Enhance: Enriching Your CRM for Deeper Customer Insights

Imagine you know everything there is to know about your customer to speak directly to their challenges, goals, and current needs. Personalized interactions become a breeze, marketing messages strike a chord with your target persona, and your sales are trending in the right direction. 

Enhance is a stepping stone for businesses to capture a competitive edge in their market by getting a more complete view of their customer. Enhanced data is a crucial component of a customer-centric approach built to grow long-term, mutually beneficial relationships with customers that drive bottom-line results. 

On the journey to a clean CRM, you aren’t just taking out bad data — you’re infusing your empty or outdated field data with quality data. For a richer, more complete 360-degree view of your customer, here’s how to complete the Enhance phase.

The CRM Hygiene Series

This blog is part of a comprehensive series of guides that dive deeper into each of the five steps in the CRM data hygiene process. Navigate to each step to learn more about each step, including how to apply them, why they’re necessary, and the technical aspects of it all below.  

The 5-step process overview

  1. Define
  2. Analyze
  3. Purge
  4. Enhance
  5. Maintain

A Key Challenge: Data Ingestion and Survivorship 

Enriching your data means you’ll run into some challenges. Namely, data survivorship and making sure you’re keeping, not losing, the right data. When blending first- and third-party data to enrich your datasets, you may have existing data in several fields, which raises the risk of data loss. 

To prevent losing data, apply the survivorship rules you established in the Define phase. These rules work as the backbone that keeps the accuracy of vital data. Survivorship rules help you maintain data integrity long-term.  

1. Fill Gaps of Existing Records in the TAM

What this step does: Filling gaps in your total addressable market (TAM) locates empty fields and fills their missing records with complete and up-to-date data. 

Why it matters: Full and accurate records are essential for understanding your market coverage, creating personalized messaging, and making optimal business decisions. 

Results to expect: By enhancing your data, you’ll work with a more detailed and comprehensive understanding of your target audience. You’ll be able to segment data much better for more targeted marketing. 

How to do it: Review your records against the TAM to spot missing information. Use data enrichment tools to automatically update these records with the needed details.

The technical details

This process typically involves integrating your CRM with data enrichment services. These services match your records with their databases, using algorithms to ensure accuracy, and then automatically fill in the gaps. 

The integration often requires API calls that match records based on key identifiers like email addresses or company names, assuring the information added is precise and relevant.

2. Add Businesses and Professionals Not Currently in the Database

What this step does: Extends your database by incorporating records of potential customers. As a result, your CRM reflects a wider slice of your market.

Why it matters: Expanding your database enriches your pool of potential leads, which is vital for exploring new business opportunities and broadening your reach.

Results to expect: You’ll increase the quantity of leads and potential contacts, offering fresh opportunities for engagement and conversions.

How to do it: Introduce lead-generation tools and external data sources to identify and add new businesses and professionals. This can be done through direct integration with your CRM or by importing data from reputable sources.

The technical details

Adding data not currently in your database takes APIs or import tools that integrate with your CRM. The process requires matching external records with your existing data structure and ensuring new entries are correctly formatted and free from duplicates. 

This is where applying data normalization and deduplication algorithms to maintain the integrity and usability of your database is key.

3. Standardize Field Values

What this step does: Ensuring parity across field values harmonizes the format and structure of data across your CRM, making sure every entry follows a uniform template. This consistency applies to all data fields, from contact names to addresses and beyond.

Why it matters: Working with uniform data makes it easier to manage, search, and analyze your CRM records. It eliminates confusion, improves the accuracy of your data-driven decisions, and enables teams across the business to work from the same data. 

Results to expect: Your CRM will become more user-friendly, trustworthy, and reliable, with fewer errors and inconsistencies. Analyzing and segmenting your data for marketing and sales will also become more straightforward.

How to do it: Define a standard for each data type within your CRM and use data cleansing tools to reformat existing entries to match these standards. This can include automating the correction of common misspellings, standardizing date formats, and unifying address formats.

The technical details

Applying field value standardization typically involves scripting within your CRM or employing data cleansing software that can process large datasets.

