Question 1

How do I know if my data is bad enough to need this?

Accepted Answer

You probably don't, and that's exactly why the Audit is free.

Most businesses have a sense that their data isn't quite right — bounced emails, the occasional duplicate, contacts they're not sure are still there. What they don't have is a measurement.

The Audit takes 100 of your real records and gives you a one-page scorecard within five working days. If your data turns out to be in good shape, we'll tell you and you can walk away. If it isn't, the scorecard becomes the basis for deciding what to do next.

There's no commitment beyond sending us the records.

Question 2

What if our data is in three different systems?

Accepted Answer

That's common, and it's the question that usually matters more than people realise.

Whether the systems should be combined into one, or cleansed separately and kept distinct, is a strategic decision — not a technical one. Combining a CRM, a spreadsheet, and a legacy management system into a single master database is a different engineering problem to cleansing each one independently and reconciling them.

We handle multi-system engagements as bespoke work, scoped during the Audit. The single-system Cleanse is the standard offering; multi-system is quoted separately based on what you actually need.

If you're not sure which you need, that's also a conversation to have during the Audit.

Question 3

How do we get our data to you, and how do we get it back?

Accepted Answer

You export your data to a CSV. We process it. We return it with a detailed import guide for your specific system.

The import itself is something you handle — either yourself, your internal IT, or whoever normally looks after your CRM. We don't push data back into your live systems; your data stays in your control throughout.

If you'd rather have the import handled for you, we can arrange this through a specialist partner — quoted separately based on your system and the volume of records.

We provide a signed Data Processing Agreement before any data leaves your system, and your data is processed on UK servers and deleted within 30 days of the engagement closing.

Question 4

How long does a Cleanse take, really?

Accepted Answer

The honest answer is: from three weeks, depending on what we find.

A business with a single CRM, reasonably well-maintained, mid-thousands of records, and no unusual complications will be at the lower end of that range. A business with multiple systems, decade-old data, or unusual structural issues (orphan records, deeply fragmented company entities, retention questions) will take longer.

The Audit gives us enough information to commit to a specific timeline before you commit to the Cleanse. You won't be quoted three weeks and then told eight.

Question 5

What happens if you find something we didn't expect — like records we've forgotten about, or worse?

Accepted Answer

We tell you. Calmly, in context, with a recommendation.

Most "didn't expect" findings fall into a few categories: contacts who should have been removed years ago under retention policy, records that look like duplicates but turn out to be parent-subsidiary relationships you'd forgotten about, suppression-list breaches, or dormant clients who never quite left.

None of these are unusual, and none of them are reasons for concern — they're the normal state of databases that have been running for more than a few years. Our job is to surface them and recommend what to do, not to judge how they got there.

If we find something genuinely concerning — material GDPR exposure, for instance — we tell you confidentially and immediately, before it appears in the formal summary at the end of the engagement.

Question 6

What if we're not happy with the result?

Accepted Answer

The Cleanse is structured to make this unlikely.

Before any change goes near your live data, you see what we're proposing — every merge, every retirement, every standardisation, every judgement call. Nothing gets handed back to you that you haven't already approved in principle.

If the proposed changes don't match your expectations, we adjust them before the work continues. If something genuinely doesn't work after delivery, we'll fix it. We don't refund time already spent, but we also don't deliver work that hasn't been signed off.

The Audit exists partly to prevent this situation entirely. By the time you commit to a Cleanse, you've seen what we do and decided it fits.

Question 7

What happens to our data after the engagement ends?

Accepted Answer

For a Cleanse: your data is deleted from our systems within 30 days of delivery. We retain a record of the engagement (what was done, when, for whom) for our own audit and contractual purposes, but the data itself is removed.

For an Engine subscription: your data remains in our processing environment for the duration of the subscription, since the Engine works on an ongoing basis. When the subscription ends, the same 30-day deletion policy applies.

We don't use client data for anything other than the engagement it was provided for. Your data is yours, and once we're done with it, it's gone.

