CRM Data Entry 5 Tips for Data-Heavy Companies

The average CRM user spends approximately 6 hours a week on CRM data entry and management tasks, equating to an entire workday lost due to manual data entry processes. This inefficiency doesn’t just affect personal productivity; it also drains business performance, pulling focus and resources away from truly important efforts like building customer relationships.

There are at least five actionable strategies for automating CRM data entry: Optical Character Recognition and AI, data scraping, third-party integrations, voice data entry, and workflow automation.

What is CRM Data Entry?

CRM data entry is a process of inputting and organizing customer information, interactions, and other relevant business data into a dedicated CRM system.

Most CRM users dislike managing and updating CRM data. According to Statista, manual data entry was among the top challenges in utilizing existing CRM systems worldwide several years ago. Manual data entry, cited by 23% of users, remains a significant barrier to effective CRM usage even nowadays.

Source: statista.com

What Is CRM Data Entry Automation?

CRM data entry automation refers to the process of capturing, inputting, updating, and managing data in CRM systems using software tools and technology, with no or minimal human intervention.

Examples of automated CRM data entry include:

• Auto-logging customer emails and calls
• Creating new contact records from web form submissions
• Adapting customer information from social media profiles
• Auto-scoring leads based on customer interactions.

For CRM data entry automation, you can use OCR (Optical Character Recognition), which turns physical documents into digital data, along with AI and APIs that integrate data into disparate systems seamlessly. Below are more specific techniques for automating CRM data entry.

5 Methods for Automating CRM Data Entry

Based on industry practices and technological advancements, the five most effective methods for automating CRM data entry fall into AI-driven strategies and workflow optimizations.

To streamline CRM data management, companies can implement the following automation methods:

Optical Character Recognition & AI

Let’s explore five proven ways to automate CRM data entry, including AI-powered solutions and system-level improvements to streamline data entry workflows.

Document-Based CRM Data Entry Automation

Document processing is one of the most labor-intensive aspects of CRM data management, particularly in industries handling large volumes of contracts, invoices, and forms. This is where Optical Character Recognition (OCR) and Intelligent Document Processing (IDP) come into play.

How It Works:

• OCR (Optical Character Recognition): Converts scanned text from physical or digital sources – like PDFs or handwritten notes – into clean, machine-readable data.
• Intelligent Document Processing (IDP): Extends OCR functionality; it validates extracted data, categorizes it, and prepares it for direct CRM integration.

For example, OCR can scan a business card and pull details like name, phone number, and email into a CRM record. IDP goes further by processing tables in invoices, validating amounts, or identifying document types for better organization.

How OCR paired with IDP works:

Step 1: Document/Image upload to the system or application. It may be a PDF, scanned image, handwritten notes, or other formats of collateral.

Step 2: Data Extraction with the mentioned above OCR technology and finalized with Natural Language Processing (NLP) techniques that analyze the text to understand its meaning and extract relevant information.

Step 3: The third step repeats the step from OCR – Identifying Uncertain Segments. The only difference is that once AI data entry tools identify uncertain elements within the analyzed document, they request the user to check and correct the uncertainties.

Step 4: Data validation process that is based on validation rules and algorithms to identify and correct errors, missing information, or inconsistencies in the data.

Step 5: Data transformation is the fifth step, and it includes formatting, standardization, or cleaning to ensure uniformity and compatibility with target systems.
Step 6: Export the processed, standardized, and validated data into CRM.

CRM data entry automation using AI is also based on constant involvement from your side. Here, we mean the following:

• Set up validation rules to check that the data entered into the CRM is correct and complete. Use the AI to flag any potential errors or discrepancies. As a result, the system will validate dates, amounts, and names, ensuring everything matches expected formats and values.
• Continuously train your AI Model as the number of your documents grows. The more fine-tuned the AI model is, the more improved accuracy and adaptability you’ll get. As a result, the AI will become better at recognizing specific document layouts or uncommon terms, improving the overall automation process.

Ascendix team can help you with data entry automation. We combine deep knowledge of modern technology with expertise in data entry automation for data-heavy industries. An experience in building custom solutions for data entry in various industries gave us significant practical knowledge in building frameworks for AI search, data abstraction tools, AI recommendations, and other advanced software.

