Reducing Customer Request Backlogs Through Data Unification
Real Story. Making Impact.
A manufacturing dealer network relied on manual workflows for customer requests and service follow-ups. With fragmented data and inconsistent processes, the team struggled to respond quickly and sustain retention outcomes. mindZvue implemented Salesforce Data 360 to unify records, recover ignored data sources, and build a reliable foundation for segmentation and retention-focused activation.
Industry: Manufacturing (Dealer Network)
Built on: Salesforce Data 360
The Challenges
- No defined process to manage and route customer requests, causing delays
- Manual handling created bottlenecks and inconsistent follow-ups
- Customer data fragmented across sources, limiting visibility and insight
- High transaction volume made it hard to unify records and act fast
The Solution
mindZvue implemented Data 360 to unify customer records, remove bottlenecks, and make request handling faster and more consistent.
- Data unification at scale: Implemented Salesforce Data 360 to unify customer records
- High-volume processing: Consolidated 40K–50K records and processed 357K data transactions
- Data recovery: Recovered previously ignored/blocked data sources by removing bottlenecks
- Program roadmap execution: Delivered 4 structured roadmaps across 2 completed projects with 1+ ongoing
- Segmentation foundation: Enabled consistent segmentation to support retention-focused activation
What Changed
This wasn’t just cleanup—it was making customer requests executable with unified profiles.
Before
Manual requests → fragmented data → limited visibility → slow follow-ups → backlogs
After
Unified records → recovered sources → scalable processing → consistent segmentation → faster request handling
Measured outcomes
60%
data
recovery
40%
efficiency improvement in 3 months
4
roadmaps
delivered
357K
data transactions processed
45K
records unified and segmented
Is This Use Case a Fit?
You’ll recognize this if you have:
- Customer requests handled manually with inconsistent follow-ups
- Data spread across systems, limiting service visibility
- High transaction volume that breaks unification efforts
- Backlogs caused by poor routing and unclear ownership
If 2+ apply, download the PDF for the full breakdown and results.