The process includes defining regex patterns for text fields, setting rules for numeric fields (like ensuring phone numbers follow a specific format), and using bulk update operations to apply these standards across the entire database.

This might require custom scripts or applying built-in CRM functionalities designed for data standardization.

4. Segment Data Populations

What this step does: Segmentation divides your CRM data into smaller, manageable groups based on shared characteristics or behaviors. This can range from demographic details to customer interactions with your business.

Why it matters: Segmentation allows for more targeted and effective marketing, sales strategies, and customer service efforts across different customer groups. By understanding the specific needs and behaviors of different groups, you can tailor your approach for higher customer satisfaction.

Results to expect: Enhanced targeting thanks to segmentation leads to improved engagement rates, higher conversion rates, and higher customer satisfaction. It also makes it easier to identify and capitalize on opportunities within specific segments.

How to do it: Use your CRM’s segmentation tools to categorize your data based on predefined criteria, such as industry, purchase history, or interaction frequency. This involves setting up filters and rules within your CRM to automatically classify new and existing records into the correct segments.

The technical details

Segmenting data populations typically involves querying your CRM database using specific criteria to create dynamic lists or segments. This may require a combination of SQL queries for complex segmentation or using software for defining and applying segmentation rules. 

Advanced segmentation might also use machine learning algorithms to identify patterns and segment data accordingly, requiring integration with more sophisticated data analysis tools or services.

5. Score Records

What this step does: Scoring assigns a value to each record based on predefined criteria — this could be anything from potential revenue, likelihood to convert, or even engagement level. Scoring records helps prioritize leads and customers according to their importance or level of interest.

Why it matters: With scoring, sales and marketing teams are able to focus their efforts on the most promising leads and the most valuable customers. You maximize where you invest your resources for greater outcomes and your outreach efforts are more efficient.

Results to expect: Scoring tends to lead to improved conversion rates and more efficient sales cycles, since teams can quickly identify and act on the highest-value opportunities based on their scores. Scoring also leads to more personalized customer engagement strategies.

How to do it: Develop a scoring model based on your business goals and customer data, then apply this model to rate each record in your CRM. This may involve assigning points for certain actions, behaviors, or demographic characteristics.

The technical details

Using record scoring often requires configuring your CRM to automatically assign scores based on the data each record contains. This involves setting up custom fields for score tracking and creating workflows or scripts that calculate scores based on your model. 

For more advanced scoring models, integration with external analytics tools may be necessary to analyze behavior patterns and update scores dynamically.

6. Assign Records

What this step does: This step makes sure you’re able to distribute CRM records to team members based on certain criteria, including location, product specialization, or account size. Record assignment makes sure leads and customers are managed by the most appropriate person or team.

Why it matters: Assigning records correctly ensures the best service to customers and maximizes sales opportunities. In addition to managing workload, it enhances the efficiency of the sales and support teams.

Results to expect: Teams that work with record assignment workflows handle leads and customer inquiries more efficiently, leading to faster response times and higher customer satisfaction rates. Additionally, it makes sure opportunities are pursued by the most qualified and relevant team members, improving sales outcomes.

How to do it: Set up automated assignment rules in your CRM to allocate new and existing records according to your team’s structure and expertise. This may involve routing leads based on geographic territories or assigning customers to account managers based on company size.

The technical details

Configuring record assignment takes using your CRM’s rule-based logic to automatically distribute records. You’ll want to create assignment rules that consider several record attributes and team member capacities. 

More sophisticated applications of record assignment use round-robin algorithms or machine learning to optimize the distribution of records based on performance data or workload balance.

From Enhancing Data To Maintaining Clean Data

By following the steps in Enhance, you set the stage for deeper customer insights, more targeted marketing, and improved GTM strategies.

The key to lasting success is not just in enhancing data but in maintaining its cleanliness and relevance over time — which takes us to our final step, Maintain. 

Dive into our Maintain guide to learn how to automate the data cleansing process to make sure your CRM remains a clean and powerful source of truth for your business.