holdout groups supported for comparison against test groups Apptimize and Optimizely approach support for holdout groups from different experimentation contexts.	Holdout and ramp-up patterns are supported in feature experimentation for safe rollouts and phased exposure Apptimize and Optimizely approach support for holdout groups from different experimentation contexts.	Control groups or visitor segmentation is possible through targeting rules to isolate a subset of traffic outside experiments or overlays Apptimize and Optimizely approach support for holdout groups from different experimentation contexts.	Apptimize and Optimizely approach support for holdout groups from different experimentation contexts.
CMS integrations Optimizely integrates with CMS environments for web experimentation, while Apptimize integrates through mobile SDKs rather than CMS platforms.	Integrates with CMS platforms through SDKs and custom scripts Optimizely integrates with CMS environments for web experimentation, while Apptimize integrates through mobile SDKs rather than CMS platforms.	Implementation through snippets, SDKs, and integrations with modern CMS and digital experience websites referenced in partner and agency guides Optimizely integrates with CMS environments for web experimentation, while Apptimize integrates through mobile SDKs rather than CMS platforms.	Browser-agnostic snippet works with major CMS and e-commerce websites. Documented compatibility for Shopify and generic web CMSs Optimizely integrates with CMS environments for web experimentation, while Apptimize integrates through mobile SDKs rather than CMS platforms.	Optimizely integrates with CMS environments for web experimentation, while Apptimize integrates through mobile SDKs rather than CMS platforms.
E-commerce website integrations Apptimize and Optimizely approach e-commerce website integrations from different experimentation contexts.	"Integrates with Shopify, WooCommerce, and other e-commerce platforms" Apptimize and Optimizely approach e-commerce website integrations from different experimentation contexts.	Strong presence in retail and commerce experimentation through SDKs and analytics connectors; specific store plugins described in partner content Apptimize and Optimizely approach e-commerce website integrations from different experimentation contexts.	"Explicit Shopify app listing and support for e-commerce experiments, checkout flows, overlays, and personalization for online stores" Apptimize and Optimizely approach e-commerce website integrations from different experimentation contexts.	Apptimize and Optimizely approach e-commerce website integrations from different experimentation contexts.
Analytics integrations Optimizely connects experiment results to analytics ecosystems, whereas Apptimize integrates mobile experiment data into app analytics workflows.	"Integrates with Google Analytics, Mixpanel, and other analytics tools" Optimizely connects experiment results to analytics ecosystems, whereas Apptimize integrates mobile experiment data into app analytics workflows.	Integrations with analytics suites, data warehouses, and BI tools; position as warehouse native analytics partner in Optimizely Analytics line Optimizely connects experiment results to analytics ecosystems, whereas Apptimize integrates mobile experiment data into app analytics workflows.	"Integrates with standard analytics suites, supports Google Analytics and data-layer events for experimentation and CRO measurement" Optimizely connects experiment results to analytics ecosystems, whereas Apptimize integrates mobile experiment data into app analytics workflows.	Optimizely connects experiment results to analytics ecosystems, whereas Apptimize integrates mobile experiment data into app analytics workflows.
CDP or data warehouse integrations Apptimize and Optimizely approach cdp or data warehouse integrations from different experimentation contexts.	Integrates with major CDPs and data warehouses for advanced data analysis Apptimize and Optimizely approach cdp or data warehouse integrations from different experimentation contexts.	Pre-built connectors for warehouse native analytics and experimentation reporting are called out on the plans page Apptimize and Optimizely approach cdp or data warehouse integrations from different experimentation contexts.	"Data export and integration via analytics connectors or custom data-layer events. No dedicated CDP integration publicly emphasized, but flexible through API/analytics link-ups " Apptimize and Optimizely approach cdp or data warehouse integrations from different experimentation contexts.	Apptimize and Optimizely approach cdp or data warehouse integrations from different experimentation contexts.
Marketing automation or CRM integrations Optimizely integrates experimentation insights into marketing ecosystems, while Apptimize integrations are typically aligned with mobile analytics and product systems.	Integrates with CRM systems for targeted marketing automation Optimizely integrates experimentation insights into marketing ecosystems, while Apptimize integrations are typically aligned with mobile analytics and product systems.	Integrations with marketing automation, CRM, and engagement websites are supported through feature experimentation and analytics pipelines Optimizely integrates experimentation insights into marketing ecosystems, while Apptimize integrations are typically aligned with mobile analytics and product systems.	Configurable via event tracking and visitor data layers. Overlay/survey results and segmentation can feed into marketing automation or CRM workflows Optimizely integrates experimentation insights into marketing ecosystems, while Apptimize integrations are typically aligned with mobile analytics and product systems.	Optimizely integrates experimentation insights into marketing ecosystems, while Apptimize integrations are typically aligned with mobile analytics and product systems.
Tag manager integrations Apptimize and Optimizely approach tag manager integrations from different experimentation contexts.	Supports integrations with Google Tag Manager and other tag management systems Apptimize and Optimizely approach tag manager integrations from different experimentation contexts.	Implementation through tag managers and direct snippet, as documented for web experimentation setup Apptimize and Optimizely approach tag manager integrations from different experimentation contexts.	Works through snippet or tag manager-based deployment. Compatible with typical tag manager workflows across CMS and e-commerce websites Apptimize and Optimizely approach tag manager integrations from different experimentation contexts.	Apptimize and Optimizely approach tag manager integrations from different experimentation contexts.
API available Both Apptimize and Optimizely provide APIs to extend experimentation workflows.	REST API for data tracking and integration with other systems Both Apptimize and Optimizely provide APIs to extend experimentation workflows.	"Feature Experimentation and website documentation expose APIs for decisions, events, and configuration " Both Apptimize and Optimizely provide APIs to extend experimentation workflows.	"API endpoints and integration hooks available under the CRO suite for custom event tracking, segmentation, and experiment management" Both Apptimize and Optimizely provide APIs to extend experimentation workflows.	Both Apptimize and Optimizely provide APIs to extend experimentation workflows.
Webhooks available Both Apptimize and Optimizely support webhook-based integrations for event-driven workflows.	Webhook support for data syncing and event-based notifications Both Apptimize and Optimizely support webhook-based integrations for event-driven workflows.	Event-driven webhooks are referenced in the developer and integration documentation for automation Both Apptimize and Optimizely support webhook-based integrations for event-driven workflows.	Webhook support and integration with external services are possible via event tracking and custom triggers defined in CRO settings Both Apptimize and Optimizely support webhook-based integrations for event-driven workflows.	Both Apptimize and Optimizely support webhook-based integrations for event-driven workflows.
No code visual editor Optimizely offers visual tools for web experiment creation, while Apptimize focuses more on SDK-driven configuration within mobile apps.	No-code visual editor for mobile app testing and optimization Optimizely offers visual tools for web experiment creation, while Apptimize focuses more on SDK-driven configuration within mobile apps.	Visual editor for web experiments that allows marketers to create variations without direct code edits Optimizely offers visual tools for web experiment creation, while Apptimize focuses more on SDK-driven configuration within mobile apps.	"Visual WYSIWYG editor for building A/B testing, overlays, personalization, and survey creation, enabling marketer-driven workflows " Optimizely offers visual tools for web experiment creation, while Apptimize focuses more on SDK-driven configuration within mobile apps.	Optimizely offers visual tools for web experiment creation, while Apptimize focuses more on SDK-driven configuration within mobile apps.