What we do	What you'd see	Why it matters
Profile your data first	A diagnostic showing what's actually in your database — duplicate rates, decay patterns, field-completeness gaps, dormant records. Done before we change anything.	Without it, every cleansing decision is a guess. Cleansing without profiling is how good records get deleted and bad ones get kept.
Find and merge duplicates	"Hartwell & Co Ltd" and "Hartwell and Co" recognised as the same company. The richer record kept, the thinner one merged in, no data lost.	Duplicates inflate your CRM, distort your reporting, and embarrass you when two staff contact the same client about the same thing in the same week.
Verify contacts are still real	Email addresses checked for valid format. Phone numbers checked for valid format. Companies checked against Companies House for active status.	A database that's 30% wrong is worse than no database at all. You make decisions on what you can see — bad data hides behind looking fine.
Retire dead records properly	Dissolved companies, bounced emails, contacts who've left — flagged, archived, removed from active lists. Not deleted; preserved with a reason.	So your team stops wasting time on records that were never going to convert. And so you keep an audit trail of what was removed and why.
Standardise the messy fields	Phone numbers in one format. Company names without trailing "Ltd" inconsistencies. Addresses normalised. Date formats standardised.	This is the unglamorous work that decides whether your AI tools, automations, and reports actually work — or quietly fail in ways no one notices.
Escalate the genuine judgement calls	The records where automated rules can't decide — flagged for human review with context. You see what we're proposing before we change anything live.	The records that need a judgement call are usually the valuable ones. Automating those decisions is how clean databases lose their best leads.
Untangle fragmented company records	"Hartwell Holdings" and "Hartwell & Co Ltd" identified as parent and subsidiary. Companies that changed name three years ago matched to their current entity. Records that look like duplicates but aren't, kept distinct.	The records that look fragmented are often the ones with the most history — long-standing clients, recent acquisitions, rebrands. Treating them as duplicates loses the relationship; treating them as separate loses the context.
Normalise addresses against UK standards	Addresses checked against the Royal Mail Postcode Address File. Inconsistent formatting standardised. Postcodes verified, missing ones inferred where possible.	Mismatched addresses fail more deliveries, more credit checks, and more verification flows than any other single field. UK address data has standards — most cleansing services don't use them.
Parse names properly	"Mr John Smith" separated into salutation, first name, last name. "Smith, John" recognised and reordered. Names with prefixes, suffixes, and double-barrels handled correctly.	So your mail merges stop saying "Dear Mr John Smith" or worse. The smallest data quality issue, and the most visible to your clients when it goes wrong.
Distinguish dormant from dead	Records that haven't been touched in three years aren't automatically retired — they're checked. Some are still valid; some are clients who'll come back; some are genuinely finished.	Aggressive cleansing kills the records you'd most regret losing. The clients who quietly go quiet for two years and then come back with a year-end project are exactly the ones you can't afford to retire.
Cross-check fields against each other	Does the postcode match the address? Does the email domain match the company? Does the Companies House registration match the trading name on file?	Records can be wrong even when every individual field looks right. Cross-checking is how you catch the records that passed the obvious tests but still aren't true.
Handle GDPR retention and suppression	Subject access requests answerable from a complete audit trail of every change we've made. Suppression flags carried correctly through every cleanse so opted-out contacts stay opted out. Retention dates surfaced so you can act on records reaching their policy limits.	When a subject access request lands, the question is always "what data do you hold and what have you done with it?" — a clean audit trail is the answer. Carrying suppression and retention markers correctly through cleansing is where most services lose them; we don't.
Show you everything we did	A summary report at the end of every Cleanse: what was found, what was changed, what was retired, what needed your input. For Engine clients, the same view delivered monthly.	Cleansing without visibility is just trust. You should be able to point to any record and see what happened to it and why — both for your own confidence and for any future audit.
Keep an audit trail of every decision	Every change recorded. Every judgement call logged with its reasoning. Every retired record preserved with its reason for retirement.	So if a question arises six months later — about a client who claims they shouldn't have been removed, or a record that's now needed — you have an answer, not a guess.

Pricing.

You're not buying records cleaned. You're buying a database your business can rely on.

Three ways in.

Acennan Audit.

Acennan Cleanse.

Acennan Engine.

What you're actually paying for.

Frequently asked questions.