CLEAN CRM

Clean up your CRM data

We identify outdated data, potential duplicates and companies without proper identification, giving you a CRM that’s easier to work with and easier to trust.

Clean CRM FOR:

Tell us about your CRM data
See how Clean CRM works

Good CRM depends on good data

CRM is only as good as the data people work with.

When outdated company information, duplicates and incomplete data start to pile up, it becomes harder to find the right information, trust what’s in the system and use CRM effectively.

With a cleaner data foundation, users get a clearer overview, less noise in their daily work and greater confidence in the information they rely on to make decisions. At the same time, CRM becomes a stronger tool for the entire business.

Less noise. Fewer duplicates. More trust in your CRM.

01

Make it easier to find what matters
Outdated and irrelevant data creates noise. With a more relevant data foundation, users can more easily find the companies and information they actually need to work with.

02

Create a clearer customer view
Duplicates can spread activities, contacts and history across multiple versions of the same company. Fewer duplicates give you a more complete and consistent view of the customer.

03

Build trust in CRM
When users know the data is relevant and reliable, CRM becomes a stronger tool for the entire organisation.

What needs cleaning up?

Clean CRM can be used for three different types of CRM data clean-up. You choose the one — or the combination — that best fits your needs.

Outdated data

Find data that no longer belongs in CRM

We analyse your CRM and identify company records (accounts) and data that may be outdated or irrelevant based on agreed criteria.

You review the results first. Once approved, we flag the identified data in CRM, so you can decide what should be removed and carry out the deletion yourselves.

Result: A more relevant CRM with less noise.

Duplicates

Find companies that may exist more than once

We analyse your CRM data for potential duplicates and identify companies that may represent the same organisation.

Potential duplicates are flagged directly in CRM, so your CRM administrator can review and merge them based on the available information.

Result: Fewer duplicates and a more complete customer view.

Data match

Give each company a unique Risika ID

We match the companies in your CRM against Risika’s company data and identify those where we can find the correct match with sufficient confidence.

We can then add the unique Risika ID to CRM, creating a stronger foundation for future updates and better data quality.

Result: Correct company identification and a better foundation for keeping company data up to date.

How Clean CRM works

You stay in control of your CRM data.
We identify and prepare the clean-up. You review the results and approve them before we make any changes in CRM.

01

We analyse your CRM

We run the relevant CRM data through our Clean CRM engine and identify the records that match the agreed criteria.

02

You review the results

You receive the analysis results, so you can see what we’ve found before any changes are made in CRM.

03

You choose what we move forward with

You review the results and decide which findings to move forward with. We never make changes to your CRM data without your approval.

04

We flag or enrich the data in CRM

Depending on the type of clean-up, we flag data for deletion or merging — or add the identified Risika ID.

If you use SuperOffice, we can also help with the actual merging.

Clean up today. Keep your data in order going forward.

Clean CRM

Clean up existing data

A cleaner CRM

CRM Connectors

Prevent new data issues

Clean CRM helps you get your existing CRM data in order. But good data quality is also about preventing the same problems from coming back.

With Siteshop’s CRM Connectors, data can be created, validated and updated automatically — reducing the risk of duplicates, errors and outdated information finding their way back into CRM.

Explore our CRM Connectors here ->

Pricing

Outdated data

From

EUR 2,500

Identification and flagging of outdated company data in CRM.

  • Start up meeting
  • Analysis and report
  • Alignment meeting
  • Collection and flagging of outdated data
  • Closing meeting


Larger data volumes may require additional hours of work.

Get started ->

Duplicates

From

EUR 3,720

Identification and flagging of potential duplicate company records in CRM.

  • Start up meeting
  • Duplicate analysis and report
  • Alignment meeting
  • Flagging potential duplicates
  • Closing meeting

If you use SuperOffice with Dev Tools, duplicate merging can be added from EUR 1,500.


Larger data volumes may require additional hours of work.

Get started ->

Data match Risika ID

From

EUR 1,500

Data matching of your companies against the Risika database.

  • Start up meeting
  • Data match analysis
  • Alignment meeting
  • Adding Risika IDs to company records
  • Closing meeting

Requires a Risika data access (API) agreement.


Larger data volumes and poor data quality may require additional hours of work.

Get started ->>

What does Clean CRM require from you?

We handle the technical analysis. You contribute your knowledge of the CRM data and stay in control of what should be cleaned up.

Your main role is to help define the criteria for the clean-up, then review and approve the results.

Siteshop handles the analysis and prepares the identified data for further processing in CRM.

We receive temporary API access to your CRM, which you provide. This allows us to analyse your data and, once approved, flag or update the relevant records.

We’ll help you get the necessary access in place before we get started.

Yes, as a general rule. We identify and flag the relevant data in CRM, so you can carry out the clean-up yourselves.

For data matching, we can add the identified Risika IDs directly to CRM. If you use SuperOffice, we can also help with merging duplicates.

Get started with Clean CRM

Tell us a little about your CRM and the challenges you’re experiencing with your data. Then we’ll talk through the type of clean-up that makes sense for you — and how to get started.