Case Studies
Real workflows.
Concrete outcomes.
The scenarios below reflect the kinds of automation workflows Sigmoid Analytica designs and delivers: the business problems, the systems involved, and the results that are realistic to expect.
The scenarios below are representative of the types of workflows Sigmoid Analytica designs and delivers. They reflect real business problems and realistic outcomes based on deployment patterns in ecommerce and SaaS support operations. Specific client names and metrics are illustrative.
~71%
Avg ticket automation rate
< 3 min
Avg automated resolution
~90%
Processing error reduction
0
Headcount added for volume
Midsize direct-to-consumer retailer
~71%
tickets automated
< 3 min
automated resolution
Problem
The support team was processing over 3,000 return and exchange requests per month, each requiring a manual policy lookup, order verification, and drafted response. Average handling time was 18–22 minutes per ticket. During peak periods like post-promotion and post-holiday sales, the queue extended to several days, and response inconsistency was a recurring complaint.
What we built
We built a return automation workflow that classifies each inbound request, retrieves the customer's order and applies the applicable return policy rules, generates a return label or issues the refund via Shopify where eligible, and sends a response built from the retailer's own policy language. Out-of-policy cases and high-value returns queue for agent review with a fully prepared brief.
Approximately 71% of return requests now resolve without agent involvement. Automated resolution time dropped to under 3 minutes for eligible cases. The support team redirected time previously spent on routine returns toward escalations, exchanges requiring judgment, and proactive outreach.
Mid-market B2B SaaS platform
< 12 min
first response time
~2×
agent capacity increase
Problem
Customer success and support teams handled approximately 1,800 tickets per month. A significant portion involved billing queries, plan change requests, and cancellation requests, each requiring the agent to retrieve the account record, check contract terms and billing status, and draft a contextually accurate response. The volume was manageable but consuming; it left little time for proactive account work.
What we built
We implemented a triage and response system that classifies each ticket on arrival, retrieves the account record and relevant contract terms from the CRM, and drafts an accurate response or routes to the right team. Cancellation requests trigger a configurable retention workflow. Billing queries below a defined threshold resolve automatically; those above queue for review.
First response time dropped from an average of 4 hours to under 12 minutes. Agent capacity effectively increased without adding headcount. The retention workflow consistently applied offer logic that had previously been applied only when agents remembered to check the ruleset.
High-volume marketplace seller
< 3 min
processing time
~90%
manual error reduction
Problem
Operations staff were manually processing order amendments (address changes, item substitutions, and pre-dispatch holds) across two warehouse systems and a third-party logistics provider. Errors were frequent when changes arrived close to the dispatch cutoff window. A single address correction could take 20 minutes and require coordination across three platforms and two teams.
What we built
We built an amendment workflow that receives inbound change requests, checks real-time dispatch status across the connected fulfilment systems, applies the correct logic for each fulfilment partner, executes the change in the appropriate platform, and confirms the update to the customer and internal team. Requests that fall outside the valid amendment window surface as structured escalations rather than silent failures.
Amendment processing errors dropped substantially. Average processing time fell from approximately 20 minutes to under 3 minutes for automated cases. Staff time previously spent on order amendments was redirected to exception management and supplier coordination.
A note on outcomes
Automation rates and resolution time improvements vary based on workflow complexity, the consistency of your existing policy documentation, and the accessibility of your integration environment. We scope every engagement with these variables in mind. Before any commitment, we provide an honest assessment of what is realistic for your specific workflows, not a projected maximum from a best-case deployment.
Want to see what's realistic for your workflows?
We'll assess the fit before any commitment, and tell you what automation rate is realistic for your specific processes.