Boosting Data Accuracy Without Overwhelming Your CRM and GTM Teams
As businesses look to take advantage of AI across the GTM space, the old adage of “garbage in, garbage out” comes to mind. To get the most of your investment in AI, focus on your foundation: your data quality. Manual maintenance/brute force is always an option but never the scalable one. In this guide, we’ll dive into automated solutions and best practices for improving and maintaining CRM data quality over time. This post will focus on 3 areas but any key object needs attention: Accounts, Contacts and Opportunities.
Account Data
Quick wins:
Minimize or eliminate new duplicate accounts by mapping all possible entry points (uploads, integrations, marketing, events) and implementing preventative measures.
Use tools like Datagroomr, Cloudingo, DemandTools to build algorithms to dedupe your existing account table.
Leverage enrichment tools to update and validate company information (check out tools like Clay, ZoomInfo and Apollo)
Processes
Create workflows that flag accounts with incomplete or outdated information based on your specific criteria. Clay has a great way to maintain data on a regular cadence.
Incorporate your data providers into marketing form fills and event lists. When a registrant fills out a form, utilize webhooks to enrich the data on the way in to the CRM.
Standardize key fields modified to your business - group employee counts, adjust Industry categorization to match your segmentation. This could leverage standard values such as NAICS/SIC but you could also leverage AI to read through how the company describes itself and categorize based on your instructions.
Contact Data
Quick Wins
Use email verification tools (Unbounce, Zerobounce, etc.) to confirm contacts are still viable.
Enhance contact records with LinkedIn profile links, enabling teams to find recent updates quickly. Clay can further leverage this data for call prep and prospecting emails.
Differentiate fields for direct dial phone numbers vs mobile vs company switchboard. I’ve seen direct dial numbers get overwritten too many times. Using direct dial and mobile numbers will increase your connect rates.
Processes
Similar to the Account enrichment, leverage tools to automatically enrich data on the way in to your CRM. Get job titles, emails, phone numbers, etc automatically. Tools like Upcell.io, ZoomInfo and Apollo can provide contact data. Identify which sources have the best quality. If you serve a niche area, the big players may not be a great resource. The random company you’ve never heard of emailing you to sell you a list? It’s not good.
If you have a decent sized customer base, use tools like UserGems to track when they change jobs.
Build a regular cadence to refresh and validate key personas.
Standardize groupings of your contacts into key personas/roles. Roll those values up to the Account level so you can understand if you have any gaps in your contact database. You can easily identify what data you need to acquire by account. I consider this the sniper approach to contact acquisition rather than broad searches in tools like ZoomInfo or Apollo.
Opportunity Data
Quick wins
Ensure you have key fields identified by stage that you require. Be realistic about the number and depth of updates you want to require. If you are requiring 5+ fields per stage, you need to reduce that.
Automate stage progression based on key field inputs. For example, once a deal secures both business and technical wins, it should move past the Demonstrate Value stage.
Make sure your activity is being tracked automatically. Manual logging of activities is a recipe for poor forecasting insights. Review your current sales tech stack and see if there are tools that have the capability.
Processes
Try leveraging tools like Weflow, Scratchpad and others that can take your call recordings and update key fields.
Nail down how you’re incorporating your sales methodology into your sales stages. Reinforcing the methodology through your sales process is a key step in building adoption of new sales training.
Trim the required information on the deal down to the most important information and remove the fluff. Keep in mind the downstream team needs: SEs who need info from discovery and CS for why did they buy - current state and desired future state.
Automate key metric tracking items such as the # of times a deal was pushed.
Other steps
Tech debt is an ongoing challenge for RevOps teams. Fields are created for short-term needs, duplicate fields are created accidentally and they are stale or not used. FieldTrip can tell you how complete a field is as a % of the total records (ie: 100% of your accounts have a Name, 72% have domain).
Build out your data dictionary. Define the fields, what they’re used for, reference any workflows that are dependent. You can use tools like Sonar to help with this as well.
Key points
It’s not hard to make big strides in data quality, but it takes effort. Make sure you’re spending your time on the highest value activities.
Assess - where do you currently have data quality issues? Are any impacting your ability to target effectively and creating drag in your sales motion? Target those areas first.
Tools - decide early on if you’re a best-in-breed or all-in-one solution company. There are tradeoffs with each so be sure to acknowledge what you gain/lose from your choice.
Capacity - be sure to allocate a certain amount of time on a regular basis to monitor and adjust any of the steps in your processes to improve. Don’t wait until it’s a big problem that’s caused lost trust in your stakeholders.
Measuring success of data programs
Be sure to understand the impact your efforts produce. Here are just a few things you can measure to show how well you’ve improved:
Duplicates in CRM (lower is better)
Field completion rates of key fields (higher is better)
Bounced email rates (lower is better)
Forecast accuracy (closer to 100% in Week 3 or 5 is better)
Wrapping things up
Improving your CRM accuracy is a key step in being able to leverage AI across the organization. It will also allow you to better prioritize where your teams are spending their time from targeting the right accounts to calling the right people to working opportunities with a higher propensity to close. A strong data foundation is critical for organizations striving for high performance. Start with quick wins in each area and build toward more comprehensive, scalable solutions.