AI Gone Wrong - The Risk of Dynamics 365 CRM with Poor Data Quality

The Impact of Poor Quality Data with AI

Unfortunately for you, the dream quickly becomes a nightmare. Your Dynamics 365 CRM data was of poor quality when you implemented those new AI tools, and the results are worse than you could have imagined. It’s a total disaster and your job is now at risk! Think this is just a story? Think again. With the rapid growth of Artificial Intelligence over the past year, many people are finding out the hard way that AI requires high quality data, or the results can be disastrous.

 

 

 

Lead and Opportunity Analysis

✅ AI-powered tools help sales teams prioritize leads and opportunities in CRM systems based on various metrics like revenue potential, purchase intent, and timeline.

❌ However, bad data can make these powerful insights incorrect and misleading, leading to distorted pipeline summaries, inaccurate revenue forecasts, and skewed performance metrics.

Additionally, your staff will be wasting time chasing these bogus leads instead of focusing on those that are worthwhile.

 

Predictions and Insights

✅ AI models use data patterns to make predictions and provide valuable insight on topics like customer behavior patterns, sales and revenue forecasting (Lead and opportunity scoring, close probability, and revenue predictions.) Additionally, AI can determine which products are most popular and analyze customer demographics.

❌ If the data is inconsistent, biased, or incorrect, the resulting insights will be flawed. Poor-quality data can lead to misleading trends, causing bad business decisions.

 

 

Account Analysis to Provide Outstanding Customer Service

✅ AI can enhance customer trust in CRM data by ensuring transparency, personalization, and security in customer interactions. AI can help provide outstanding customer service in the following ways:

• AI-Driven Personalization – AI analyzes CRM data to tailor recommendations, offers, and interactions based on customer preferences.
• Predictive Customer Needs – AI anticipates what a customer might need next, showing that the business understands them.
• Sentiment Analysis for Tone Adjustment – AI detects customer sentiment in messages and adjusts responses for a more empathetic and helpful approach.

❌ Bad data can result in AI suggesting incorrect products, false fraud alerts, or poor customer service interactions.

 

Identifying Opportunities for Market Trends

✅ AI can help identify market trends and opportunities in CRM data by analyzing customer interactions, and preferences.

AI analyzes historical CRM data to detect patterns in customer behavior, purchases, and preferences. It can also predict emerging trends by identifying shifts in customer engagement, purchase frequency, and sentiment. AI can also scrape competitor mentions and customer feedback to identify gaps or opportunities in the market.

❌ Market Trends: Inaccurate or incomplete data can lead to missed insights into market trends, preventing businesses from capitalizing on emerging opportunities.

 

Increase Operational and User Efficiencies

✅ AI significantly enhances operational efficiencies by automating processes, reducing manual effort, and improving decision-making. Some examples include:

• Automated email follow-ups and reminders
• Enhanced customer support efficiency via chatbots and virtual assistants
• Automated workflow triggers based on customer behavior, opportunity budgets or the number of leads.

❌ Garbage in, garbage out—bad data leads to wasted resources, time, and costs trying to correct errors after they’ve influenced decisions.

 

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The Importance of Data Quality

Accurate insights depend on high-quality data for AI tools. Common data quality issues—including duplicates, incomplete information, and outdated records—can significantly affect the performance and efficiency of AI-driven Dynamics 365 CRM systems as well as business decisions.

Data Cleansing and Maintenance Tools

To ensure high data quality, tools like Paribus 365™ assist in cleansing duplicates and preventing their creation. Additionally, address management and data enrichment solutions from vendors such as Smarty, SumSub, ZoomInfo, and Clearbit can enhance CRM data quality. These tools can automatically fill in addresses and enrich customer profiles with relevant organizational and demographic information.

Data Governance Framework

Implementing a Data Governance Framework is essential for maintaining long-term data quality. This framework should contain clearly defined guidelines for data entry, merging, and reporting issues, which will ensure that AI capabilities are fully utilized with clean, reliable data. 

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Summary

Artificial Intelligence (AI) in Dynamics 365 CRM systems has the potential to transform decision-making and increase efficiency. However, its effectiveness depends heavily on having clean and accurate data. To fully harness the power of AI tools, businesses must invest in maintaining high CRM data quality. This investment helps prevent errors that could negatively impact customer relationships and business outcomes.

For organizations looking to improve their data management, tools like Paribus 365™ are recommended for removing duplicates and ensuring data accuracy.

For more information on this topic, including tips and recommendations with detailed scenarios for each capability mentioned above, please watch our 30-minute recorded webinar: "Artificial Intelligence (AI) and Dynamics 365 Improved with Clean Data."