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TOOL COMPARISONSOctober 26, 20267 min read

VWO vs Optimizely: Testing With Heatmaps or With a CMS

JH

By Joris van Huët

Enterprise Interim CMO & Marketing Leader · 15+ years · 50+ orgs

Published

2026-10-26

The short answer: neither vendor publishes a price, so the decision turns on what sits around the test. If your team wants heatmaps, recordings and experiments on one platform and a trial before any sales call, VWO, sold as Wingify since its merger with AB Tasty, offers 30 days without a card and quotes on monthly active users (Wingify pricing, checked on 26 October 2026). If your content already lives in Optimizely's CMS, or engineering runs server-side flags and wants analytics on its own data warehouse, Optimizely packages a plan around that, every one individually (Optimizely plans).

Disclosure: I may earn a commission through some links on this site. It does not change what this page says.

Before either demo:

  1. Measure how much testing happens now. For example, 6 tests last year at 4 weeks each is 24 test-weeks out of 52, so the testing tool sat idle for more than half the year; a larger platform will not fill a thin backlog, and both vendors will price the platform, not the backlog. Count yours from last year's records before the first call.
  2. Start from the stack you already pay for. Optimizely's CMS lists native testing and personalization, and its experimentation plan lists warehouse-native analytics (Optimizely plans); Wingify reads behaviour data it collects itself, from journeys and intent to on-site feedback (Wingify homepage). A CMS contract, a data warehouse or a separate behaviour tool already in place moves the answer before any feature does.
  3. Pick one programme measure and take it by hand first. The quarterly win rate, the share of experiments that reached significance with a positive result, is an example prompt in Optimizely's MCP documentation (example prompts). Work out last year's figure in a spreadsheet, so an agent's answer later has something to be checked against.

First, the name

The address vwo.com now opens wingify.com, where a banner says AB Tasty and VWO have united. The merger was announced on 20 January 2026; the combined company reports more than $100M in revenue and over 4,000 customers, and existing VWO contracts, pricing, service levels and support stay unchanged (merger announcement). A VWO trial or quote now starts at Wingify, so that is the platform compared here.

On the page, side by side

On the vendor's pageVWO, sold as WingifyOptimizely
What is soldSix suites on one customer profile (homepage)A CMS, experimentation and an agent platform (plans)
How a price is setProposal on monthly active users (pricing)Every plan individually packaged (plans)
Starting without sales30-day trial, no card (pricing)A conversation; no trial on the plans page
StatisticsBayesian or frequentist, fixed before launch (statistics guide)Stats Engine with confidence intervals and false discovery rate control (results docs)
Traffic imbalanceSRM detection in the Pro tier (pricing)Traffic counts checked continuously for SRM (results docs)
Behaviour dataHeatmaps, recordings, funnels, forms, surveys in-platform (Wingify's comparison)Not among the plan features listed (plans)
Agent accessMCP with read and write tools, EU endpoint available (MCP guide)Experimentation MCP server; Agent Platform must be enabled (MCP overview)

What separates them

What arrives with the test

Wingify's homepage pitches a loop: understand, decide, act and measure, all on one data foundation (Wingify homepage). Optimizely's is the wider estate: an agentic CMS with built-in content approvals, experimentation with web, feature and server-side tests, and an agent platform with its own library of agents (Optimizely plans). Wingify's own comparison page claims Optimizely relies on third-party connectors for heatmaps and recordings (Wingify vs Optimizely); treat that as one vendor's reading and ask Optimizely directly.

The statistics you will be asked to defend

Wingify lets each campaign run on Bayesian or frequentist statistics, declares a winner at a threshold that is typically 95%, and computes nothing before 500 visitors and a baseline conversion (statistics guide). Optimizely's Stats Engine applies false discovery rate control and is built so the primary metric reaches significance as fast as it can, with secondary metrics slower as you add them (results docs). Both are defensible. The one to choose is the one your analyst can explain to a finance director without a slide.

Prices: both on request

Neither vendor printed a figure on 26 October 2026. Wingify's FAQ prices on monthly active users, or tracked users for behaviour analytics, discounts bundles and multi-year deals, and gives non-profits preferential rates (Wingify pricing, checked on 26 October 2026). Optimizely's plans page asks about your digital needs and builds a plan from them (Optimizely plans, checked the same day). So write your own comparison line before the calls: twelve months of active users, the number of experiments planned, the products needed on day one and those you are only curious about, and ask both quotes to price the two groups separately.

The agent step: a programme audit in three prompts

Optimizely documents a chained audit for its Experimentation MCP server: list experiments running more than 30 days, keep those that reached significance, then summarise their results with metrics, lift and confidence (example prompts). On Wingify, ask which campaigns have had no winner in the last three months, then pull each campaign's report through the same connector (MCP guide).

The human check: before anyone stops or ships a test on the strength of that summary, the analyst opens each results page in the product, checks visitors per variation against the plan, and confirms no traffic imbalance was flagged. Writes stay behind confirmation on both sides: Optimizely's agent confirms the project and environment before committing a change, and Wingify will not let Claude edit a running campaign until it is paused (MCP overview, Claude connector guide).

The route to that agent is also a line on the quote. Optimizely's MCP server needs the Agent Platform enabled on the account, and the plans page sells that platform as a product of its own; Wingify gives MCP access free with paid products but keeps behaviour data in it for Wingz Advanced, a paid upgrade (MCP overview, Wingify pricing). On both, the agent you see in a demo can be a separate line on the invoice, so ask which plan in your quote carries it.

Choose VWO if

  • Your job is a testing programme fed by heatmaps, recordings and surveys from the same platform (Wingify's comparison).
  • You want 30 days of hands-on trial before a sales conversation.
  • You already hold a VWO contract, which carries on under the Wingify name.

Choose Optimizely if

  • Your job is experimentation tied to content in Optimizely's CMS, or feature flags run by engineering.
  • Your analysts work from a data warehouse and want experiment analysis there (Optimizely plans).
  • You plan to build agents on a platform the vendor also sells for content and commerce.

When the question is the stack

Sometimes this comparison hides a bigger decision: whether one vendor should hold the website, the experiments and the customer profile together. That is a question about the whole stack rather than the testing tool, and the Startup Fixer, a fixed one-week review that I sell, answers it before either suite is signed.

FAQ

Can I still buy VWO?

Yes, as Wingify. The merger announcement keeps existing VWO contracts and pricing unchanged, and new trials and quotes start at wingify.com (merger announcement).

Does Optimizely publish a price or a trial?

Not on its plans page, read on 26 October 2026: it says every plan is individually packaged and invites you to build one with its team (Optimizely plans).

Can an agent change a running experiment?

On Wingify, not until the campaign is paused (Claude connector guide). On Optimizely, the MCP server can create and update experiments after the agent confirms the target, but variation code for Web Experimentation is changed in the Visual Editor, not through MCP (MCP overview).

TAGS
VWOWingifyOptimizelyA/B TestingExperimentation Platforms

ABOUT THE AUTHOR

I am Joris van Huët, an enterprise interim CMO. 15+ years, 50+ organizations, including ING, P&G, Nestlé, BNP Paribas, WeTransfer and Vinted. I take on innovation projects (venture building, design sprints), agentic marketing (setting up and running AI agents) and hands-on multi-channel work. See the track record.

I wrote and published this with AI assistance, and I answer for it. Claims about my own experience are limited to the track record above, and a statistic links to its source or is labelled as an example. I sell interim and fractional CMO work, which is why this site exists. How this site is written.

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