How to Improve Data Quality in RevOps with HubSpot's AI Tools

Imagine a familiar situation: your sales team is spending hours correcting duplicate or incomplete contact records in the CRM. While they're caught up in these manual tasks, valuable opportunities slip through the cracks and sales forecasts become about as reliable as a weather forecast without data.

This isn't just an efficiency problem; it's a tangible drain on revenue and a major hindrance to growth. According to a Gartner study, poor data quality can lead to a 27% loss of revenue. Dirty, outdated, or fragmented data is the biggest enemy of Revenue Operations (RevOps), the discipline that aligns marketing, sales, and service teams.

Fortunately, we no longer have to rely on long days of manual cleanup. HubSpot' s Artificial Intelligence (AI) is transforming data management in RevOps, and here's how.

The Diagnosis: Why Does Data Fail in RevOps?

To understand how AI can help, we first need to identify the fundamental problems. Poor data quality is a systemic problem that comes in many forms, often invisible until it's too late.

• Duplicate or fragmented data: The same contact or company appears in multiple records without a unified history, leading to confusion and duplicated efforts.
• Empty mandatory fields: Critical fields like "industry," "company size," or "lead source" are left blank, making proper segmentation, personalization, and performance measurement difficult.
• Lack of standardization: Data entries are not consistent. Sometimes it is written "Mexico", sometimes "MX"; one position may be "Director of Sales" and another "VP of Sales". This complicates filtering and analysis.

Without clean, consistent data, it is nearly impossible to reliably forecast sales, effectively align marketing and sales teams, and make strategic decisions based on accurate information. In RevOps, data quality is not a luxury, it's the foundation of everything.

HubSpot's AI Tools to Rescue Your Data

HubSpot has integrated AI directly into its platform to proactively address these challenges. These tools work like an invisible data cleansing team working 24/7.

Automatic deduplication with AI

HubSpot uses machine learning algorithms to identify and merge duplicate contact and company records, even when the information is not 100% identical. For example, if you have two contacts, one named "John Smith" with the email "juan.perez@empresa.com" and another as "John P." with the email "j.perez@empresa.com," the AI can recognize that they are the same person and suggest merging.

Here's what HubSpot's data cleansing dashboard looks like, where you can manage and approve the AI's suggestions:

Real-time data enrichment

HubSpot's AI automatically enriches your contacts' and companies' information. When someone registers on a form, the tool searches for public data such as industry, company size, job title and LinkedIn profile, and adds it to your record. This not only saves you time, but also ensures that your sales team always has up-to-date and relevant information to personalize their interactions.

Proactive Inconsistency Alerts

Imagine having an assistant that alerts you when something isn't right. HubSpot's AI does just that. You can set up rules to automatically notify you when a lead enters the system without "source" information or when a critical record is missing a required field. These alerts allow your teams to fix problems on the spot, before they become a systemic error.

Case Study: B2B SaaS optimizes its RevOps with HubSpot AI

A B2B SaaS company specializing in project management tools was struggling with inconsistent data. Its sales and marketing teams complained that the information was unreliable, leading to inaccurate sales forecasts and significant wasted time.

Before: 15% of sales reports contained errors, and reps were spending up to 5 hours a week on manual clean-up tasks. This directly affected forecast accuracy.

After: They implemented HubSpot's AI tools. In just three months, the results were astounding:

• They reduced duplicate records by 40% in an automated way.
• Sales forecasts reached 95% accuracy, thanks to the quality of the data.
• Time spent on data cleansing was reduced by 75%, allowing the sales team to focus on what really matters: selling.

Quick Guide: The 3 steps to get started with AI.

1. Audit your data: Use HubSpot's data quality dashboard to detect issues that may be affecting your data. This tool provides a clear view of duplicate records, incomplete fields, and other inconsistencies that need attention.
2. Set up automation rules: Set up workflows and automation rules for the most important fields. For example, if a new contact comes in without an assigned industry, you can automate the process for AI to complete or for your sales team to receive an alert.
3. Train your team: It's critical that your marketing and sales teams understand the importance of keeping data clean and how to interact with AI suggestions to ensure your database is always in tip-top shape.

Data is the fuel of RevOps: with AI, it will no longer be 'adulterated gasoline'.

The era of tedious, manual data management is over. HubSpot's AI isn't just a tool; it's a strategic ally that ensures your RevOps engine runs on the cleanest, most powerful fuel possible.

Want your data to work for you (and not the other way around)? At Digitalegy, we’re experts in implementing HubSpot AI for RevOps teams. Book a call and let’s discuss how we can optimize your data quality and fuel your growth. Get started with us today  🚀😎