FINDING 01·CRM administrators, customer service teams, sales ops·2 sources
Duplicate records created by manual/direct CRM data entry
When customer service reps or automated workflows enter data directly into the CRM (e.g., via Outlook or email-based pipelines), duplicates proliferate because there is no reliable deduplication at the point of entry. This makes the data unusable for reporting and customer service. Evidence spans 2013 and 2026, suggesting this is a persistent, long-standing pain.
Source
“This last method creates lots of duplicates and makes it imposible to use this data for better customer service and reporting.”
Source
“I am building an AI automation service for a client using a workflow automation platform. The goal is to automate lead management by processing incoming emails, extracting customer information with an LLM, saving the data to a CRM, and automatically sending a personalized follow-up email... Check whether the customer already exists in the CRM.”
FINDING 02·CRM administrators, data engineers, operations teams·1 source
Fragmented multi-source data integration causing quality degradation
Organizations pulling data from multiple systems (e.g., purchase data from one platform, subscription data from another, plus manual CRM entries) struggle to maintain data quality when merging these sources. The deduplication and quality checks applied to automated feeds are absent for manually entered data, creating a two-tier data quality problem.
Source
“We bring these two database together and merge it in to one and then using thirdparty service, push it in to the CRM. (we process these data that's de-dups rows, checks for data quality etc) PROBLEM start when the third type of data gets entered in by customer service.”
FINDING 03·B2B SaaS sales teams, sales operations leaders·1 source
CRM data siloed from AI workflows, leading to inconsistent and low-quality outputs
Sales teams using AI tools (e.g., ChatGPT) operate without a live connection to CRM data or standardized processes, resulting in generic, inconsistent outputs and no measurable productivity gains. The CRM remains a passive data store rather than an active part of AI-driven workflows.
Source
“Individual reps copy-pasting prospect info into ChatGPT, writing their own prompts, getting generic outputs. Some reps loved it, some ignored it. No consistency, no shared context, no connection to our CRM or our actual sales processes. Very little productivity gains.”
FINDING 04·B2B sales teams, sales managers·2 sources
No systematic follow-up on stale or 'Closed Lost' CRM deals
B2B sales teams leave thousands of closed-lost deals untouched in the CRM, even though many become re-engageable over time due to budget changes, personnel moves, or competitor failures. The CRM itself provides no mechanism to surface these opportunities, forcing reps to rely on generic prospecting lists instead.
Source
“I spent years watching B2B sales teams treat 'Closed Lost' as a graveyard. Thousands of deals sitting in CRM, never touched again. But here's the thing – most of those deals aren't actually dead. They're just badly timed.”
Source
“The same prospect who said 'not now' 8 months ago might be ready today – but nobody's systematically tracking this. Meanwhile, reps burn hours chasing net-new leads from the same generic ZoomInfo lists everyone else has.”