Clarity
Do they understand what you do?
Strong15 of 15
15 could name what kind of product this is, unprompted.
Saved report, kept for 60 days — expires in 44 days. Re-opening it is free.
01
Your verdict
Relevance
Can they tell what it solves, and who it's for?
Strong15 of 1515 could quickly tell what problem it solves and who it is for.
Value
Do they actually want it?
Mixed10 of 1510 would take a meeting to learn more.
Differentiation
Fix firstIs there a reason to pick you over the alternatives?
Fail4 of 154 could name a reason to pick you over a similar option.
See what they thought you were
Your page describes: attribution software. They said:
- 1×Marketing/Revenue Attribution Softwarematches
14 couldn't name one; 1 got it right.
Four separate measures, not stages: all 15 personas answered all four questions. Each square is one persona.
Additional signalBrand alignment11 of 15MixedShow finding ▸
Two respondents flagged a credibility gap: the case studies are stated confidently while the FAQ stays silent on the obvious questions, and the jargon-heavy messaging offers nothing to a budget decision-maker. The mismatch between assertion and proof was read as a tone problem, not just a content gap. Not one of the four layers, and it does not affect the scores above or the order to fix them in.
These are 15 simulated buyers. Want 15 real ones?
Test with humans02
Fix these firstFix these first
Three edits, in the order that matters.
The first is on your weakest layer, the second on the next, the third on the layer the most buyers had a problem with. Each says what to change on the page and why, with one simulated answer behind it.
State what Atlas does that a warehouse plus BI cannot.
Why: 'Atlas is HockeyStack's data foundation that ingests, unifies, and actions your GTM data' reads as the same pipeline story every competitor tells, and 'Reasoning Layer' compounds it. Say the specific thing: which identity matches Atlas resolves that last-touch and CRM-based models drop, and what percentage of anonymous account activity it recovers. A named, checkable capability separates the section; 'data foundation' does not.
2 of 15 raised this
“to pick this one I'd need a side-by-side or at least a named customer saying why they left one of those for HockeyStack, not just a case study…” Show full quote
“to pick this one I'd need a side-by-side or at least a named customer saying why they left one of those for HockeyStack, not just a case study headline”
Senior Demand Generation Manager, Technology Services · 51-200 employeessimulated Moves DifferentiationConcrete over abstractAdd lift report specifics beside the incrementality claim.
Why: 'Lift reports compare exposed and unexposed accounts to prove which campaigns actually drive conversions' is the one line readers repeat back — and the one they immediately qualify with 'if proven'. Right now the word 'prove' is doing work nothing on the page supports. Put the mechanics next to the claim: how control (unexposed) accounts are selected, minimum account volume needed for a readable result, and the confidence or significance threshold the report uses. A single named example — 'a…
6 of 15 raised this
“no sample dashboard, no methodology for the lift reports (what's the control group, how do they define "unexposed"?)”
Head of Demand Generation, B2B SaaS · 1001-5000 employeessimulated Moves ValueProof next to the claimDefine 'Atlas' and 'Agents' where each term first appears.
Why: 'HockeyStack Agents: Forecast Challenger' and the ATLAS section both use branded names before the reader knows what they are, and 'Reasoning Layer' compounds it with an undefined internal term. Add a plain gloss at first mention — Atlas as the ingestion and identity-resolution layer, Agents as the automated recommendation feature — so readers stop reverse-engineering the data flow to work out what the product does.
5 of 15 raised this
“phrases like "actionable source of truth" and "reasoning layer" are the kind of vendor filler that don't tell you anything mechanical, so I had to infer that Atlas…” Show full quote
“phrases like "actionable source of truth" and "reasoning layer" are the kind of vendor filler that don't tell you anything mechanical, so I had to infer that Atlas is just ETL plus identity resolution”
Head of Demand Generation, B2B SaaS · 1001-5000 employeessimulated Moves ClarityPlain language
Keep these · 3
These landed. Keep the wording when you edit around it.
