Clean Your Bad CRM Data & Boost Efficiencies: Best Practices

Clean Up Your CRM Data & Increase Efficiency

Clean Up Your CRM Data & Increase Efficiency 700 500 Xcelpros Team

At a Glance

Sales teams around the world rely on Customer Relationship Management (CRM) systems to drive sales force automation. Bad data or “dirty data” prevents companies from gaining the benefits of a CRM system. It causes revenue losses while risking damage to your brand reputation through incorrect messaging and lack of targeted marketing.

  • 15% of companies have confidence in the quality of their CRM data
  • Poor quality data costs US businesses $3.1 trillion per year, IBM estimates
  • Eight out of 10 companies surveyed stated that bad CRM data had a significant impact on lead generation campaigns and industry outreach
  • A data quality initiative can boost sales by 20% – 40% while reducing IT costs by 40% – 50%

An overview of CRM and Customer 360

Today’s Customer Relationship Management (CRM) solutions are a lot more than just salesforce automation or contact management tools. CRM systems are being leveraged to run Sales, Field Service, Customer Service, Project Service Automation, Marketing, internet of things (IoT), call records, emails and more.

CRM is now at the core of every aspiring company. They can capture and present a 360 degree view of 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.

Fig 1: Customer 360

One Customer’s Story

One of our customers decided to migrate to Microsoft Dynamics CRM. They immediately saw their data quality was bad and required extreme manual intervention. The clean-up initiative was a nightmare lasting several weeks requiring 10 full-time people to clean three years worth of dirty data.

Among the questions this client asked were: “Are there any tools that can help automate this clean-up? Is this some kind of prehistoric CRM?” This is more common than you might think.

Only 15% of all companies are confident in the quality of their CRM data. This customer was using a good CRM solution equipped with powerful data-cleanup tools. So why weren’t these tools used? According to the customer, they were.

A major reason for the dirty data was some technology-averse users recorded data inconsistently and used fields for incorrect purposes. Enforcing good data capture processes would have eliminated these issues.

This customer’s database includes more than 30,000 leads in the system. About 10% are duplicates. Roughly 20% of the remainder have problems such as:

  • Leads (people) not with the company
  • Missing email and contact information
  • Missing revenue details
  • Missing customer feedback


All of this dirty data delayed marketing campaigns for key events, costing revenue. Current leads are at best “unknown” causing missed sales and opportunities and adding stress to the sales and marketing teams.

Some Truth

This customer isn’t the first to have these problems. Many of our customers suffered similar ordeals resulting in lost opportunities and revenue earning potential.

How did data get this dirty, and most importantly, what are the lessons learned?

A few of the many ways that a CRM system can go from a super valuable tool to an expensive headache are:

  • Improper training
  • Years of incorrect processes when capturing data
  • Failing to perform due diligence when selecting specific fields
  • Careless typos
  • Lacking an embedded data quality management

These recurring issues can be addressed proactively by active management.

Why is CRM data critical for companies?

The success of an organization relies on a constant flow of smart data-driven decisions. This creates the question: “How do you make the right decisions to ensure organizational growth?”

Among the environmental challenges facing chemical and pharmaceutical firms are setting and meeting public targets for greenhouse gas (GHG) emissions in-line with the 2018 Intergovernmental Panel on Climate Change (IPCC) report.

High-quality information and strategy are the pillars of any objective decision taken within an organization. Imagine the impact of incomplete or unreliable CRM data—a significant element used by sales and marketing departments—on marketing campaigns? Lead conversions and other metrics cannot be calculated because of bad data.

A CRM solution with unreliable data is similar to buildings without foundations. Just as a building can’t stand without its foundations, a customer relationship management system can’t deliver intended value to businesses without up-to-date, high-quality, reliable information.

Poor data quality costs organizations an average of $9.7 million per year. Source: Gartner Research


Trillion amount of loss being incurred by US-based businesses annually due to poor quality data.

Source: IBM

How to Identify dirty data

Dirty data or bad data refers to information with incorrect facts or assumptions. It can exist anywhere —in your CRM, ERP, shared documents, reports, etc.— and it’s usually a specific type of error or simple mistake.

According to Techopedia: misleading data, incorrect data, inaccurate data, duplicate data, non-integrated data, misspelled data, non-formatted data and incomplete data fall within the category of dirty data.

Some definitions are:

Sources of bad CRM data

  • Invalid Data: Information that is inserted in wrong fields, records that cause software errors or unusable information from improper formatting.
  • Fraudulent Data: Intentional insertion of wrong information by users or sophisticated CRM bots designed to adversely impact a company.
  • Duplicate Data: Records of the same customer under various pseudonyms and accounts input by user error.
  • Inconsistent Data: Data redundancy in the system that when left unchecked, causes greater problems.
  • Outdated Data: CRM data that was valid years ago but was not updated or is no longer required.
  • Incomplete Data: Records that don’t contain important information requiring additional material to make it functional.

