---
title: How Upstack Used Arovy to Create a Shared Salesforce Language Across 34 Acquired Companies -  - Arovy
description: Learn how Upstack used Arovy to align Salesforce definitions across a fast-growing business, support self-service, and strengthen reporting consistency. -  - Arovy
image: https://www.arovy.com/hubfs/upstack.jpg
---

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3 MIN READ

# How Upstack Used Arovy to Create a Shared Salesforce Language Across 34 Acquired Companies

![How Upstack Used Arovy to Create a Shared Salesforce Language Across 34 Acquired Companies](https://www.arovy.com/hubfs/upstack.jpg)

<https://twitter.com/intent/tweet?url=https%3A%2F%2Fwww.arovy.com%2Fcase-studies%2Fhow-upstack-used-arovy-to-standardize-salesforce-definitions-across-a-fast-growing-business> <https://www.linkedin.com/shareArticle?mini=true&url=https%3A%2F%2Fwww.arovy.com%2Fcase-studies%2Fhow-upstack-used-arovy-to-standardize-salesforce-definitions-across-a-fast-growing-business> <https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Fwww.arovy.com%2Fcase-studies%2Fhow-upstack-used-arovy-to-standardize-salesforce-definitions-across-a-fast-growing-business>

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With 34 acquisitions, each bringing its own Salesforce terminology, UPSTACK needed a unified language for a full Salesforce reimplementation. Previous attempts to manage definitions in Excel created trust issues between teams and executives, so UPSTACK turned to Arovy’s Data Dictionary to create a more consistent business language, improve trust in reporting, and support future AI initiatives.

### **The Challenge**

At UPSTACK, the challenge was not just documentation. It was alignment.

As the business grew through acquisition, different teams were using the same terms in different ways. Even simple terms like 'customer' could mean different things across the organization. That created confusion in reporting, made leadership alignment harder, and increased the risk of drawing the wrong conclusions from the data.

UPSTACK was about to conduct a full Salesforce reimplementation, which meant the business needed a cleaner, more consistent way to define and use data across the new environment.

Excel had already shown its limits. Earlier dictionary efforts became outdated quickly, and once people saw inaccurate information, trust dropped. For a fast-changing Salesforce environment, static documentation was not enough.

<iframe data-hsv-src="https://play.hubspotvideo.com/v/6636061/id/194326477923" referrerpolicy="origin" sandbox="allow-forms allow-scripts allow-same-origin allow-popups" allow="autoplay; fullscreen;" style="position: absolute !important; width: 100% !important; height: 100% !important; left: 0; top: 0; border: 0 none; pointer-events: initial" title="HubSpot Video" loading="lazy" data-hsv-id="194326477923" data-hsv-style="" data-hsv-width="1920" data-hsv-height="1080" data-hsv-autoplay="false" data-hsv-loop="false" data-hsv-muted="false" data-hsv-hidden-controls="false" data-hsv-full-width="false"></iframe>

\- Kylie Powell - VP, Business Systems & Data at UPSTACK

### **Why a Data Dictionary Mattered**

For UPSTACK, the need for a data dictionary was tied directly to business consistency.

The team needed a central place to define terms, standardize field usage, and make sure different teams like finance, sales, and customer support were pulling from the same source of truth. Without that shared language, reporting discrepancies and interpretation issues were bound to continue.

The Salesforce reimplementation created the right opportunity to fix that. Instead of trying to clean things up later, UPSTACK could build with shared definitions from the start.

### **The Arovy Solution**

UPSTACK implemented Arovy’s Data Dictionary as part of its greenfield Salesforce build.

That gave the team a centralized, system-connected place to manage definitions and create consistency across the business. Rather than relying on spreadsheets that quickly went stale, teams had a reference point tied more closely to the live Salesforce environment.

That change mattered immediately. The data dictionary gave teams a clearer way to define fields, standardize terminology, and resolve disagreements around how business terms should be used. Instead of revisiting the same debates repeatedly, UPSTACK had a shared reference point aligned with leadership.

 *"Even simple terms like ‘customer’ meant different things to different teams. Every time someone tried to dispute how we should use a term, I just send them the data dictionary.  Now that this is our source of truth of how we use these terms, it shuts down those discussions pretty quickly.”  
Kylie Powell - VP, Business Systems & Data*

### **Adoption Across the Business**

The value of the data dictionary extended well beyond documentation.

UPSTACK rolled it out early, even while some definitions were still being refined, so end users could start using it as a maintained, centralized resource. That helped drive adoption sooner and gave teams a stable place to go when questions came up.

Engineering became one of the earliest adopter groups. Developers used the data dictionary as a self-service resource to understand which fields to use in the systems and workflows they were building. That reduced the risk of developing against outdated or unused fields and made the work easier to support across teams.

### **Governance That Kept It Useful**

To keep the dictionary current, UPSTACK built governance into the process.

The team established a weekly cadence across data operations, change management, and data quality stakeholders to review changes in the org, confirm ownership, and keep definitions up to date. The data dictionary was also distributed alongside Salesforce release notes, helping make it part of the company’s regular operating rhythm rather than a one-time documentation project.

### **A Foundation for AI Initiatives**

As UPSTACK looked ahead to AI, the value of consistent terminology became even more important.

A shared data dictionary made it easier to extend business definitions into outside tools and models, helping ensure those systems used terms the same way UPSTACK did internally. That gave the company a stronger foundation for AI initiatives built on consistent business language, not conflicting interpretations.

### **The Impact**

For UPSTACK, Arovy’s Data Dictionary became more than a documentation tool.

It helped establish a shared Salesforce language after 34 acquisitions, improved trust in reporting, reduced friction between teams, supported self-service for end users and developers, and made governance easier to maintain over time.

Most importantly, it gave the business a clearer source of truth for how data should be defined and used as UPSTACK scaled and took on AI initiatives.

## Related Posts

Explore our recent articles.

<https://www.arovy.com/resources/blog/how-arovy-customers-automate-their-salesforce-data-dictionary>

![](https://www.arovy.com/hubfs/customer%20data%20dictionary%20webinar%20blog%20recap.jpg)

### How Arovy Customers Automate Their Salesforce Data Dictionary

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<https://www.arovy.com/resources/other/webinar-recording-how-arovy-customers-automate-their-salesforce-data-dictionary>

![](https://www.arovy.com/hubfs/How%20to%20automate%20your%20salesforce%20data%20dictionary..png)

### Webinar Recording | How Arovy Customers Automate their Salesforce Data Dictionary

 Watch customers share the steps to build an automated Salesforce data dictionary—less manual work,...

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