Customer Relationship Management (CRM) Clean Your Bad CRM Data & Boost Efficiencies

At a Glance

• Sales teams world over, rely on Customer Relationship Management (CRM) systems to drive sales force automation.
• According to Gartner, one of the prime reasons why organizations have not been able to derive the intended benefits from a CRM system is due to bad data, also referred to as dirty data.
• Only 15% of the companies are confident of the quality of their CRM data.
• IBM Estimates that poor quality data costs US businesses $3.1 trillion per year.
• Every 8 out of 10 companies surveyed reported that bad CRM data had a significant impact on lead generation campaigns and industry outreach.
• A data quality initiative can raise your sales bar as high as 20-40% and you can cut down your IT cost by 40-50%.
• Bad data in CRM not only causes greater loss in revenue but also places your brand reputation at stake possibly due to incorrect messaging, lack of targeted marketing etc.
• This article talks about the importance of CRM data, its impact to your interactions with your customers and ways to proactively ensure clean data that can be of significant value to your business. The article connects the pain in your real-life and provides solutions to the practical problems we all face.

Why is CRM and its data critical for your business - An overview of CRM & Customer 360Today's Customer Relationship Management (CRM) solutions are a lot more than just Salesforce Automation or Contact Management tools. CRM systems are being leveraged by most organizations to run their Sales force, Field Service, Customer Service, Project Service Automation, Marketing, Surveys, IoT, Telephony and Call Records, Emails, the list goes on..CRM is now at the core of every aspiring company.Industry-leading CRM applications have the ability to capture and present a 360 degree view of all your customer interactions in real-time. Different departments within your organization can benefit from this single source of truth. Embedded Analytics tools assimilate data from different data sources such as ERP, Big Data, Social Media, Email interactions and aid in building this 360 degree view. It is imperative to plan for and include Data Quality Management (DQM) processes and tools while managing such critical data.A Real-Life Story..One of our customers decided to migrate from an industry-leading CRM to Microsoft Dynamics CRM. On the onset of the project, they realized that their data quality was bad and required extreme manual intervention. The clean-up initiative was a nightmare and lasted a few weeks. They had to engage more than 10 resources full-time to clean three (3) years worth of dirty data. Sounds ridiculous, but true.Aren’t there any tools that can help automate this clean-up? Is this an archaic dinosaur-age CRM, or what?Only 15% of all companies are confident in the quality of their CRM data.Quite the contrary, the customer was using a good CRM solution embedded with all kinds of powerful data-cleanup tools out-of-the-box. So why weren't these data cleanup tools used? They did.Despite the data clean-up and tools, there was a significant amount of additional manual intervention required because some of their technology-averse users decided to record data inconsistently and used fields for incorrect purposes. This could have been controlled by enforcing good data capture processes in place. Hindsight is always 20/20.They have more than 30000 leads in the system with approx. 10% of them being duplicates. 20% of the remaining leads are filled with incorrect data such as:

• Leads (people) not still with the company
• Missing email and contact information
• Missing revenue details
• Missed customer feedback / surveys etc and many more

What's the consequence?Marketing campaigns for key events had to be delayed, resulting in a loss of tangible revenue. The status of current leads is at best "unknown" leading to missed sales and opportunities, causing a huge deal of stress to the sales and marketing teams..So, here is the truthThey are not the first to experience this. Quite a few of our customers have been through a similar ordeal resulting in lost opportunities and more importantly the loss of serious revenue earning potential.How did data get this dirty, and most importantly, what are the lessons learned?Below are just a few of the many ways that a CRM system can go from a super valuable tool to an expensive headache.

• Years of incorrect processes when capturing data
• Improper training
• Failure to perform due diligence when selecting the fields for specific data
• Simple typos
• Lack of a data quality management processes embedded within the overall flow

These issues are recurring and can be addressed proactively with active management and right processes. In the sections below we will talk more about the detrimental effects of having a CRM with unusable / ineffective data, and ways to avoid it.Why is CRM data critical for companies?The success of an organization to a great extent relies on an incessant flow of smarter data-driven decisions. The question that arises in this context is: How do you make the right decisions to ensure organizational growth?