The Cost of Dirty Data

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.

Consequences of bata CRM data

  • Companies can’t afford to ignore their CRM data quality.
  • Companies need an effective approach to data quality management when they want to convert bad leads to viable customer opportunities.
  • Implementing a Data Quality Management initiative can boost sales by 20% – 40%.
  • IT spending can be reduced by 40% – 50%.

Bad data costs U.S. companies $3 trillion a year. Most organizations lose $14.2 million a year. Source:

How bad CRM data impacts a business

Bad data cost businesses a minimum of of their revenue, which reached as high as 25% in some cases. – EXPERIAN | 2017

Dirty CRM data is a plague that should be eradicated. Its impact on a single business can be staggering. Drawbacks to having and using outdated, inaccurate or just plain bad data include:

  • Increased maintenance costs and resource utilization
  • Lower customer satisfaction and retention
  • Increased errors in messages and emails, resulting in spam reports and potential fines of $16,000 for each email sent in violation of the CAN-SPAM Act
  • 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

Impact of bad CRM data on sales

Any one of these effects is bad news for a business. Dirty data can create many of them at once.

Figure: 1Impact of Bad Data in all Areas of the Enterprise

Impact of bad CRM data on Enterprise

The typical organization invests roughly $150,000 to generate 1,000 leads.Of these leads, only 30% are typically routed to sales and 700 leads are left behind. This translates to the company losing millions of dollars in pipeline opportunities– Carlos Hidalgo, Founder & CEO of VisumCx

Data Failures are Expensive

Data failures can happen to any organization big or small causing serious damage. The cost to repair a company’s reputation can be in the millions. Fines and penalties for legal violations are already steep, and will continue to rise.

For example, the Fleet Bank set out to deploy a $38 million CRM project in 1996. The project failed to meet its objectives for three straight years, leading to a complete failure, TDWI reported.

  • A large insurance wasted thousands of dollars on a campaign from duplicate records in its list of mail contacts.
  • Erroneous data entry prevented bills from being sent, costing a major telecommunications company $8 million in one month.

Risks due to bad CRM data

A global chemical company’s failure to identify and reconcile with global suppliers cost it millions in lost volume procurement discounts. The average cost of fixing and cleaning a single, duplicated data record can range anywhere from $20 – $100.

Prevent Dirty Data with Data Quality Management

Multiple data challenges

Most organizations don’t have a data quality management strategy in place. A minimum amount of planning would enable these organizations to design a suitable data quality management (DQM) plan. A DQM plan ensures that the information gathered within a developed long-term business strategy is properly maintained. Such a plan prevents interruptions to day-to-day operations. Among the topics the DMQ looks at are:

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

It’s time to Clean Your CRM Data

Data decays at an average rate of 2% per month or up to 25-30% per year. Losing any of this data often results in lost opportunities. Cleaning 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 a company achieve this? What are some ways to prevent dirty data?

ways to prevent dirty data

  • Regularly update complete customer information: Train the sales and marketing staff to gather all essential data during their customer contacts.
  • Integrate other systems with the CRM solution to update purchase order details and customer payment status levels. This helps keep customer details current.
  • Maintain records. Stored information becomes stale in the database when it is unused or administrators have not actively managed it. Confirming customer information at every contact helps prevent this. Another option is hiring professional database cleaners to keep the CRM data current.

Other methods include:

Setting a data quality policy. Management can hold CRM data input training sessions while using a comprehensive data management policy to guide employees.

Automating data entry to avoid incorrect data insertion and duplication using software that automatically captures and logs information. When manual entry is the only option, check what’s been input for spelling and grammatical errors.

  • Ensuring only clean data is entered into the CRM database

Clean CRM Data Creates Successes

With a little planning and by having the right processes in place to follow, a company can turn its CRM into the organization’s financial heartbeat. Businesses of any size can benefit from keeping clean data.

For example, Schwan Food Company’s parent firm was greatly impacted by invalid customer records leading to delays in delivery. Customer service representative efforts to satisfy complaints were wasted. The company placed a concentrated effort on eliminating duplicate CRM data. This generated a quality data management solution removing duplicate customer records and establishing a 360-degree view of the customer. The result was better customer service.

After a merger, MSC Industrial Direct Co. – a Forbes Platinum 400 company – discovered its business workflow was being affected by duplicate customer record entries, causing compensation issues within sales. To resolve this, the organization implemented a business-insight driven data management solution that removed duplicate customer records while minimizing credit risk exposure.

