Top mistakes businesses are making with CRM data, how to avoid them

The past two years have been challenging for businesses everywhere, so it’s not surprising to learn that adherence to good data practices may have slipped somewhat during this period.

In fact, new research from Validity found that 74% of Aussie CRM administrators felt that data decay increased as a result of COVID-19, while 71% said that a rise in movement of employees between jobs since March 2020 has led to an all-time low in data quality.

Why is data decay a concerning issue?

While it’s understandable that many businesses’ processes fell by the wayside as they fought to survive the first two years of the pandemic, data decay is a very concerning issue given the significant flow-on effects it has on a business’ operations and bottom line — especially now when many are trying to make up for lost earnings over the last 24 months.

Validity’s research found that despite concerns about data quality, reliance on data remains high in Australia. 93% agree that most decision makers rely on CRM data to make key decisions, however 43% of those say that data requisition to drive decisions is inaccurate, and 29% say that the CRM data requested to drive decisions often does not exist at all.

Some of the most common oversights contributing to poor quality and unreliable data are housing data in an inaccurate location in the company’s CRM (40%) and storing data with inaccurate names (33%) and titles (30%).  A common factor that contributes to poor data practices is a lack of clarity around who is responsible for managing data in a CRM system.

How can you find and remediate bad data?

Only 16% of respondents said managing data in their CRM system is the full-time responsibility of department. While finding and remediating your firm’s bad data is a big task, it can be done! Here are three tips to get your house in order and implement strong data practices, setting you on your way to becoming an efficient, ethical and innovative business.

Understand where your data is coming from

Within firms, there is often confusion between teams regarding who is responsible for the quality of data as it is input into the CRM system. Validity’s research found that 11% of respondents said that who the owning department should be is debated within their firm.

Most commonly it’s the sales, marketing and customer teams that input the majority of customer and prospect data, while the CRM administrator’s role is to ensure ongoing data quality. The administrator’s job can be made near impossible though if the various teams responsible for inputting data aren’t doing this consistently or thoroughly.

Add to this the fact that every month three percent of data decays globally and B2B data decays at an astonishing rate of 70.3 percent per year according to Gartner.

To ensure your organisation’s data remains as up to date as possible, you must first identify where your data is coming from. Which departments are entering data into the system? Where is their data coming from – other databases, direct from customers?

How regularly is this data being updated? Is it possible to automatically receive updates? How is the data being entered and does this format potentially differ from how other sources are inputting it? Legally, are you able to store this data and if so, for how long?

Answering these questions will help identify weak points in the current system and to develop a plan to overhaul your data processes. Automating as much of your data standardisation and hygiene processes is key to ensuring high-quality data at scale across your entire firm.

Standardise how data is stored before importing it to your CRM system

Once you know where your data is coming from, you can start the clean-up phase.

It’s a lot more costly to remediate data after it’s been input into your CRM, so focus on cleaning data before it enters your system. Fix poor data at the source – create guidelines outlining what data the organisation needs and uses, and any data that is unhelpful.

To ensure these guidelines are followed, speak with a key stakeholder from each business function about their data needs, how they store data, and how they would ideally use it.

Define the data points within your CRM system and document potential sources for each of these fields. The admin should create clear, universal standards for teams outlining the format of data the business needs and how this should be updated on an ongoing basis.

Try to keep data input processes as efficient as possible. Colleagues are more likely to cut corners and make mistakes if the standard entry process is too laborious or time consuming.

Make changes to your data systems cautiously and as required

When updating processes, you could get caught up in the improvements, but it’s crucial that you document the customisations you’re making as you go for future reference. Equally vital is conducting regular audits to determine whether your data needs have changed over time.

When all users can easily access and edit accurate data, their jobs are made simple and they are more likely to trust the CRM as a result, rather than feeling they need a range of tools, services, and add-ons that will only slow things down while they perform their duties.

It should also be noted that the more system changes and customisations you make, the more time-consuming storing and maintaining data can become. Therefore, start with the minimum viable product needed and once you know with confidence that customisations are valuable and being used, you can expand the complexity of your data model from there.

As touched on, ensuring that all system changes are clearly documented and communicated to each business function for ongoing use and buy-in is critical, as are regular audits of your data organisation-wide. Typically, the more complex a system is, the more frustrating using it will be for employees, leading them to stop trusting and prioritising the data.

In an ideal world you’d flick a switch and your data would be clean, organised and accessible, sadly however this isn’t the case. The time required to remediate bad data and well and truly worth it though, as a business’ data is its most valuable asset, impacting everything from reporting, to decision making, sales productivity, marketing ROI and customer retention.

By making data’s value clear to all personnel and departments as well as investing in its ongoing maintenance, you will stand to reap the significant benefits.


William Zhang is the Director of Sales APAC, Validity Inc.