• High-quality information and strategy are the pillars of any objective decision taken within an organization. Just imagine if the CRM data, a significant element to be used by the sales and marketing departments of any organization, is filled with bad, dirty or even unreliable data? How successful would marketing campaigns be? Can Lead conversion be even calculated or improved upon? There are so many metrics that are not relevant because of bad data.
• A CRM solution with unreliable data is similar to buildings without foundations. Just as a building cannot stand without its foundations, a customer relationship management system cannot deliver its intended value to the business without up-to-date, high-quality, reliable information.

Dirty data - What is it and How to identify it?The term Dirty data / bad data refers to data consisting of any number of incorrect facts or assumptions. It can exist anywhere - your CRM, your ERP system, shared documents, reports etc.- and it’s usually a specific type of error or mistake.According to Techopedia: misleading data, incorrect data, inaccurate data, duplicate data, non-integrated data, misspelled data, non-formatted data, incomplete data, all fall within the category of dirty data.

• Invalid Data: Information that is inserted in wrong fields, records that cause software errors, unprocessable information due to erroneous formatting.
• Fraudulent Data: Intended insertion of wrong information by users or sophisticated CRM bots to take the you out of the competition.
• Duplicate Data: Records of the same customer under various pseudonyms and accounts due to user error.
• Inconsistent Data: Data redundancy in the system that is unchecked over a period of time causing bigger inconsistencies.
• Inaccurate Data: CRM data that was valid in the past years, but was not updated or no longer required.
• Incomplete Data: Records that don’t contain holistic information, requiring additional CRM data fields to make it a functional information.

Many companies overestimate their quality of data and at times even ridicule any chance of dirty data attack to their business. This often causes significant losses in business.

• CRM data is no longer an issue that companies can afford to ignore.
• You need an effective approach to data quality management and convert bad leads to viable customer opportunities.
• Implementing a Data Quality Management initiative can benefit your organization with a 20-40% increase in sales.
• Additionally, you can cut down the IT spend of your company by as much as 50%.

How can bad CRM data impact your business?Dirty CRM data is a plague, and it must be eradicated. The impact bad data can have on a business is staggering, and understanding how to avoid it is a strength as some of the side-effects include

• Increased maintenance costs and resource utilization
• Lower customer satisfaction and retention
• Increased errors in messages and emails, resulting in spam reports
• Prolonged sales cycles heightening costs
• Reduced productivity and performance

• Affected sales and distribution channels due to inaccuracies
• Non-compliance issues resulting in regulatory penalties
• Damage to reputation and a decrease in revenue generation

Any one of these things alone can be bad news for a business, and dirty data can create many of these effects at one time.The typical organization invests roughly $150,000 to generate 1,000 leads.

• Only 30% of those leads typically get routed to sales.
• The company leaves 700 leads behind that are never routed to sales.

This translates to the company losing millions of dollars in pipeline opportunities.- Carlos Hidalgo, Founder & CEO of VisumCxAre data failures in CRM history?It can happen to any organization big or small, and it can lead to serious damages. Damage to reputations can cost millions, and fines and penalties as well, can be quite steep - just as the following companies found outIn the banking sector, the cost of dirty data is over $400 billion, an estimated 15%-25% of its global revenue, at $2.2 trillion.

• The TDWI reports that in 1996, the Fleet Bank (at present a part of Bank of America) set out to deploy a CRM project of $38 million. Consecutively for three years the project failed to generate the expected outcome as per the objectives, and as a consequence led to a complete failure.
• A large insurance firm had to suffer an annual loss of thousands of dollars during a campaign due to duplicate records in list of mail contacts.
• Erroneous data entry cost a major telecommunications company $8 million in one month, by preventing bills from being sent out.
• A major Information services firm suffer an annual loss of over $500,000 due to inaccurate data. This caused reports to be recalled over and over, which were sent to out subscribers and as a result led to a loss of a significant amount of customers.
• A well known bank discovered that 62 percent of its home equity loans were being miscalculated leading to a higher principal every month.
• A global chemical company unearthed the root cause of millions of lost dollars in volume discounts in the procurement of supplies. The organization had failed to identify and reconcile with suppliers globally.

The average cost of fixing and cleaning a single, neglected data entry is $100. Per IBM, in the US, average yearly expense of dirty data is in excess of $3.1 trillion.What is Data Quality Management (DQM)?The image above tells us that most organizations don’t have a strategy in place to manage data quality. A minimum amount of planning would enable these organizations to design a suitable data quality management plan. The concept of data quality management is a standard that sees the information gathered within a developed long-term business strategy able to efficiently and successfully handle day-to-day operations is correctly maintained. The following key aspects are essential in achieving a certain level of quality:

• Accuracy: Is the information right and can it be validated?
• Integrity: Does there exist a coherent, logical structure?
• Consistency: Is the data consistent and easily understood?
• Completeness: Does it provide all the information required?
• Validity: Is it within the acceptable parameters required by the business?
• Timeliness: Is it available whenever required?
• Accessibility: Can the data be easily accessed and exported to other applications?
• Compliance: Does it comply with regulatory and industry standards?