2. Text-Based Automation

This approach targets unstructured text sources, such as emails, social media messages, or chat logs, and transforms them into actionable CRM entries.

Key Technology: Natural Language Processing (NLP)

With Natural Language Processing (NLP) users can analyze and extract necessary information from various text sources like emails, chat logs, and social media interactions. The process identifies key details such as customer names, contact information, and sentiment, and automatically inputs this data into CRM systems. By applying NLP for your automated CRM data entry, you’ll free up your team, enhance the accuracy and consistency of CRM data, and keep your data always updated.

Here’s how NLP data entry works:

• Text Analysis: NLP systems first analyze the incoming text data (sentences broken down into words) from sources such as emails, chat logs, or social media.
• Entity Recognition: The system identifies and extracts key entities like names, dates, addresses, and products.
• Intent Detection: NLP determines the intent of the text, whether it is a support request, feedback, sales inquiry, review, etc.
• Sentiment Analysis: It assesses the emotional tone of the text to gauge customer sentiment, whether positive, negative, or neutral.
• Data Structuring: Extracted information is structured into predefined formats suitable for CRM integration.
• Automating Entry: Finally, the structured data is automatically populated into the appropriate fields within the CRM system, ensuring timely and efficient data entry without manual handling.

Example Use Case:

A prospect emails your support team asking about product pricing. NLP automatically identifies key data like their name, email, and inquiry type, populating the CRM fields without manual intervention.

3. Voice and Audio-Based Automation

Voice-based automation is ideal for industries where verbal client interactions (e.g., sales calls or meetings) are the primary source of information.

Key Technology: Speech-to-Text

Speech-to-text technology converts any type of audio record into text format in real-time. Key information like customer names, inquiries, and contact details are extracted and automatically entered into CRM systems.

Speech-to-text for automating CRM data entry includes the following steps:

1. The capture of audio records and their transcriptions based on advanced algorithms and machine learning models. The technology analyzes the audio, recognizes and converts speech patterns into corresponding text.
2. Natural Language Processing follows the capture of audio records. It identifies and extracts vital info like customer names, phone numbers, and key discussion points.
3. The third step is data structuring into relevant fields in your CRM. It means that the information is organized accordingly.
4. The last step involves the population of the structured text data into the appropriate fields within the CRM system

4. The Rise of Speech-to-Text in CRM: Virtual Agents

This technology is now being used in CRM platforms as Virtual Agents. For example, Salesforce CRM has introduced AgentForce, a cutting-edge tool designed to act as an intelligent CRM assistant.

It is a suite of AI-powered, trusted, natural language conversational agents that transform businesses’ operations. Unlike basic automation tools, AgentForce leverages advanced language models (LLMs) to understand context, make decisions, and execute complex tasks.

With over 20 years of expertise in Salesforce consulting and custom software development, our team can empower your business with any Cloud Salesforce has and an advanced AgentForce solution.

5. Workflow Automation Tools

Automation doesn’t end with data extraction. One of the most impactful ways to enhance your CRM operations is by automating how data flows through your system and enabling seamless, actionable workflows.

This is where workflow automation tools truly shine, particularly in Salesforce.

We took Salesforce as an example because it is a well-known CRM platform and it offers extensive customization functionality accompanied with a wide range of applications.

So, how to automate CRM data entry in Salesforce? Let’s analyze it briefly.

• Integrate through APIs with third-party tools to enable seamless data transfer from various channels into Salesforce.
• Leverage Salesforce Einstein to automate data entry tasks such as automatically filling in of missing data fields, lead scoring leads, etc.
• Explore tools like Flow and Process Builder to create automated workflows for handling repetitive data entry processes.  Based on specific events these tools can trigger required actions.
• Implement OCR technology within Salesforce that we’ve described in the previous passage.
• Integrate the speech-to-text services mentioned above, which transcribe and process verbal customer interactions into text, which is then automatically entered into Salesforce, enhancing efficiency and record accuracy.

To ensure a smooth automation process, engagement with Salesforce AI consulting partners like Ascendix will benefit you.
Our consultants can answer all your questions, dispel doubts, and guide you step-by-step through decision-making, customization, and implementation. We focus on understanding your unique business objectives and gathering requirements to design customized AI solutions that deliver tangible value.