How to reap benefits from CRM data

Use Dynamics 365 Rules to Keep Data Clean

Microsoft Dynamics customer engagement apps (Dynamics 365 Sales, Dynamics 365 Customer Service, Dynamics 365 Field Service, Dynamics 365 Marketing, and Dynamics 365 Project Service Automation) automatically detect several types of duplicate records. These include: accounts, contacts and leads.

Companies can use Dynamics 365 to clean data by having authorized users—systems administrators and above—create new rules to avoid duplications in other fields. They can create a new duplicate detection rule or edit an unpublished one.

The process starts by selecting a base record type and then a matching record type plus criteria such as “Exact Match.”” The people setting these rules can also exclude inactive matching records, be case sensitive, ignore blank fields and adjust other settings.

These Microsoft D365 apps have a limit of five rules for the same base record type.

Key Takeaways – Move Forward Plan

Employees of some companies take a casual approach to entering CRM data, which often results in incomplete records. Three years later there are thousands of garbage leads and contacts in your CRM. They lack a quick way to fix the data errors and cannot run campaigns until the mess is sorted.

Keeping a CRM free of dirty data CAN be done with a little work. Having the right processes in place will minimize the amount of dirty data. Your sales and marketing teams can take advantage of an immensely valuable technology.

Cleaning dirty data is admittedly a time-consuming affair: don’t ignore it. The effort you spend on cleaning your CRM is worthwhile. The effort you spend keeping data clean will lead to major growth and a positive change in your day-to-day operations.

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Artificial Intelligence in Sales Performance

How Artificial Intelligence Helps in Boosting Sales Performance

How Artificial Intelligence Helps in Boosting Sales Performance 700 500 Xcelpros Team

At a Glance

  • In today’s hyper-connected digital world, customers expect personalization, convenience, and targeted sales experiences. Sales professionals are continuously striving to provide an enhanced and integrated customer experience.
  • Sales Professionals face many challenges every day – a better understanding of buyers’ needs, value communication, demand prediction and most importantly, staying connected with the customer.
  • Low customer engagement hinders companies’ brand image, forcing them to switch to other brands that better cater to customer requirements. Availability of market data and customer behavior is driving sales professionals to understand customer needs better. Enhanced customer experience ensures business outcomes.
  • Sales powered by Artificial Intelligence is the differentiator that can build better customer relationships as AI helps to understand customer behavior, enhances your ability to forecast, and enables you to focus on sales that matter. AI in sales also helps you in effective demand forecasting to stay in line with the market demands.

The Age of Distraction

Your sales departments play a pivotal role in your organization. They face numerous challenges in increasing customer satisfaction. The significant consequence of living in a digital era is that sales reps get defocussed as they cannot accurately read the customer information. Sellers need appropriate tools to instill a focused effort on sales.

These distractions reduce sales efficiencies by 14%

59%Sales people claim to have too many tools

64% Sales reps’ time is spent on non-selling activities

50%Sales reps’ have no idea about what is expected of them

In addition to distractions, sellers face increasing complexity in today’s sales environment. They work with an average of 10 stakeholders for every purchase decision to be made, resulting in buying decisions to take 97%¹ (Gartner) longer than expected.

Yet, 60% of companies lack a well-defined sales process, further contributing to the long sales cycles. The need to work with different functions and people requires more collaboration, adding to its complexity.

Using Artificial intelligence in sales helps you streamline your sales process by automating various functions like – sales execution, tracking sales performance, connecting with prospects helping you increase your conversion and win rates.

For instance, AI automation in sales has helped automate purchasing using bots decreasing 15 to 20% of expenditure sourced through e-platforms.

Gartner predicts that 30% of all B2B companies will employ some type of AI to augment at least one of their primary sales processes by 2020. Your competitors are experimenting with artificial intelligence, looking at the benefits it offers from automating their sales processes. Per McKinsey, companies using artificial intelligence in sales have seen –

  • 50% increase in leads and appointments
  • 40-60% decrease in overall costs
  • 60-70% decrease in call time

While staying at par with competition makes automation a must, clarifying the software’s personalized capabilities and limitations is paramount.


of customers will manage their relationships with different enterprises using bots or virtual assistants by 2020.

Source: Gartner

Smart CRM Solutions Can

  • Transform decision-making across many functional areas
  • Unite key functional areas on organizational goals
  • Improve efficiency, accuracy, profitability
  • Allow staffers to do more creative & strategic work

How can AI help your sales department?

There remains a misconception that AI automation can replace humans. Instead, AI helps humans to increase accuracy and perform their jobs better than before. Incorporating artificial intelligence in your sales departments enables you to automate various tasks done by humans and reduces the scope for human error increasing efficiency. Your sales department can benefit from AI by –

AI for increased price optimization: To decide the discount to be given to a client is always a tricky question for companies. As important as winning the deal is, leaving money on the table is a loss for you. Adopting artificial intelligence in sales departments helps you estimate the ideal discount rate for a proposal by viewing the specific features of a past deal closed. These features also include Features could include: the size of the deal in dollars, product specification compliance, number of competitors, company size, territory/region, client’s industry, client’s annual revenues, a public or private company, and level of decision-makers (influencers) involved.