- Keep · Relevance
The hero line and audience callout are the one part respondents read cleanly
“the hero line "Modern Attribution that captures the complete buyer journey. From first touch to closed-won" tells you the problem (fragmented marketing/sales data, no clear pipeline attribution) and…” Show full quote
“the hero line "Modern Attribution that captures the complete buyer journey. From first touch to closed-won" tells you the problem (fragmented marketing/sales data, no clear pipeline attribution) and the fix in one breath. The "Empower Every Revenue Team" section spells out the audience directly: Marketing Leaders, GTM Operations, Sales Leaders”
Demand Generation Manager, Enterprise Software · 5000+ employeessimulated - Keep · Value
Lift and incrementality is the claim respondents could repeat back and wanted to be true
“The Lift & Incrementality piece — "compare exposed and unexposed accounts to prove which campaigns actually drive conversions... ideal for low-volume, high-impact programs like events and content" —…” Show full quote
“The Lift & Incrementality piece — "compare exposed and unexposed accounts to prove which campaigns actually drive conversions... ideal for low-volume, high-impact programs like events and content" — is the one thing here that could actually differentiate this from a Bizible or Dreamdata”
Head of Demand Generation, B2B SaaS · 1001-5000 employeessimulated - Keep · Brand alignment
The tone lands with marketing leaders under budget pressure
“it skips the 101 explainer and goes straight into "attribution model," "dark funnel," "lift and incrementality," which assumes I already know why last-touch CRM data is garbage. That's…” Show full quote
“it skips the 101 explainer and goes straight into "attribution model," "dark funnel," "lift and incrementality," which assumes I already know why last-touch CRM data is garbage. That's a plus”
Demand Generation Manager, Technology Services · 1001-5000 employeessimulated
03
All recommendations
Differentiation
Fail4 of 15Moves DifferentiationGive a reason to choose you
Add a switching section for teams leaving an incumbent tool.
Why: Readers standing next to Bizible or Dreamdata found no reason to move. Add a short block that names the migration case in their terms — historical data backfill, how long parallel running takes, what breaks in existing QBR reporting — and one customer who switched, with what changed in their reports. This answers the objection an evaluator is already holding without asking them to infer it from feature lists.
2 of 15 raised this
“to pick this one I'd need a side-by-side or at least a named customer saying why they left one of those for HockeyStack, not just a case study…” Show full quote
“to pick this one I'd need a side-by-side or at least a named customer saying why they left one of those for HockeyStack, not just a case study headline”
Moves DifferentiationGive a reason to choose you
Replace 'source of truth' hero with the incrementality claim.
Why: 'Modern Attribution that captures the complete buyer journey' and 'one actionable source of truth' are lines Bizible, Dreamdata and every other attribution vendor could run unchanged. The one idea readers could not find elsewhere — proving causation by comparing exposed and unexposed accounts — is buried as the third feature card. Lead with it: name causal measurement, not attribution coverage, in the H1 and subhead.
2 of 15 raised this
“to pick this one I'd need a side-by-side or at least a named customer saying why they left one of those for HockeyStack, not just a case study…” Show full quote
“to pick this one I'd need a side-by-side or at least a named customer saying why they left one of those for HockeyStack, not just a case study headline”
Value
Mixed10 of 15Moves ValueProof next to the claim
Add a before/after case study for lift specifically.
Why: The case studies on the page ('cutting ad spend in half', '8x8's Marketing Team Drives Business Growth') sit far from the Lift & Incrementality block and don't say what the lift report showed. Readers wanting to act on incrementality asked for a before/after against their own numbers. Publish one case with the prior attribution read, the lift-report read, and the budget decision that followed — dollars moved, program killed or scaled — placed directly under the Lift & Incrementality copy…
6 of 15 raised this
“no sample dashboard, no methodology for the lift reports (what's the control group, how do they define "unexposed"?)”
Moves ValueAnswer the live objection
Offer a validation pilot against recent closed-won deals.
Why: The only CTAs are 'Get a Demo' and 'Live Preview', neither of which answers the question buyers actually hold: does this match my CRM? Add a named, bounded next step under the Lift section — for example a benchmark run against the last two quarters of closed-won opportunities, with a stated turnaround — so the evaluator has a way to test the claim rather than accept it.
6 of 15 raised this
“no sample dashboard, no methodology for the lift reports (what's the control group, how do they define "unexposed"?)”
Clarity
Strong15 of 15Relevance
Strong15 of 15No specific edits needed here — this layer held up.
Brand alignment
Mixed11 of 15Moves Brand alignmentAnswer the live objection
Answer the obvious measurement objections in the FAQ.
Why: The confident case-study headlines ('hit their monthly revenue targets after cutting ad spend in half') sitting beside a page that never addresses accuracy, minimum data volume, or CRM reconciliation reads as evasion rather than confidence. Name the hard questions in plain terms — what happens when account volume is too low for a lift read, how the numbers reconcile when they disagree with Salesforce — and answer them. Stating a limit raises trust in the claims that remain.
