Experimentation and personalization
Asked as “website experimentation and personalization platform”, and as “A/B testing and personalization tool”, on behalf of a mid-market B2B software company. 55 first choices recorded across the direct, paraphrase, budget and scale prompts, six models each.
Standing · first-choice share
27%
Contested · Convert Experiences 24%
27VWO24Convert Experiences15GrowthBook35others
27% of first choices, contested.
Since September 2026▼−8Since September 2026: 34% → 26%, −8 points. Inside the 12-point floor: within noise. Read over the models both editions asked.VWO held the lead, −8 points on 34%, inside the 12-point floor.
The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all six models, for a mid-market B2B software company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince September 2026
01
VWO27%11%56accepted challenger▼−8Since September 2026: 34% → 26%, −8 points. Inside the 12-point floor: within noise. Read over the models both editions asked.34% → 26%
VWO27%11%56accepted challenger▼−8Since September 2026: 34% → 26%, −8 points. Inside the 12-point floor: within noise. Read over the models both editions asked.34% → 26%02
Convert Experiences24%0%33accepted challenger▲+8Since September 2026: 15% → 23%, +8 points. Inside the 12-point floor: within noise. Read over the models both editions asked.15% → 23%
Convert Experiences24%0%33accepted challenger▲+8Since September 2026: 15% → 23%, +8 points. Inside the 12-point floor: within noise. Read over the models both editions asked.15% → 23%03
GrowthBook15%8%25accepted challenger▲+11Since September 2026: 2% → 13%, +11 points. Past the 12-point floor: movement. Read over the models both editions asked.2% → 13%
GrowthBook15%8%25accepted challenger▲+11Since September 2026: 2% → 13%, +11 points. Past the 12-point floor: movement. Read over the models both editions asked.2% → 13%04
Mutiny7%22%18accepted challenger▲+4Since September 2026: 2% → 6%, +4 points. Inside the 12-point floor: within noise. Read over the models both editions asked.2% → 6%
Mutiny7%22%18accepted challenger▲+4Since September 2026: 2% → 6%, +4 points. Inside the 12-point floor: within noise. Read over the models both editions asked.2% → 6%05
Optimizely CMS7%47%55criticized challenger▲+1Since September 2026: 8% → 9%, +1 point. Inside the 12-point floor: within noise. Read over the models both editions asked.8% → 9%
Optimizely CMS7%47%55criticized challenger▲+1Since September 2026: 8% → 9%, +1 point. Inside the 12-point floor: within noise. Read over the models both editions asked.8% → 9%06
Kameleoon4%0%31accepted challenger=heldSince September 2026: 4% → 4%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.4% → 4%
Kameleoon4%0%31accepted challenger=heldSince September 2026: 4% → 4%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.4% → 4%07
PostHog4%5%19accepted challenger▲+4Since September 2026: 0% → 4%, +4 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 4%
PostHog4%5%19accepted challenger▲+4Since September 2026: 0% → 4%, +4 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 4%Show the five products at 0%, ordered by negative rate
12
Google Optimize Lab in the set0%92%12criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%
Google Optimize Lab in the set0%92%12criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%11
Adobe Target0%58%36criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%
Adobe Target0%58%36criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%10
Dynamic Yield0%38%24criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%
Dynamic Yield0%38%24criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%08
AB Tasty0%13%30accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 12-point floor: within noise. Read over the models both editions asked.2% → 0%
AB Tasty0%13%30accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 12-point floor: within noise. Read over the models both editions asked.2% → 0%09
Statsig0%0%14accepted challenger▼−4Since September 2026: 4% → 0%, −4 points. Inside the 12-point floor: within noise. Read over the models both editions asked.4% → 0%
Statsig0%0%14accepted challenger▼−4Since September 2026: 4% → 0%, −4 points. Inside the 12-point floor: within noise. Read over the models both editions asked.4% → 0%The floor is 12 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. How the floor is measured
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its product page.
Google Optimize is made by Google, whose model Gemini 3.1 Pro is in the set. On the four share prompts that model made it the first choice zero times of 4; the other five models zero times of 20. Lab treatment is defined on the method page; the row is marked, not excluded.
All ten head-to-head pages: the top five products, each against each
Recommended versus criticized
Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.
Criticized challengerCriticized default
Negative label rate →
010203040506070809101112Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative40%
Key
01VWO27%
VWO27%02Convert Experiences24%
Convert Experiences24%03GrowthBook15%
GrowthBook15%04Mutiny7%
Mutiny7%05Optimizely CMS7%
Optimizely CMS7%06Kameleoon4%
Kameleoon4%07PostHog4%
PostHog4%08AB Tasty0%
AB Tasty0%09Statsig0%
Statsig0%10Dynamic Yield0%
Dynamic Yield0%11Adobe Target0%
Adobe Target0%12Google Optimize0%
Google Optimize0%What they warned about
A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
Optimizely CMS47%
26 of 55 labels negative · 11 of 6 models · 4 hard negative
“more enterprise-y, pricier ~$36K/yr min, dev-heavy). Avoid if mid-market budget/timeline constrained.” Grok 4.20, direct prompt
Adobe Target58%
21 of 36 labels negative · 11 of 6 models · 2 hard negative
“Force you into a **closed ecosystem** (Adobe Target unless you're already all-in on Adobe)” DeepSeek V4 Flash, negative prompt
Google Optimize92%
11 of 12 labels negative · 9 of 6 models · 10 hard negative
“Google Optimize (the former standard for small-to-mid-size businesses) was sunsetted in late 2023, forcing many users to migrate to other solutions.” Qwen 3.7 Flash, comparative prompt
Dynamic Yield38%
9 of 24 labels negative · 6 of 6 models · 1 hard negative
“Charge **enterprise prices without transparency** (Dynamic Yield, Adobe Target)” DeepSeek V4 Flash, negative prompt
What they cite
Citations exist only for the models that return a source list: fourteen of the six in this edition.