CRM Data Entry Automation Benefits

CRM data entry automation is no longer a promo heading from a marketing team. It’s a beneficial process that has been implemented by a number of companies. Here are the benefits that they received.

*Please note, that names are changed due to the privacy policy

“Automating our CRM data entry has been a game-changer for our sales team. We now have cleaner, more accurate data, which has significantly improved our lead qualification process. This has led to more closed deals and increased revenue.”– Jane Smith, Sales Director

“Before implementing automated data entry, our sales team spent 5+ hours weekly on manual data input. Now that time is cut by 80%, allowing us to focus on actual selling.”– Sarah Rodriguez, Sales Operations Director

“We reduced our data entry costs by 60% while doubling our database size. The ROI was evident within the first quarter.” – David Thompson, Operations Manager

So, based on the testimonials above, CRM data entry automation is beneficial because it:

• saves time
• provides cleaner database
• increases ROI
• reduces errors
• ensures reliable information.

5 Common CRM Data Entry Challenges

Challenge #1. Manual Data Still Wins Over Automated CRM Data Entry

One of the significant challenges in the realm of CRM adoption is still the reliance on manual data entry. While automation technologies have advanced with AI data entry, manual data entry remains prevalent in data-heavy industries. This dependency persists due to cost constraints, lack of technological adoption across these industries, and the need for human judgment in certain contexts.

Manual data entry is not only time-consuming but also prone to errors. According to various reports, human error rates in manual data entry can be as high as 4%, leading to inaccuracies that can significantly impact business operations. As a result, manual data entry continues to play a crucial role, even though it is less efficient and more error-prone compared to automated CRM data entry.

Challenge #2. Employees are Reluctant to CRM Data Entry

CRM data entry can be monotonous activity and most employees may be reluctant to perform it. Data-heavy industries consist of many transactions, client communications, and property listings, contracts, invoices, offering memos that generate significant amounts of data, making it challenging to keep the CRM updated accurately and in real-time.

Challenge #3. Huge Relying on Excel as a Core CRM Solution

Even though Excel is a commonly accepted tool, data deduplication and visibility in Excel tables are among the biggest headaches for data entry operators.

Without stringent controls and data cleansing tools, duplicate entries can proliferate, impacting data visibility and accessibility. For instance, a client’s contact information might be entered multiple times with slight variations resulting in duplicated records that will be difficult to find and allocate within thousands of records in the database.

Data deduplication is hard to control, and without proper automation, it may cause money loss.

Challenge #4. Stereotype That Automated CRM Data Entry is Less Secure Than Manual

For many companies, automated CRM data entry presents significant security challenges compared to manual data entry. Key concerns with automated CRM data entry include:

• Increased vulnerability to cyber attacks
• Data encryption and storage
• Compliance and privacy risks
• Internal threats
• Regular updates and vulnerability management.

Challenge #5. Lack of Standardization

Lack of standardization causes inconsistency across the team. It leads to CRM data duplication entries, missing fields, and inaccurate data overall. Whether your team enters data into CRM from property valuation details, property listings, sales and commission information, legal files, invoices, contracts, or other documents, the process should be based on specific rules.

How Can Ascendix Help in Automating CRM Data Entry?

Ascendix team is a galvanizing force in the pulsating heart of CRM customization (Salesforce, D365, and any other CRM), automation of business processes with AI technologies, and Salesforce AI consulting services (including all Salesforce clouds and newly introduced AgentForce).

Due to our 27+ years of expertise in CRM consulting, we combine professionalism with sparking creativity and catalyze innovation at every turn.

Our consultants can answer all your questions, dispel doubts regarding CRM data entry automation, and guide you step-by-step through decision-making, customization, and implementation. We focus on understanding your unique business objectives and gathering requirements to design customized solutions that deliver tangible value.

For companies who want to automate CRM data entry, we can:

• customize your current version of Salesforce and implement AI technology in it;
• audit current CRM solution and suggest data entry best practices;
• consult about existing AI technologies for processing big data and suggest the best integration options.

Contact us directly or book a FREE CRM consulting call to learn how you can leverage our CRM consulting expertise to empower your business.