2 of 15 raised this
“that gap between the swagger of the case study headlines and the silence on methodology is what makes we wonder if the substance matches the tone.”
04
Buyer evidence
Biggest risks
A deliberately adversarial read of the same answers. Each claim was checked back against what the personas said and dropped if nothing supported it.
- high
The page's one differentiating claim cannot survive contact with a buying committee, because nobody can act on it without proof the page never supplies.
Six respondents named lift and incrementality as the only substantive idea, and seven attached an explicit 'if proven' condition to it, demanding control group definitions, sample sizes, CRM accuracy benchmarks and before/after case numbers. Three would only advance to a pilot or technical review of a real lift report. The single asset that carries the page is also the single asset that stalls the next meeting.
- high
Strip out incrementality and there is no reason to switch vendors left on the page.
Four respondents filed the product into the standard attribution/GTM analytics category next to Bizible and Dreamdata with no separation, two flagged 'Atlas' and 'source of truth' as language every competitor uses, and two asked for a direct competitor comparison. Since the only claim treated as more than table stakes is the unproven one (theme 6), the page offers incumbents no threat.
- high
Branded vocabulary is doing the work that mechanism explanation should do, and it is costing comprehension.
Six respondents said 'Atlas', 'Agents', 'cookieless tracking', 'dark funnel' and 'industry-best scoring' appear with no definition of how they work, and two had to reverse-engineer the data flows themselves. Two separately named 'Atlas' and 'source of truth' as generic competitor language. The naming buys no differentiation and destroys clarity at the same time.
- medium
Customer logos are carrying the segment positioning the copy refuses to state, which means qualification depends on whether a reader recognises the brands.
Two respondents could not tell whether the platform is built for mid-market or enterprise and inferred fit only from logos; one read the logos as signalling mid-market B2B SaaS. Two respondents also credited case study logos and role tabs with doing persona work in the absence of a stated persona line. Positioning that only works for readers who already know the customer base is not positioning.
- medium
The page is written for someone who already believes attribution matters and locks out the person who signs the cheque.
Three respondents praised the voice for assuming attribution literacy and targeting marketing leaders defending spend, but two said the jargon-heavy messaging offers nothing to a budget decision-maker and that the FAQ stays silent on obvious questions. The literacy assumption that earns credibility with the champion is the same thing that leaves them without material to sell internally.
- medium
Confidence without evidence is reading as evasion, not authority.
Two respondents flagged confidently stated case studies against an FAQ silent on the obvious questions and called it a credibility gap, a tone problem rather than a content gap. Combined with the seven respondents who conditioned the headline claim on proof and the six who found branded terms undefined, the assertive voice reads as concealment.
Differentiation
Outside of incrementality, the page reads as the same category language every competitor…
2 of 15
“to pick this one I'd need a side-by-side or at least a named customer saying why they left one of those for HockeyStack, not just a case study…” Show full quote
“to pick this one I'd need a side-by-side or at least a named customer saying why they left one of those for HockeyStack, not just a case study headline”
Senior Demand Generation Manager, Technology Services · 51-200 employeessimulated See all 3 comments
“Basically a B2B attribution/GTM analytics tool, same category as Dreamdata or Bizible, not something new.”
Director of Demand Generation, Technology Services · 501-1000 employeessimulated “the language ("Modern Attribution," "Atlas," "forward-looking insights") is the same vocabulary every vendor in this space uses, so it reads like a company that understands its market segment…” Show full quote
“the language ("Modern Attribution," "Atlas," "forward-looking insights") is the same vocabulary every vendor in this space uses, so it reads like a company that understands its market segment well but hasn't earned the right to talk to me like they've beaten the incumbents yet”
Director of Demand Generation, Technology Services · 501-1000 employeessimulated
Value
Every respondent who liked the incrementality claim conditioned it on proof that is not…
6 of 15
“no sample dashboard, no methodology for the lift reports (what's the control group, how do they define "unexposed"?)”
Head of Demand Generation, B2B SaaS · 1001-5000 employeessimulated See all 7 comments
“It's basically a Bizible/Dreamdata-type competitor - not something new to me, and given I already run something adjacent, I'd need to see specifics on data accuracy and integration…” Show full quote
“It's basically a Bizible/Dreamdata-type competitor - not something new to me, and given I already run something adjacent, I'd need to see specifics on data accuracy and integration coverage before I'd say this beats what I have.”