How dirty is your CRM data? It’s time to cleanIt’s said that data decays at an average rate of 2% per month, that can add up to as much as 25-30% of your data every year.Every 8 out of 10 companies surveyed reported that their lead generation campaigns were negatively impacted by bad CRM data, and approximately 6 out of 10 expressed concerns regarding compromised marketing efforts due to inaccurate databases and dirty data. To marketers, losing any data is bad and usually results in damaged opportunities. Cleaning up this data lets your marketing efforts reach prospects faster, helps target the right audience, increases revenue from campaigns, and eliminates wasted time and labor.So how can we achieve this? What are some ways that we can prevent dirty data?

• Updating Complete Customer Information: The sales and marketing staff need to be trained to gather all essential data during their contact with customers. Integrating other systems with the CRM solution in your organization helps to update purchase order details such as invoices, and payment status for customers, allowing complete customer details to be obtained automatically.
• Maintaining Up-to-Date Records: The information in the database can go obsolete if it has not been used for a while or the administrators have not managed it actively. One way to deal with this is by confirming customer information whenever in contact. In case the customer email address has changed for example, you would now update that accordingly. There is even the option of hiring professionals to perform database cleaning services helping to keep your CRM data up-to-date.
• Setting the Data Quality: You can seek assistance from your management team, requesting them to conduct training sessions on the management of data in CRM solution. Alternatively, the administration can take initiatives to prepare a comprehensive policy on data management, making it a continuous commitment for the staff. This will guide employees in meeting data standards day after day.
• Implementing Automation Procedure: Wherever possible, automate data entry to avoid incorrect data insertion and duplication. Use software that can automatically capture and log data. In cases when manual entry may be the only option, put forth your best efforts to avoid typos or misspells. Get it right on the first attempt!
• Analyzing and Getting New Prospects: While you can contact your existing customers with CRM data, it cannot get you new prospects to boost your sales. The marketing team needs to put more effort in finding potential leads to include them into the sales pipeline. As you find new prospects, keep on updating their details in the CRM solution.

Clean CRM data - Success storiesIt’s very easy to ignore the data in your CRM allowing it to cause severe damage to your business, but with a little planning and by having the right processes in place to follow, you can turn your CRM into your organization’s financial heartbeat. Businesses of any size can benefit from keeping clean data, as the following examples show:

• The home service of well-known Schwan Food Company was greatly impacted by invalid customer records which were leading to delays in delivery and the efforts of customer service representatives to satisfy complaints were going wasted. The company placed a concentrated effort on eliminating the duplicate CRM data. The solution was a quality data management solution that improved their customer service by removing duplicate customer records and establishing a 360-degree view of the customer.
• Following a merger, MSC Industrial Direct Co. - a Forbes Platinum 400 company - discovered that its business workflow was being affected due to duplicate customer record entries. This brought about compensation issues within sales. To resolve this, the organization implemented a business-insight driven data management solution that allowed them to minimize their credit risk exposure by removing duplicate customer records from the system.

Key Takeaways – Move Forward Plan

• You may have been using your CRM with little thought to the data that was going into it. You think you’ll just put some lead information here, and a contact’s information there, and you’ll feel good for doing your job. Three years later you’ve got literally thousands of garbage leads and contacts in your CRM and there’s no way to quickly fix it, no way to run campaigns, and a mountain of work ahead to attempt to salvage as much data as you can.
• You may think it’s impossible to keep your CRM solution entirely free of dirty data, but it CAN be done - with a little work and the right processes in place the amount of dirty data in your system can be minimized, allowing your sales and marketing teams to take advantage of an immensely valuable technology.
• Even though cleaning dirty data is a time-consuming affair, don’t ignore it. The effort you spend on cleaning your CRM is a worthwhile investment, and the effort you spend maintaining clean data in your systems can lead to major growth and a positive change in your day-to-day operations.

Source: https://xcelpros.com/clean-your-bad-crm-data/