Surge

A week in which an account's contact or ticket volume exceeds a stated multiple of its own trailing median. Read as a product problem when several accounts share a category, or an account at risk when one account surges alone.

DefinitionA week in which an account's contact or ticket volume exceeds a stated multiple of its own trailing median. Read as a product problem when several accounts share a category, or an account at risk when one account surges alone.

Own baseline

A global threshold flags large accounts always and small ones never. Each account against its own history.

Paired with silence

An account whose volume went to zero is the other half of the signal.

How it is computed

A week in which an account's ticket or contact volume exceeds a stated multiple of its own trailing median.

Example

An account with a median of 2 tickets a week raised 11. Nine are in one category. It renews in ten weeks.

Where it goes wrong

Thresholds set on absolute volume, which flags large accounts every week and never the small one in trouble.

Articles that use this term

AI and self-service analytics

A weekly sales digest worth reading: what a good one looks like, line by line

An annotated example of a weekly sales digest built from computed tables: the header that states the period and the checks, ten movements each with the measure, the level, the change, the threshold and the citation, the three lists that follow, untouched, slipped and dormant, the line that says what did not move, and the footer with the definition version. What each element is for, and the version of the same digest that nobody reads.

16 Sept 20263 min read AI and self-service analytics

Account health score: why a computed score beats a colour-coded one

What is wrong with the red-amber-green account health field most CRMs carry, what a computed health score is made of, five inputs from the ledger and the CRM with stated weights, how the weights are set from the company's own churn history rather than opinion, why the score is shown with its inputs and never alone, the identity that every account has one score from the same rule, and how the score is validated against what happened.

16 Sept 20263 min read Data quality and reconciliation

Baseline and norm: what this account usually does, and what accounts like it do

The difference between a baseline, an account's own typical level from its own history, and a norm, what similar accounts do when the relationship is full, why the two answer different questions, has this account changed and how far is it from where it could be, which measures use which, surge and dormancy against baseline, gap and share against norm, the case where an account is at its baseline and far from the norm, and the rule that both are stated on the line that uses them.

16 Sept 20263 min read Forecast and pipeline · Customer service

Contact volume per account against its own baseline: the surge list

How a customer service leader turns the ticket export into a weekly list of accounts whose contact volume has jumped against their own history, why the account's own baseline beats a global threshold, the surge score, and the two readings every surge has: a product problem or an account about to leave.

16 Sept 20262 min read Coverage and territory

Dormancy by industry: order cadence from weekly to annual, and the threshold that follows

A dormant account is one silent beyond a multiple of its own cadence, and the cadence runs from twice a week to once a year depending on the desk. This hub sets out, for twelve industries, the typical cadence, what silence looks like in that industry's data, the threshold that follows, the run rate that values the account, and the seasonal trap in each, with the full guide for each desk.

16 Sept 20263 min read Board and management reporting · Customer service

First contact resolution per account: the customers who have to call twice

How a customer service leader measures repeat contact per account from the ticket export: tickets reopened or re-raised on the same issue within a stated window, the accounts whose repeat rate is well above the base, the categories where repeats cluster, and why an account-level repeat rate is a churn signal the team average cannot show.

16 Sept 20262 min read