Why serviceMob
If your analytics were working, you would have fewer contacts.
You would know how many customer experiences you had last week, which issues cause repeat contacts, what they cost and what to fix first. Most enterprises cannot answer those questions. That is the problem serviceMob exists to solve.
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R² 0.981
AMPRx to CSAT and NPS
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R² 0.0699
Average Handle Time to CSAT. It explains 7%.
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100%
of experiences measured. Surveys sample about 5%.
The Franken-Stack
You have the best tools in the world. Why does contact demand never change?
| Point tools in the stack | Suites and add-ons | Consultancies | serviceMob | |
|---|---|---|---|---|
| What it models | Its own outputs: contacts, cases, tickets, surveys, QA scores | The same outputs in one vendor's schema | Assessments of the outputs | The experience the outputs add up to, across every system |
| Who does the work | Your administrators | Your administrators and an implementation partner | Their consultants, for the length of the project | Forward Deployed teams that ship with the software and stay |
| What you pay for | Seats | Seats and modules | Hours | The engagement, metered by the platform |
| What moves | Handle time and dashboards | Handle time and dashboards | A roadmap | Contact demand, gross margin, churn and cost to serve |
The metric problem
Average Handle Time explains 7% of satisfaction.
Customer service runs on metrics designed to optimize handling. AHT measures how long a call lasted. CSAT captures perception from about 5% of interactions. FCR measures ticket closure, and never sees the customer who came back through another channel. None of them explains why demand exists.
-
R² 0.981
AMPRx to CSAT and NPS
Average Minutes Per Resolved Experience, measured on 100% of behavior
-
R² 0.0699
Average Handle Time to CSAT
Explains 7% of satisfaction
The missing infrastructure
Experience metrics require an experience model.
You cannot measure CPRx or AMPRx without first modeling what a resolved experience looks like, across every channel, every contact reason and every resolution path. That is why most platforms cannot do what serviceMob does. They measure contacts. We model experiences.
serviceMob builds a prescriptive data ontology for each client: a structured framework that maps every customer experience across point of view, channel and phase, down to component, actor and resolution. Every interaction is modeled as an experience object. Where a value does not exist, the ontology exposes a NULL, and the NULLs reveal the structural data gaps the business cannot see. NULLs are not missing data. NULLs are the deployment plan.
How we deploy
Strategy, operationalize, transform, deliver.
Every engagement runs the same arc. Strategy: set the priorities from the customer's perspective and model the experience and the demand it creates. Operationalize: put the Brain in front of the teams that cause and handle demand, with governance over performance management, data, technology and process. Transform: move the business units that cause contacts. Delivery: deliver, measure, iterate and optimize to reduce customer effort, mitigate churn and improve gross margin.
The entry point is a proof engagement on a single portfolio, 12 to 16 weeks, scoped to your numbers and ending in a quantified business case. The evidence comes before the commitment.
Questions
What people ask when they compare.
Do we have to replace our contact center tools?
No. serviceMob is technology agnostic and sits on top of any stack: CCaaS, CRM, WFM, QA, ticketing, case management, bots, speech analytics and homegrown tools. Every one of them produces an output. The Brain ingests them as inputs.
How is this different from a BI layer on top of our data?
A BI layer reports the outputs you already have, faster. The Brain models the experience those outputs belong to, computes the metrics that predict satisfaction and demand, and tags each issue to the business unit that caused it. The difference is the ontology, and the Forward Deployed team that builds it from your data.
What do you need from us to start?
Two exports: your ticket or case data and your WFM forecast. A working session shows the delta between what your contact metrics say and what your experience metrics reveal.
Ready to measure what matters?
Bring two exports to a working session: your ticket or case data and your WFM forecast. We will show the delta between what your contact metrics say and what your experience metrics reveal.