Age no bar? Not anymore!
CRMs tend to accumulate a lot of data over some time. That’s why you must think about some of your oldest records first to decide whether they’re still accurate or relevant to your SMB.
An easy way to wade through old data is to look at the engagement levels. If it lacks activity for more than six months, then it’s not the most sought-after lead/prospect record. Save some time and avoid turning this cleaning into a project and involving too many hands. Try making an inventory of old records as a standard procedure, along with automated reminders to help sales teams and others to stay on top of it.
Merge or delete
Cleaning your CRM data isn’t just about removing records. Due to the way it allows for input across several different departments, a possibly bigger issue is duplicity. The existence of data doppelgangers.
It can be a challenge for your business as well, because “duplicate” may only refer to the records about the same customer, but they might be different in terms of accuracy or relevance. A new employee might not check the CRM first before creating a new record about an existing customer, for instance, and this may cause the rise of duplicates.
In certain cases, it might be sensible to merge data than deleting duplicates because they both have valuable information. E.g. the marketing team might have researched a customer that addresses their pain points, while a duplicate record already exists about the particulars of the customer’s buying process that a sales rep had learned first-hand. Merging duplicates can get the best of both worlds from a data perspective.
Design a CRM style process
CRMs are designed to evaluate information based on patterns and commonalities. Details are significant because If every data is unique, then cleaning it becomes more difficult.
This is where a style process can be of use. Create a standard procedure that all information should be keyed into the CRM and ensure that everyone across all teams understands and follows it.
It’s beneficial to pay attention to things like the way designations are abbreviated; whether job titles like “Sales Development Representative” can be shortened to “SDR” and so on. This isn’t about being picky. It’s better to have clarity around the manner the data for CRM is captured rather than cleaning the mess later.
Have a talk with your teams about the notes that get updated in the CRM and assess whether people are entering information that’s truly useful in terms of improving sales or retaining customer loyalty.
Review, clean, repeat!
It will be unrealistic to assume that the CRM will be spotless, especially if it’s used by most employees regularly.
Some SMBs try to get the data cleanliness issue addressed by restricting the number of administrators. This may help in the reduction of errors. But you need to aim for endorsing the policy of treating each piece of data like treasure.
Remember that like your cubicle or home office, cleanliness is not the finish line but something you need to constantly work on. Your CRM might get cleaned up, but as your organization gets busy the dirty data will creep back in. Just repeat the process and you’ll soon observe an upward trajectory of sales. This might become a repetitive cycle too.
A CRM is like a collective work area for the entire organization to come and share information. And in all honesty, a workspace needs quite a bit of care. Emphasize the importance of keeping the data clean and avoiding its death in the CRM. If you are curious to know how data can be managed easily in a CRM then let’s talk.