Sites the answers cite
78 of 84 answers in this category came back with a source list, from 14 of 6 models: citations where the model returns them, or the search results it consulted. 1152 links across 297 sites, every framing counted. Ranked by the number of answers carrying the site or page. None of the 36 answers across every segment cited this index's own page for the category.
vendor site · Mida37 answers · 45 citations · 11 models
vendor site · Contentsquare33 answers · 44 citations · 12 models
vendor site · Convert31 answers · 50 citations · 12 models
vendor site · Optimizely26 answers · 38 citations · 14 models
vendor site · Guideflow25 answers · 33 citations · 12 models
vendor site · Kameleoon25 answers · 30 citations · 12 models
vendor site · Webflow25 answers · 25 citations · 12 models
vendor site · Personyze23 answers · 24 citations · 11 models
21 answers · 41 citations · 10 models
vendor site · GrowthBook19 answers · 41 citations · 10 models
17 answers · 19 citations · 11 models
16 answers · 23 citations · 7 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
25 answers · 10 models
25 answers · 12 models
21 answers · 10 models
18 answers · 10 models
17 answers · 11 models
16 answers · 10 models
16 answers · 9 models
15 answers · 8 models
15 answers · 10 models
15 answers · 8 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “best website experimentation and personalization platform”, “website experimentation and personalization platform”. US estimates from DataForSEO and Google's Ads Transparency Center. A small company's site, or a mid-sized company's site for its flagship, is marked company; a product on a large parent's site (Google, Microsoft) has no site figures. A column with no figures for this category is left out, and an empty cell means none were seen, not none exist. Two measurements side by side: neither is read as the cause of the other.
| Company and products | Share | Own site cited | Name searches, Google | AI search demand, est. | Organic visits | Paid search a month, est. | Google ads, last 30 days | Best Google position |
|---|---|---|---|---|---|---|---|---|
| VWO vwo.com | 27% | 156 | 22,200 | 449 | 25,874 | 14 | 5 | |
| Convert Experiences convert.com | 24% | 80 | 50 | 22 | 20,882 | 1 | ||
| GrowthBook growthbook.io | 15% | 71 | 2,900 | 14 | 26,646 | 26 | ||
| Optimizely optimizely.com Optimizely CMS 7%, Optimizely Web Experimentation 4% | 11% | 237 | 60,500 | 36,211 | 200,757 company | $2 | 120 | 3 |
| Mutiny mutinyhq.com | 7% | 71 | 110,000 | 3,032 | 680 | 0 | ||
| Kameleoon kameleoon.com | 4% | 82 | 590 | 3 | 28,601 | 3 | ||
| PostHog posthog.com | 4% | 355 | 33,100 | 271 | 25,936 | 120 | ||
| Personyze personyze.com | 2% | 19 | 50 | 1 | 536 | 0 | ||
| Mida mida.so | 2% | 16 | 49,500 | 18,197 | 33,190 | 3 | 2 | |
| Croct croct.com | 2% | 8 | 7 |
Google's top ten for the two searches hold 17 sites; 3 of them are among the sites the models cited here (guideflow.com, mida.so, optimizely.com). The first result for “best website experimentation and personalization platform” is gartner.com.
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.ShowHide
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ShowHideModelDirect“What is the best website experimentation and personalization platform for a mid-market B2B company?”Paraphrase“Which A/B testing and personalization tool would you recommend to a mid-sized B2B company?”Comparative“What are the top experimentation and personalization platforms and how do they differ?”Budget-constrained“What is the best website experimentation and personalization platform for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a website experimentation and personalization platform. What should we look at?”Negative“Which experimentation and personalization platforms should I avoid or be cautious about?”
Claude Opus 5no first choiceno first choiceno first choiceno first choiceno first choicenothing named
Claude Opus 4.8no first choiceno first choiceno first choiceno first choiceno first choicenothing named
GPT-6 Astrano first choiceno first choiceno first choiceno first choiceno first choicenothing named
GPT-5.6 Solno first choiceno first choiceno first choiceno first choiceno first choicenothing named
Gemini 3.1 Prono first choiceno first choiceno first choiceno first choiceno first choicenothing named
Perplexity Sonar Prono first choiceno first choiceno first choiceno first choiceno first choicenothing named
Bold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency. Full answer text is in the free responses file. Download the record
Zero rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
ShowHide
Category-scoped readings
Adobe read as Adobe Target
Convert read as Convert Experiences
Convert (Convert Experiences) read as Convert Experiences
Convert (Convert.com) read as Convert Experiences
Convert.com read as Convert Experiences
Convert.com (Convert Experiences) read as Convert Experiences
Salesforce Personalization read as Salesforce Marketing Cloud Personalization
Unresolved, counted raw
Contentsquare Convert
Datadog Experiments
Dynamic Yield – now Mastercard Dynamic Yield
Hello Bar
Rebuy
Salesforce
Shogun A/B tools
VWO Testing
VWO – Visual Website Optimizer
Discontinued, still offered
No shut-down product was recommended here.