Lease-to-own (LTO) has become an important part of how consumers access products they may not be able to purchase outright. Across retail categories, LTO providers function at the intersection of financing, customer relationships, and physical products. 

And that leaves little room for operational mishaps. 

The stakes couldn’t be higher. Operational missteps can immediately threaten an individual or a family’s financial security and daily living. 

And what if systemic misconfiguration allows errors to propagate at machine speed? 

Naturally, running customer operations in an ungoverned setup is a non-starter. 

Our client, Acima, an LTO service provider, understands this better than anyone else. Acima partners with thousands of retailers across the U.S. to deliver affordable leasing options and increase customer purchasing power. 

SFMC gave Acima the orchestration capabilities it needed to manage journeys and campaigns across many locations. The limitation was elsewhere: the data architecture and governance had not evolved at the same pace as the business.

They turned to us for an end-to-end audit and cleanup of their SFMC instance.

80,000 duplicate subscriber records 

As a business grows, its Marketing Cloud account often becomes more complex. New campaigns add Data Extensions, integrations introduce new identifiers, and journeys are built using available data. Different teams may also use different Subscriber Keys.

When email data comes from multiple sources, issues can arise. 

Acima’s portal records included duplicate or invalid addresses, while API-driven sends created additional subscriber records.

Its journeys and workflows in Automation Studio relied heavily on manual processes, while inconsistent Data Extension structures and limited preventive controls made duplication harder to stop. Overlapping targeting also made frequency harder to control. 

“Acima has many locations across different states, and multiple locations could be associated with the same email address,” says Navendu Mehta, one of our Marketing Operations executives who worked on Acima’s account. “If an offer or notice was specifically intended for a location in California, the same email could also be associated with a location in another state. Because the email address was the same for both locations, there was a risk that the communication intended for California could also be sent to the location in the other state,” he adds. 

The scale of the issue made this difficult to manage. In fact, when we took on the project, a single email address could be associated with as many as 5-20 child locations. Because Lease-to-Own operates at the intersection of recurring payments, asset tracking, credit reporting, and legal property rights, duplicate records create immediate financial leakage, regulatory liability, and operational gridlock.

Acima’s system had 80,000 duplicate subscriber records. Their team was also manually removing subscribers every 15 to 30 days to stay within billing limits.

How we approached the problem

The first step was a comprehensive audit across All Subscribers, DEs, Journeys, and Automations. We then standardized Email Address as the unified Subscriber Key, identified records associated with multiple Subscriber Keys, and redesigned recurring journeys and related Data Extensions around consistent relationships.

That changed the role of cleanup.

Now, instead of repeatedly removing records to keep subscriber count under control, we could address the conditions that were creating those records in the first place. 

Backup Data Extensions were created for engagement, bounce, and unsubscribe data, allowing cleanup to happen while preserving important historical information. Governance controls, validation rules, and standardized data-management practices were also introduced to reduce the scope of the same problems returning.

Automation retrained to remove, not create, work

Our team reviewed and optimized its workflows in Automation Studio, restructured journey entry sources to control record injection, and aligned Data Extension relationships and naming conventions. The goal was to make recurring and ad-hoc campaign execution more predictable and scalable. 

Deliverability starts with the database 

Poor-quality addresses can increase bounces. Duplicate or overlapping records can create unnecessary frequency. Weak suppression logic can expose engaged subscribers to too many messages. And gaps in domain or IP configuration can affect inbox placement.

We addressed these areas alongside the data work.

Our team implemented Einstein Send Time Optimization, strengthened deliverability through IP warming, domain alignment, and standardized authentication, and introduced engagement-based segmentation and suppression to improve frequency and targeting. 

Bounce rates declined, duplicate sends were eliminated as a direct result of the data cleanup, and send-time optimization was associated with improved open and click-through rates.

What changed for Acima 

Acima no longer needed recurring manual deletions simply to control billing limits. The unified Subscriber Key structure preserved historical engagement tracking, while the database became more stable and reporting gained a clearer view of subscriber activity.