AI for Better Forecasting: Forbes estimates that 74% of large B2B firms engage in sales forecasting every week. They also estimate that 69% of companies, regardless of their size, consider their sales forecasting methods to be ineffective. Sales managers face a daunting challenge in tracking where their team’s total revenue falls short each revenue cycle. Using AI in sales can help you effectively estimate and predict your revenue, reducing your operational challenges to manage your inventory and resources better.

Companies boasting accurate sales forecasts are 10% more likely to grow their revenue and 7% more likely to meet their targets.Source: Aberdeen Group

Cross-selling and up-selling: The most effective and economical way to increase profits is to sell more to your existing client base. But how do you understand which audience to target? You can spend your revenue marketing your product to the wrong audience or use AI algorithms to identify which clients would be willing to update their product (up-selling) and/or buy a completely different product that you offer (cross-selling).

Enhanced lead scoring: 61% of companies say misleading buying signals are a huge barrier to effective lead scoring. They claim to fall prey to customers’ gut impulses and inaccurate information, which significantly hurts their lead scoring or bottom line. Per Forbes, 68% of respondents reported implementing lead scoring strategies, whereas 40% believe in the value associated with lead scoring.

Effective performance management: Sales managers are expected to eagerly track their team performance and look out for barriers in meeting their revenue targets. With AI, they can now use dashboards that showcase employee performance and help managers predict which salespeople are likely to hit their quotas and which deals have a higher chance of being closed.

Empowering your sales force with AI technology

Before investing in a pilot project, you need to meet your sales managers and understand the potential use cases to determine the suited requirement. Three types of AI technology promises results for B2B sales organizations. They are –

  • AI in Sales Predictions – Analytics like AI in sales forecasting find correlations between various data points. Such tools automatically create the insights that are essential to managers and sales reps. For example, they can determine a prospect’s likelihood to become your client and help in sales forecasting.
  • Prescriptive – Such analytics supports guided selling. AI suggests activities based on all the sales methodologies adopted by the firm. This is a step forward to move a deal to the next sales stage or develop a pricing model based on a prospect’s general preferences.
  • AI for Text and sentiment analysis with Natural Language Processing – understands and analyzes the context of customers’ questions and their behavior. Using sentiment analysis, sales reps are alerted if signs of dissatisfaction are discovered.

What Microsoft Dynamics has to offer: Exclusive Features

Dynamics 365 AI for Sales enables salespeople to build stronger functional relationships with their customers to increase customer satisfaction. It helps them take actions based on helpful insights helping them close sales faster.

Dynamics 365 AI for Sales offers the following capabilities for sellers:

  • Relationship analytics: This feature helps you assemble relevant information from the entire database to create a graphical representation of all the KPIs and activity histories. Such a visual display showcases KPIs and activity histories for any contact, opportunity, lead or account.
  • Predictive lead scoring: This feature helps you generate scores for all your leads in the pipeline. It assigns a score between 0 to 100 to leads based on signals from them and related entities such as contact and account. This helps you identify and prioritize leads with more chances of converting into opportunities.
  • Predictive opportunity scoring: This feature provides a scoring model to generate scores for opportunities in your pipeline. It assigns a score between 0 and 100 to all the opportunities based on the signals they give out and other related entities such as contact and account. This helps identify and prioritize opportunities that have more chances of converting into sales.
  • Notes analysis: Notes give you intelligent suggestions to help you save time and effort by taking actions such as creating a meeting request and adding a contact. The text in the note is highlighted and when selected, suggestions are displayed.
  • Talking points: This feature is useful to help you start conversations with customers based on emails. The conservation starters include topics that are related to Health, sports, vacation, family, and entertainment. These topics help you start a conversation with your customer, as you can choose your customer’s area of interest. Talking points will display only the latest communication for each topic in hand.
  • Who knows whom: This feature provides you details such as your contact’s name and email address who knows the lead. Using these details, you can reach out to your contact and get introduced to a lead and increase the chances of a positive outcome during the interaction.

Key Takeaways

  • Good sales professionals advance their sales processes by leveraging the right skills at the right time. They become agile in their approach to numerous stakeholders who represent a host of opinions and interests.
  • Sales managers will require their workforce to have skills and tools to help customers build the case for change by understanding how factors like desired outcomes and solution options influence decisions.
  • Companies can benefit from seeing tangible rep to customer conversion analytics and identify different ways to improve deal closure rate.

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