Over the years, data has increasingly been regarded as an organization’s most vital asset. It’s central to everything you use Salesforce for. It’s the engine that powers your customer marketing and sales programs. It’s a resource relied on to understand customer motivations and make critical business decisions. And an organization’s ability to protect it has become integral to its reputation and success.
But for data to do the important job we all ask of it on a daily basis, it must be up-to-date, accurate, and complete. And it must be routinely managed to keep it that way.
What is Routine Data Management?
According to Businessdictionary.com, data management is the administrative process by which data is acquired, validated, stored, protected, and processed, and by which its accessibility, reliability, and timeliness is ensured to satisfy the needs of the data users.
Routine data management is about implementing data quality processes on a regular basis to achieve and maintain high quality data, including the data in your Customer Relationship Management (CRM) system.
This proactive approach to data quality has become increasingly important for organizations to not only implement, but enforce as part of the workplace culture.
Why Such a Focus on Routine Salesforce Data Management?
The sheer quantity of data businesses produce and acquire is constantly growing, as are the number and variety of channels through which data flows into a company’s databases. The more data an organization holds, the bigger the challenge to store and use it efficiently, effectively, and safely.
Without routine Salesforce data management, organizations risk making ill-informed decisions based on incorrect assumptions and misleading information. And data that can’t be trusted inevitably leads to lost sales opportunities and revenue (IBM estimates the yearly cost of poor data quality in the U.S. alone to be $3.1 trillion), as well as unhappy employees and customers.
Salesforce databases can be particularly prone to errors, with multiple users and points of data entry or capture, as well as a high reliance on customers inputting data correctly.
Fixing these errors can be costly. According to the 1-10-100 quality principle, the relative cost of fixing a problem increases exponentially over time. If the cost of preventing bad data from entering a CRM system is $1, then the cost of correcting existing problems is $10, and the cost of fixing a problem after it causes a failure, either within an organization or with a customer, is in the neighborhood of $100.
This makes ensuring data quality a high priority for CRM professionals. It is an essential element in the organization’s ability to achieve its strategic goals, while reducing costs.
Effects of Bad Data Management
Poor data management causes undesirable interruptions in the normal flow of business activities. It can result in:
Poor Business Decisions
Bad data produces misleading CRM reports and dashboards that sabotage the best efforts of decision-makers to guide the enterprise. But organizations that can turn to trusted data assets to fuel their business strategies can remain a step ahead of the competition.
In fact, according to the 2018 Global Data Management Benchmark Report from Experian, “Getting better insight for decision-making is a key source of competitive advantage.”
In some markets, “organizations may not have the sophisticated capabilities—or clarity around their data assets—to take full advantage of available data resources.” But this is something they’ll need to strive for to remain competitive. As the authors of the report stated, “As more organizations rely on their data for strategic decision-making, their ability to derive actionable insights will be fundamental to their success.”
According to the Experian report, “U.S. organizations believe 33% of their customer and prospect data is inaccurate in some way.” Sales stats derived from bad data can be overly optimistic or pessimistic, causing frustration in the sales team.
Poor Customer Service
The Experian report also stated, “From a global perspective, improving the customer experience is the most mentioned business priority for the coming year.” But when customer service representatives rely on incomplete or incorrect information, they’re unable to deliver a top-notch experience to customers.
Wasted Resources (Time and Money)
When customer data is inaccurate, organizations launch inefficient direct mail/email campaigns, produce poorly targeted marketing materials, and generally underperform in sales and marketing activities.
In an example from a marketing perspective, a company specializing in automotive data and marketing solutions mailed marketing packages at a cost of $20 per package to 4,000 car dealers across North America. Because of bad data (bad addresses, duplicates, and pricing errors), they wasted 25% of the total spend ($80,000) – incurring a loss of $20,000 on a single campaign.
When something like this happens, it’s not just the loss of campaign dollars. It’s also the loss of opportunities. Imagine the potential sales revenue that could have been generated if those 1,000 packages had reached the intended target audience.
In an example from a sales perspective, when data is inaccurate, it can lead to sales teams wasting time working on non-selling related tasks (such as having to update their territories), calling the wrong leads, or calling prospects that are, in fact, existing customers.
The Experian report also found, “When it comes to shaping a data strategy, a majority of organizations (57%) say that data security is the biggest consideration for them.” Security of data is a key threat to any business. Effective routine data management helps in ensuring that vital data is not just useful and correct, but remains protected inside the organization through data governance and restricted access.
Poor routine Salesforce data management causes sales teams to lose trust in the CRM system and work around it. It can also lead to clashes with colleagues and management.
According to a report from Validity, when CRM data quality is poor, adoption rates plummet, sales teams have significantly more overhead in the selling cycle, and conflicts can arise when colleagues nurture the same opportunity or customer without realizing it. In addition, sales managers may become frustrated as they end up dealing with concerns about account ownership and pipelines rather than expediting the sales process.
Routine, but Essential Work
No company is immune to bad data. But they are all responsible for what they do about it. Since poor data quality is a significant root cause of customer relationship problems, poor business decision-making, and lost opportunities, data administrators must be vigilant and proactive about keeping their databases clean.
Even if, to some, it sounds like mundane, perhaps even boring work, Salesforce data management is inextricably linked to the performance and well-being of an organization.
Having the Right Tools is Key
The good news is you can achieve and maintain high quality data by implementing the correct systems and processes, while receiving a little help from the right technology and software.
Validity Connect, which includes DemandTools, is a data quality powerhouse that cleans and optimizes data, addressing data deduplication, normalization, standardization, and comparison, as well as importing, exporting, and more. Learn more about Validity Connect today. And remember to…
Thank a Salesforce Administrator
Their job is crucial. When a Salesforce admin is diligent in achieving and maintaining high quality data, they can have a huge impact on your organization’s revenue generation, reputation, and ability to maintain its competitive advantage.