As organization infrastructure and its processes get more automated, data quality becomes the differentiating factor between a successful business and a failure. The accuracy and timeliness of CRM data become pivotal for the organization, be it for creating customer personas or optimizing the outbound sales strategy – the success of your business all rides on data and its quality.
It is no surprise that enterprises today are striving to gain the most out of the data in their CRM systems. But, without continuous and real-time maintenance of data, it can decay and stagnate, and eventually become 'bad data' which can be a threat to your organization. The bad data in your CRM doesn't just refer to 'wrong data'. It also involves missing, incompatible data formats, out-of-date, and incomplete data.
If bad data isn't detected and fixed as soon as possible, it can cause severe problems in the enterprise, leading to a waste of time and effort. Bad data can cause your innovative ideas to vanish, high bounce rates, squandered phone calls, and erroneous marketing campaigns.
CRM is a valuable asset in the organization that helps your marketing team to run campaigns effectively and manages your clients efficiently. Therefore, having bad data can be highly detrimental to your CRM and your business. Because low-quality data comes with serious drawbacks such as paying extra for CRM storage containing dead, duplicated, or incorrectly formatted data, poor business decisions, and many hidden risks that initially, you may not even see.
This blog will uncover how bad data affects businesses and why we should enrich it.
The Consequence of Bad Data
The more complex the data is, the more strenuous it becomes to keep all data sets organized and updated for any enterprise. For instance, the consequence of bad data can be observed in the sales team if they have poor prospect lists, which would affect the business revenue. Eventually, this leads to customer losses due to ineffective marketing campaigns. Therefore, if organizations do not sort obsolete data and continue to neglect their data enrichment process, it will highly impact their business growth.
According to Gartner research, “the average financial impact of poor data quality on enterprises costs them anywhere between $10 to $14 million annually. At the macro level, IBM also discovered that bad data is estimated to cost the US more than $3 trillion per year. Simply put, bad data is detrimental to business.
More notably, the research firm found that 60% of businesses don’t know how much bad data actually costs them because they don’t measure the impact. This indicates that a majority of businesses lack a fundamental understanding of how the quality of the data they have running through their systems affects their business outcomes.
Why Should We Enrich Bad Data in CRM?
An erroneous CRM with outdated data has severe harmful effects on an organization such as a meltdown in revenues, productivity, and business growth. It ultimately creates a serious impediment to B2B lead generation as well. There are various other significant risks associated with bad data which entail us to clean and enrich the CRM database regularly which include-
1. Damage to brand reputation
Brand reputation holds a significant value in a successful business but low-quality data can highly impact the customer base. Bad data entail wrong names, undelivered messages, contact or gender mix-ups, duplicate communications, and more. So, if your CRM data contains inaccuracies, you might be basing your buyer personas on false information and leaving them with a negative impression of your brand. As a result, it can have disastrous consequences for the entire marketing team, such as deterring prospects and poor brand reputation.
2. Missed opportunities
Time is an invaluable resource in the marketing team and they completely rely on customer data for their marketing campaigns. So, having bad data can cause missed opportunities or dead-end leads and it will slow down the sales pipeline in turn dismaying the sales team. Optimized CRM data can help you save time to engage with the leads who are more likely to become your potential customers. It also leads to incorrect forecasting and poor decision-making negatively impacting production and profitability.
3. Increased churn rate
Bad data not only deter new customers but can affect existing customers as well with poor content approaches and ineffective emails. There are many facets to email marketing but if you're dealing with low-quality CRM data then it can lead to an increased churn rate. The churn rate refers to the percentage of email subscribers who have dropped your services and no longer wish to receive your organization’s emails. Therefore, mismanaging email churns can have negative impacts on your customer base.
4. Increased Costs
Poor CRM strategy can lead to not only revenue losses but increased costs as well due to the additional maintenance of bad data. The organization doesn't just lose new sales but their workplace environment also gets affected leading to poor employee engagement. It must also decide whether to lower expenditures to compensate for a loss of income or enhance its customer service through extra marketing efforts to attract new clients.
Eliminate the Risk of Bad Data by Enriching Your CRM
The cost of Bad Data may be high, but it can easily be alleviated/remediated with continuous data maintenance and better CRM management. Being data-driven is about finding the key component that can help your organization acquire new prospects and retain existing customers. Also, it's about making your marketing and sales teams operate efficiently by providing them with accurate data.
Therefore, a planned approach to CRM data reduces difficulties for enterprises while ensuring end-users acquire the data they need to retain crucial prospects and increase revenue. If you need help in understanding why your organization needs better CRM then you may book a free appointment with us. We focus on building highly customized CRM software solutions and help organizations embed best practices.