Demand Generation Manager, Enterprise Software · 5000+ employeessimulated “I'd want them to show me the 8x8 or ActiveCampaign case study specifics (what stack size, what it replaced, how long setup took) before I'd give it more…” Show full quote
“I'd want them to show me the 8x8 or ActiveCampaign case study specifics (what stack size, what it replaced, how long setup took) before I'd give it more than 30 minutes”
Senior Demand Generation Manager, Technology Services · 51-200 employeessimulated “I'd need to see accuracy benchmarks against my own CRM reporting before I believe the "defend it in the boardroom" line.”
Director of Demand Generation, Technology Services · 501-1000 employeessimulated “But as written it's just a feature description with no proof: no sample size, no definition of what counts as "exposed," no case study number tied specifically to…” Show full quote
“But as written it's just a feature description with no proof: no sample size, no definition of what counts as "exposed," no case study number tied specifically to a lift result”
Director of Demand Generation, B2B SaaS · 201-500 employeessimulated “I'd want them to run a pilot against our own last 2-3 closed-won deals and show me their attribution matches or beats what we already know happened”
Director of Demand Generation, Technology Services · 501-1000 employeessimulated “A real case study with before/after attribution numbers that survived a boardroom challenge — if I could take one customer's data and reconcile it against what our CRM…” Show full quote
“A real case study with before/after attribution numbers that survived a boardroom challenge — if I could take one customer's data and reconcile it against what our CRM currently shows, that's the only thing that would justify pulling budget for this.”
Head of Demand Generation, Enterprise Software · 501-1000 employeessimulated Lift and incrementality is the claim respondents could repeat back and wanted to be true
5 of 15 · what worked
“The Lift & Incrementality piece — "compare exposed and unexposed accounts to prove which campaigns actually drive conversions... ideal for low-volume, high-impact programs like events and content" —…” Show full quote
“The Lift & Incrementality piece — "compare exposed and unexposed accounts to prove which campaigns actually drive conversions... ideal for low-volume, high-impact programs like events and content" — is the one thing here that could actually differentiate this from a Bizible or Dreamdata”
Head of Demand Generation, B2B SaaS · 1001-5000 employeessimulated See all 6 comments
“The "Lift & Incrementality" section is the one thing that could differentiate it — comparing exposed vs. unexposed accounts to prove campaigns actually drive conversions is a real,…” Show full quote
“The "Lift & Incrementality" section is the one thing that could differentiate it — comparing exposed vs. unexposed accounts to prove campaigns actually drive conversions is a real, specific claim, not just "unify your data" fluff”
Senior Demand Generation Manager, Technology Services · 51-200 employeessimulated “the "Lift & Incrementality" bit for proving campaigns like events actually converted is genuinely useful if it holds up, since that's hard to prove with what I have…” Show full quote
“the "Lift & Incrementality" bit for proving campaigns like events actually converted is genuinely useful if it holds up, since that's hard to prove with what I have now.”
Demand Generation Manager, Enterprise Software · 5000+ employeessimulated “If it actually worked, I'd stop arguing in QBRs about whether that dark-funnel content program or that events spend actually moved pipeline — the "Lift & Incrementality" piece…” Show full quote
“If it actually worked, I'd stop arguing in QBRs about whether that dark-funnel content program or that events spend actually moved pipeline — the "Lift & Incrementality" piece comparing exposed vs. unexposed accounts is the one feature that would genuinely change my day-to-day”
Director of Demand Generation, B2B SaaS · 201-500 employeessimulated “The "lift and incrementality" piece is the part that would actually matter to me — proving events and content drive conversions rather than just correlate with them”
Director of Demand Generation, Technology Services · 501-1000 employeessimulated “if this genuinely does exposed-vs-unexposed testing that's a real methodological difference, not a marketing line”
Director of Demand Generation, Technology Services · 501-1000 employeessimulated
Clarity
Branded and buzzword terms are used without any mechanism behind them
5 of 15
“phrases like "actionable source of truth" and "reasoning layer" are the kind of vendor filler that don't tell you anything mechanical, so I had to infer that Atlas…” Show full quote
“phrases like "actionable source of truth" and "reasoning layer" are the kind of vendor filler that don't tell you anything mechanical, so I had to infer that Atlas is just ETL plus identity resolution”
Head of Demand Generation, B2B SaaS · 1001-5000 employeessimulated See all 4 comments
“"Cookieless tracking" and "dark funnel" are the culprits — both get used as if they're self-evidently understood mechanisms, but neither is defined: does cookieless mean IP-based firmographic matching,…” Show full quote
“"Cookieless tracking" and "dark funnel" are the culprits — both get used as if they're self-evidently understood mechanisms, but neither is defined: does cookieless mean IP-based firmographic matching, first-party pixel, email hash matching?”
