We have had our customer database transferred from another system and it would be handy to remove duplicate customers, or at least merge them.

We would like to put our vote in for the ability to remove customers from the system in bulk. We are needing to remove aged customers now and the current system is not productive.

Merging customer details into a single reference point, but retaining their sales data would be very useful. We have customers who have two records, they bought from us initially through ebay or amazon and have subsequently come over to us direct (maybe it was the great service?).

It would be useful to be able to merge their sales transaction into a single account and easier to deal with any issues in the future, warranty etc.

You look a bit daft when you tell them they didn't buy it from you, because you looked up their postcode in the correct format with a space, then it turns out they bought it via ebay and their postcode has no space.

Not all of the team here are as experienced with the subtle nuances of the system, where a partial search shows multiple records for a customer.

This should be merged with https://www.citruslime.com/feedback/point-of-sale/p/duplicate-customer-account-warning, https://www.citruslime.com/feedback/point-of-sale/p/search-for-customers-using-mobile-number, https://www.citruslime.com/feedback/point-of-sale/p/gdpr-compliance, https://www.citruslime.com/feedback/citrus-lime-backoffice/p/customer-account-no-sort-order-wrong,

as all of these relate to identifying and cleaning up 'dirty' data, including correctly identifying duplicate records and being able to merge them (including any transaction history connected to them).

The effectiveness of any database-driven POS, e-Commerce marketing system, etc. is only as good as the accuracy of the data stored within it. Having multiple entries for the same customer because of minor differences (e.g. old mobile number, email or address change, etc.) reduces the impact and value of any marketing campaign, analysis, trend matching, etc. However, CL still does not have effective tools with which to manage the raw data itself, identify potential duplicates and compare 2 or more potential duplicates in order to select the correct data to keep and merge, yet identify clearly when two similar records are in fact separate individuals. As an example of a real-life non-duplicate, my brother-in-law and father-in-law share the same first name and surname and live at the same address, with a shared home phone. However, they have different dates of birth, email and mobile numbers.

Common duplicates include where the postcode, mobile or landline numbers and even email addresses are the same, but some entered with spaces and some without. In these instances, the database needs to have formatting rules that correctly insert spaces where required (e.g. 02033268505 should be 020 3326 8505; 07973166946 should be 07973 166946 and post codes should be WS11 1GR, not WS111GR).

Hi all,

We currently have a feature planned that will involve the option to remove all details from a customer and marking them as inactive, which I believe suits what you are looking for.

As such, I'm going to merge this post into that one.

The feature has an estimated development date of early next year.

Many Thanks,

Stacey

agreed

Hi,

Thank you for your interest in this feature. We have added it to our development schedule, with the aim to implement it early next year.

The development ticket has been linked to this request.

Many Thanks

Stacey