Campaign execution also became more efficient. Optimized journeys and automations reduced manual effort and improved consistency, lowering the operational risk associated with recurring campaigns.

The work was supported through a dedicated half-time team consisting of a Salesforce Marketing Cloud SME and a Campaign Manager & Developer. That model gave Acima ongoing oversight across data architecture, governance, automation, deliverability, and reporting without requiring a full in-house team.

Platform scale eventually creates a choice for teams in a similar position; keep adding manual fixes around an increasingly complicated system, invest in the architecture and governance that make those fixes less necessary, or some combination of both depending on where the risk is greatest.

Acima chose the latter. The payoff was a more reliable foundation, with better control over subscriber utilization, more accurate engagement visibility, improved campaign efficiency, and a stronger base for continued growth.

Acima and Agentforce

As you are aware, if your SFMC instance is overrun with messy workflows, Agentforce will inherit the same and make decisions you can’t validate and shouldn’t trust. 

In most established environments, the sensible approach is targeted stabilization: 

• Start by mapping the data that actually supports your marketing operations
• Identify the authoritative customer identifier
• Find where duplicate identities have accumulated
• Trace the relationships between Data Extensions, Journeys and Automation Studio
• Then establish which engagement and suppression data needs to survive the cleanup

And this is broadly what we did with Acima. The work gave the team a more stable foundation for what comes next. Acima is now evaluating Agentforce and Marketing Cloud Next, with implementation targeted for early next year. 

“Key initiatives include auditing legacy email templates to map functional complexity into Marketing Cloud Next, alongside scoping Agentforce for potential customer support and service deployment,” says Siddhartha Guha, the dedicated SME supporting Acima.

Considering Agentforce?

What we found at Acima isn’t unique to Acima. SFMC environments that grow quickly tend to accumulate the same shortcuts underneath their workflows: duplicate subscriber records, disconnected DEs, inconsistent keys, undocumented logic, aging or obsolete automations, and reporting that requires someone who knows the account’s history to interpret it.

An agent can only work with the information and permissions available to it. Acima’s environment made that limitation concrete — the same duplication and inconsistent Subscriber Keys that forced manual deletions every 15 to 30 days would have been just as invisible to an agent as they were to standard reporting.

That creates a difficult situation: teams can end up carrying technical debt into an agentic environment, where it becomes agentic debt too.

If you’re considering Agentforce, Guha recommends a very targeted audit first. These are close to the questions we asked when we first audited Acima’s account:

• Have you enforced strict naming conventions across all SFMC assets? 

(Standardize prefixes such as DE_, AUTO_, QUERY_, and EMAIL_, and include the team name, frequency, and purpose.) 

• Have you centralized data retention policies across your Data Extensions? 

(Apply automated retention policies to every Data Extension when it is created, such as clearing records after 30 to 90 days. Unmanaged staging Data Extensions can consume database resources over time.)

• Have you decoupled data from presentation? 

(Keep business logic out of email templates by handling data transformation upstream in Automation Studio through SSJS or SQL Queries rather than relying heavily on inline AMPscript within content blocks.)

• Have you built a modular folder structure for your Marketing Cloud assets?

(Use clear, permission-restricted folder hierarchies for Content Builder, Data Extensions, and Automations instead of allowing teams to accumulate assets in root folders.)

• Are you documenting automated dependencies? 

(Maintain an external matrix or repository that tracks SQL query dependencies, API integration endpoints, and contact deletion rules.)

Mavlers’ Maturity Assessment shows you how your SFMC setup is doing in areas like data, architecture, automation, governance, and campaign operations. We used these same categories with Acima before they moved forward. This way, you can focus on what matters most before things get more complex.

You can take the assessment here.  

Agentforce may eventually change how much of your marketing operation can be automated. The more immediate question is whether your SFMC org is structured well enough for that automation to be trusted.