Director of Demand Generation, B2B SaaS · 201-500 employeessimulated “the friction is words like "Atlas," "Agents," and "one actionable source of truth," which are branded/vague enough that I have to translate them back into normal terms”
Demand Generation Manager, B2B SaaS · 501-1000 employeessimulated “Two phrases did it: "cookieless tracking" and "dark funnel" — both get used as if the mechanism is self-evident, but neither is defined anywhere on the page.”
Senior Demand Generation Manager, Enterprise Software · 1001-5000 employeessimulated
Relevance
Company size and segment fit cannot be determined from the page
2 of 15
“What's less obvious is company size/segment fit — the case studies (8x8, ActiveCampaign, n8n) suggest mid-market to enterprise B2B SaaS, but that's inferred from logos, not stated outright.”
Head of Demand Generation, B2B SaaS · 1001-5000 employeessimulated See all 2 comments
“What's still fuzzy is company size/stack fit — nothing tells me if this is built for a 51-200 person shop like mine or only makes sense at enterprise…” Show full quote
“What's still fuzzy is company size/stack fit — nothing tells me if this is built for a 51-200 person shop like mine or only makes sense at enterprise scale with messy multi-source data.”
Senior Demand Generation Manager, Technology Services · 51-200 employeessimulated The hero line and audience callout are the one part respondents read cleanly
6 of 15 · what worked
“the hero line "Modern Attribution that captures the complete buyer journey. From first touch to closed-won" tells you the problem (fragmented marketing/sales data, no clear pipeline attribution) and…” Show full quote
“the hero line "Modern Attribution that captures the complete buyer journey. From first touch to closed-won" tells you the problem (fragmented marketing/sales data, no clear pipeline attribution) and the fix in one breath. The "Empower Every Revenue Team" section spells out the audience directly: Marketing Leaders, GTM Operations, Sales Leaders”
Demand Generation Manager, Enterprise Software · 5000+ employeessimulated See all 5 comments
“the hero line "Modern Attribution that captures the complete buyer journey... unify your marketing and sales data into one actionable source of truth" tells you the problem (fragmented,…” Show full quote
“the hero line "Modern Attribution that captures the complete buyer journey... unify your marketing and sales data into one actionable source of truth" tells you the problem (fragmented, last-touch-biased marketing/sales data) in the first two lines. The audience is spelled out too, not inferred: "Empower Every Revenue Team — Marketing Leaders, GTM Operations, Sales Leaders"”
Director of Demand Generation, B2B SaaS · 201-500 employeessimulated “the hero line "Modern Attribution that captures the complete buyer journey... Unify your marketing and sales data into one actionable source of truth" tells you the problem (fragmented,…” Show full quote
“the hero line "Modern Attribution that captures the complete buyer journey... Unify your marketing and sales data into one actionable source of truth" tells you the problem (fragmented, last-touch data) and the fix.”
Head of Demand Generation, Enterprise Software · 501-1000 employeessimulated “the "Empower Every Revenue Team" section naming Marketing Leaders, GTM Operations, and Sales Leaders makes it easy to place yourself”
Senior Demand Generation Manager, B2B SaaS · 5000+ employeessimulated “the hero line "Modern Attribution that captures the complete buyer journey. From first touch to closed-won" tells you the problem (disconnected marketing/sales data, no clean pipeline attribution) in…” Show full quote
“the hero line "Modern Attribution that captures the complete buyer journey. From first touch to closed-won" tells you the problem (disconnected marketing/sales data, no clean pipeline attribution) in one breath, and the "Empower Every Revenue Team — Marketing Leaders, GTM Operations, Sales Leaders" section spells out exactly who it's for”
Demand Generation Manager, B2B SaaS · 501-1000 employeessimulated
Brand alignment
Confident claims sitting next to unanswered objections read as evasive
2 of 15
“that gap between the swagger of the case study headlines and the silence on methodology is what makes we wonder if the substance matches the tone.”
Demand Generation Manager, Enterprise Software · 201-500 employeessimulated See all 2 comments
“Tone's aimed at marketing ops people, not budget owners like me — heavy on jargon, light on proof.”
