Tips for improving your sales data

A five-step process to improve your CRM system

Tips for improving your sales data

A five-step process to improve your CRM system

When it comes to CRM systems, one of the biggest barriers to long-term adoption is the difficulty associated with maintaining data quality. The accuracy and the usefulness of the data you harvest rests upon ensuring account and contact data remain unique, up to date – that you only capture data that adds real value.

Your sales team’s frustrations with the quality of data in your CRM can rapidly decrease their overall confidence in the system and therefore their ability to do their jobs. An independent CRM Health Check can iron out all of these problems and restore the profitability of your systems.

In this post, I’ll take you through a five-step process to ensure that you get the best out of your CRM system.

1. Set targets

Make sure you share an understanding of what good quality data actually looks like – what’s important, but also what can be comfortably ignored. It’s likely that you’re interested in particular sets of data, perhaps existing customers or leads. You need to decide exactly which fields are most important to your business and make sure that your business leaders buy into and enforce these measures.

2. Assess Users’ concerns

Are they accurate? Are they significant? Listen, create a hypothesis and then build reports that measure against the targets you have specified to assess whether or not there is actually an issue.

3. Improve

First explore why you have a problem. Perhaps, for instance, you are capturing too many attributes, or maybe you are capturing them at the wrong stage of the process. Seek business process improvements first: training, or a simple change – this may include monitoring the quality of your data, or preventing the creation of a new account. Then, look to the simple technical fixes you can implement. You should only aim for the big issues that require significant investment and/or big changes to systems or software once these smaller tweaks are in place. Having optimised your data, you should be able to see clearly where the real problems lie.

4. Communicate

Through this process, be sure to let your users know exactly what is happening and how you intend to fix the issues. Hold yourself accountable by publishing the measures and targets on a month-by-month or real time basis. Engage your audience, ensure they take responsibility for their own data and don’t let them claim it’s not their problem.

5. Monitor and continue improving

The process doesn’t simply end once your immediate problems are resolved. Data isn’t a static problem, it evolves with the business, as does what you need from your data. So, it’s crucial that there’s a process in place that enables you to continue to not only glean relevant and useful data as your business develops but also monitor the quality of the existing data.

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