106 terms from CRM and Lifecycle, each defined in a sentence or two, with a link to the calculator that works the number out where one exists.
Items left unpaid. The highest-return automated flow in most stores.
Everyone who arrived in the same period. The base unit of honest retention analysis.
The share of new customers who reached first value.
The share of customers who refer someone else.
A message when a wanted item returns. Very high intent, very little effort.
Grouping by what people did rather than who they are.
The specific action that fires it.
Someone viewed products and left without adding anything.
Customers grouped by the campaign that won them.
Customers grouped by where they came from. Reveals which channel buys worse customers.
Open the calculator →Someone started paying and stopped.
Forecasting who is about to leave, usually from falling usage.
How likely a given account is to go. Useful only if someone acts on it.
Clicks divided by opens. More reliable than open rate, because it measures what happened after.
A group defined by when they joined.
The rules governing how often and through which channels you may reach someone.
The system holding your customer records and the history of every interaction.
A sequence offering adjacent products.
Likelihood of buying an adjacent product.
Short for click-to-open rate.
The moment they get that result. Weak activation shows up as churn months later.
Open the calculator →Customers bringing other customers. The cheapest acquisition that exists.
Growing revenue from an existing account.
A composite read on how likely an account is to stay and grow.
The whole arc from first contact to churn or advocacy.
Getting a new customer to their first real result.
Waking up someone dormant but not formally gone.
The full term, and the discipline as much as the software.
Bringing back someone who already left.
The share of sends that reached a mailbox at all.
Opens divided by delivered. Badly inflated since privacy protection started prefetching images.
How actively someone uses or interacts with you.
The opening order. Usually the least profitable one after acquisition cost.
Open the calculator →The specific action that counts as having got value.
Deciding how often to contact someone before it costs more than it earns.
A group defined by how often they buy.
A suppression list applied across every campaign, no exceptions.
Retention before any expansion revenue is counted. Cannot exceed one hundred percent.
Revenue kept from existing customers, ignoring expansion.
Permanent failures, usually dead addresses.
The share that landed in the inbox rather than spam. Different from delivery rate, and far more useful.
A read on how close someone is to a purchase decision.
A group defined by which stage they are in.
Where someone sits in that arc right now.
A trigger tied to a stage change rather than a single action.
Retention counted in customers rather than money.
A group defined by total spend.
Retention including upgrades. Can exceed one hundred percent even while customers leave.
The single most valuable thing to do with this customer right now.
The same idea applied to what to sell them.
The share who finished setup. Drop-off here predicts churn better than most health scores.
Changing content by who is looking. Effective when it uses real signals, irritating when it just inserts a first name.
Messages after an order, covering delivery, use and the next purchase.
A message when a watched item gets cheaper.
Customers grouped by what they first bought. Often the strongest predictor of lifetime value.
Open the calculator →A message trying to sell something.
A modelled probability of any given behaviour.
The same, viewed from the sales side.
The typical gap between orders. Once you know it, you know when someone is late.
Likelihood of buying in a defined window.
The share that produced a tap through to content.
The share of push notifications opened.
How long after the usual interval you treat someone as lapsed.
A group defined by how long since they last acted.
The system choosing what to show each person.
Asking a customer to bring someone else.
Projected renewal revenue for a period.
The odds a given contract renews, usually from health scoring.
The share of contracts up for renewal that renewed.
Money from renewals rather than new business.
Any order after the first.
The period within which a repeat counts as normal rather than a reactivation.
A cohort tracked by money rather than headcount.
Retention counted in money. Different answer whenever your largest accounts behave differently from your smallest.
Asking for a review at the point the customer is happiest.
Grouping by recency, frequency and monetary value. Simple, and it beats most complicated models.
Choosing when to send per person rather than per campaign.
Clicks divided by messages delivered.
The share who stopped messages. Higher tolerance than email, and higher cost per lost contact.
Temporary failures such as a full inbox.
The share who marked it as spam. Above a fraction of a percent and deliverability starts falling.
The stages of an email or SMS subscriber, from signup to fatigue.
Contacts excluded from sending, whether opted out or already customers.
How long from signup or first visit to buying.
The gap that matters most, because the second order is where lifetime value starts.
Open the calculator →How long before a new customer gets something useful. Shorter is worth real money.
A message triggered by an action such as an order confirmation. Different consent rules, and much higher engagement.
Any message fired by behaviour rather than by schedule.
Opens counted once per person.
The share who opted out. A cost of every send, and worth pricing.
A sequence offering a higher tier.
Likelihood of taking a higher tier.
The first sequence after signup. Usually earns more per recipient than anything else you send.
A sequence aimed at lapsed customers.
The share of lapsed customers a campaign brought back.