Director of Demand Generation, Enterprise Software · 51-200 employeessimulated The tone lands with marketing leaders under budget pressure
3 of 15 · what worked
“it skips the 101 explainer and goes straight into "attribution model," "dark funnel," "lift and incrementality," which assumes I already know why last-touch CRM data is garbage. That's…” Show full quote
“it skips the 101 explainer and goes straight into "attribution model," "dark funnel," "lift and incrementality," which assumes I already know why last-touch CRM data is garbage. That's a plus”
Demand Generation Manager, Technology Services · 1001-5000 employeessimulated See all 3 comments
“The tone does feel aimed at someone like me specifically — phrases like "prove what's working, fix what's not" and the explicit "Marketing Leaders / GTM Operations /…” Show full quote
“The tone does feel aimed at someone like me specifically — phrases like "prove what's working, fix what's not" and the explicit "Marketing Leaders / GTM Operations / Sales Leaders" tabs are written by someone who's sat in my budget review and knows the exact fight I'm having”
Head of Demand Generation, Technology Services · 201-500 employeessimulated “they know their buyer is a marketing leader tired of reconciling five reports”
Director of Demand Generation, Technology Services · 501-1000 employeessimulated
05
How this works
Who we simulated (15 personas)
15 AI-simulated personas matched to your target market. Each answered independently, without seeing your goal, the scoring criteria, or each other’s answers. Attribution is role, industry and company size only.
Director of Demand GenerationTechnology Services · 501-1000 employeesEU
Head of Demand GenerationB2B SaaS · 1001-5000 employeesUS
Demand Generation ManagerEnterprise Software · 5000+ employeesEU
Senior Demand Generation ManagerTechnology Services · 51-200 employeesUS
Director of Demand GenerationB2B SaaS · 201-500 employeesEU
Head of Demand GenerationEnterprise Software · 501-1000 employeesUS
Demand Generation ManagerTechnology Services · 1001-5000 employeesEU
Senior Demand Generation ManagerB2B SaaS · 5000+ employeesUS
Director of Demand GenerationEnterprise Software · 51-200 employeesEU
Head of Demand GenerationTechnology Services · 201-500 employeesUS
Demand Generation ManagerB2B SaaS · 501-1000 employeesEU
Senior Demand Generation ManagerEnterprise Software · 1001-5000 employeesUS
Director of Demand GenerationTechnology Services · 5000+ employeesEU
Head of Demand GenerationB2B SaaS · 51-200 employeesUS
Demand Generation ManagerEnterprise Software · 201-500 employeesEU
Methodology
Every answer on this page was written by an AI model role-playing a buyer profile, scored on Wynter’s B2B Message Layers framework. The personas were sampled in code across role, industry, company size and behavioral traits; the model wrote only the answers. Scores arrive through fixed verdict categories and the counts are computed in our own code, so no number here was written by a model.
Score details: the count and the strength
The count is how many personas cleared the bar on each question. A yes can be unhesitating or come with reservations; the scorecard counts both as a yes, and this is the only place the difference is shown. Per layer:
- Clarity: 15 of 15, 1 without hesitation, 14 with reservations
- Relevance: 15 of 15, 1 without hesitation, 14 with reservations
- Value: 10 of 15, all with reservations
- Differentiation: 4 of 15, all with reservations
These answers are AI-simulated and directional. Validate anything you’re betting on with real buyers, your ICPs.
Your next 3 moves
- 1.State what Atlas does that a warehouse plus BI cannot.
- 2.Add lift report specifics beside the incrementality claim.
- 3.Define 'Atlas' and 'Agents' where each term first appears.
See what real buyers say.
A detailed, section-by-section message test report from verified B2B professionals who are actually in-market for what you sell.
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RetentionThis report is kept for 60 days, until 21 Oct 2026, then deleted along with the personas, their answers and everything derived from them. The link stays live for that whole period so it can be shared or revisited, and stops working afterwards.
The email address it was requested from is kept beyond that, because it subscribes you to the newsletter — that was the price of the report. You can unsubscribe in one click from any issue, which stops the email without affecting a report still inside its 60 days. The public report page never shows the requester’s address.
The email address it was requested from is kept beyond that, because it subscribes you to the newsletter — that was the price of the report. You can unsubscribe in one click from any issue, which stops the email without affecting a report still inside its 60 days. The public report page never shows the requester’s address.