Business data accountability Stop debating your data. Start making evidence-based decisions.
Gohvio is the trust layer between your CRM and your decisions. It checks your data against your own guardrails and shows what is broken, what it does to pipeline and forecast, and the rows behind it.
Revenue doesn't end at closed-won. Neither does trust.
Click any part of the bow tie. Demand flows in from the left. Expansion and referrals flow back from the right.
Showing: Quality of demand. Click any part of the bow tie to explore it.
Quality of demand
Is Marketing doing its job?
Whether Marketing is generating quality demand, from the right channels, that justifies the money being spent. Quantity is easy. Quality is the question.
The share of new leads that meet your MQL criteria, by channel. Lead volume counts people. Lead-to-MQL rate counts demand.
Not: LinkedIn generated 2,000 leads.
Which channels turn leads into MQLs, and which just add volume?
| Channel | Leads | MQLs | Lead → MQL |
|---|---|---|---|
| Paid social | 2,000 | 60 | 3% |
| Organic search | 900 | 135 | 15% |
| Webinars | 400 | 80 | 20% |
The biggest channel by leads is the smallest by MQLs.
- Leads with no original source, so no channel gets the credit
- MQLs that don’t meet your own MQL criteria
- The same person counted twice as two leads
Are we generating demand, or just generating activity?
Clean data isn't the same as trusted data.
Is each record right on its own?
The field is filled in. The email is valid. The date is a date. The amount is a number. No exact duplicates. Necessary, and not enough.
Can the number built from those records be believed?
One agreed definition, applied the same way to every record, traceable back to the rows behind it. So Marketing, Sales and Finance reach the same answer.
Bad data doesn't announce itself. It shows up as a confident number in a board deck.
Every morning you trust a paper filter you never think about. It keeps the grounds out, so what reaches your cup is just coffee. Gohvio does that for revenue data: the layer your numbers pass through first, so what reaches the forecast, the board deck and the budget is the part you can trust.
| Data quality asks | Data trust asks |
|---|---|
| Is the field filled in? | Does the number built on it mean what we say it means? |
| “17 records are stale.” | “$4.2M of pipeline breaks your stage rules.” |
| Generic rules for every company | Your own definitions, checked on every record |
| A score you take on faith | Every finding points to records you can open and check |
| One team's report | One definition Marketing, Sales and Finance share |
Every organization wants data it can trust. Gohvio is the layer it passes through first.
Stop debating your data.
When two teams bring two different numbers, the meeting becomes a debate about whose number is right. Gohvio checks the data against your own guardrails, so the meeting can be about what to do. Every finding points to the rows behind it.
What is data quality, and how does Gohvio check it?
Data quality is whether the records in your CRM are complete, consistent and fit for the question you are asking. Gohvio checks your CRM data against your own guardrails and shows each finding with the rows behind it. A check to run today: pick one field your forecast depends on and ask who defined it.
What is data integrity, and why does it matter for the forecast?
Data integrity is whether a figure still agrees with the records it came from and the rule that defines it. Gohvio's Dashboard says what is broken, against which guardrail, and what it does to pipeline and forecast, with the rows behind it.
What is business data accountability?
Business data accountability means every definition your numbers rely on has a person who approved it and a record of who changed it. In Gohvio you upload your own guardrails as a document, a person approves them, and each change is recorded with who changed it and when. Workspace admins can see that Version history. Different teams may mean different things. Nobody knowing is the problem.
What is data reconciliation, and can Gohvio do it across files?
Data reconciliation is checking that the same record agrees across sources, and showing where it does not. Gohvio lets you upload more than one file, matches records across the files on a shared ID, email or name and, where a field holds amounts, shows the dollar gap.
How does this help with board reporting?
A board number only holds if you can answer "where does that come from?" Gohvio shows the rows behind each finding so you can check the data under a figure before anyone presents it. Gohvio does not produce the board pack. It checks the data beneath it.
A trust tool has to be trustworthy first.
So here is exactly how Gohvio treats your data and your answers. Encrypted in transit. Never sold.
Gohvio is a revenue data trust platform. It checks your CRM and marketing data against the definitions your team agreed on (MQL, SQL, pipeline stages, bookings, ARR) and points to the records that break them, so Marketing, Sales and Finance can defend the same number.
Confidence that a revenue number means what everyone thinks it means. A trusted number is built on one agreed definition and can be traced back to the records behind it.
Data quality asks whether each record is right on its own: fields filled in, valid emails, real dates, no exact duplicates. Data trust asks whether the number built from those records can be believed: one agreed definition, applied the same way to every record, traceable to the rows behind it.
A funnel that keeps going after the sale. The left side narrows from demand to a won customer. The right side widens as that customer adopts, renews and expands, and loops back as referrals that create new demand.
Ending ARR = Starting ARR + New + Expansion − Contraction − Churn. For example, $1,000,000 + $150,000 + $80,000 − $20,000 − $60,000 = $1,150,000. Bookings are not ARR: a three-year $300K contract is $300K of bookings and about $100K of ARR.
Cleaning tools fix fields. Gohvio tests whether the numbers built from those fields can be trusted, points to the records that break your rules, and shows what they are worth in pipeline and revenue.
No. Gohvio is read-only today: it reads your CRM and does not write to it, and it never changes your original file. Salesforce has no read-only API permission, so the permission you grant there would technically allow changes; Gohvio's code only reads. If you want Salesforce itself to enforce read-only, connect with a Salesforce user whose profile has read-only access.
Your uploaded file is deleted as soon as it is read. The data from it is cleared automatically after 24 hours without activity. Rules you save are kept until you delete them. Everything is encrypted in transit (HTTPS), and we never sell your data.
From a connected CRM, Lumi sees counts and summaries, not the contents of your records. From a file you upload, Lumi sees up to 50 rows, including names and contact details. Columns holding card, bank or government ID numbers, passwords, dates of birth or sensitive categories such as health are left out. We detect these by column name and pattern, not with a guarantee, so something typed into a free-text column such as Notes can still reach the model. With more than one file loaded, Lumi also sees Gohvio's comparison of them: file, column and guardrail names, record counts and dollar totals, not the other files' rows. We save the questions you ask Lumi, up to 1,000 characters, with email addresses, phone and card numbers and street addresses that can be detected removed first; a name typed into a sentence stays. After 90 days we remove your email address, and on a team workspace your job title too; the question stays linked to your company workspace. The question text itself is kept. The Trust Center has the details. Rules drafted from a policy document you import can differ from one import to the next, so review them before you save.
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Stop arguing about the number. Trust it.
Connect HubSpot or Salesforce, or upload an export, and see which records break your own definitions, from first lead to renewal.
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