Call Center Nesting: How to Score and Coach New Hires
A nesting program works when new hires get their own quality bar. Two scorecard models support teams run, and the coaching loop that makes them stick.
A nesting program works when new hires get their own quality bar. Two scorecard models support teams run, and the coaching loop that makes them stick.
Quick answer MaestroQA rebranded to Rippit on 24 February 2026. It was a rebrand, not an acquisition: same company, same team, same product, new name
Deflection rate counts the tickets your AI agent closed, not the ones it closed well. How to audit the deflected population and find the silent failures.
Under peak pressure most teams loosen the standard, which corrupts the data for good. Cut coverage instead, and know which criteria can never move.
A spreadsheet is the right place to start a QA programme and the wrong place to keep it. The five failure signatures, and what to carry across when you move.
A fixed coaching cadence and a variable supply of real problems forces leads to invent feedback. Five better uses of the slot, and how to tell the difference.
High QA scores and unhappy customers usually means one of five things. Check whether the two numbers even describe the same conversations first.
Industry statistics about poor service are useless in a budget meeting. Here is how to calculate what a bad conversation costs you, from your own data.
Peak is the one quality failure you can see coming. The decisions that matter eight weeks out, two weeks out, during the surge, and in the January clean-up.
Your team grew and QA quietly stopped working. What breaks at 10, 30 and 100 agents, the tell for each one, and the single thing to change at each threshold.
Your AI agent closes tickets alone and its worst answers never escalate. How to find out if it is doing damage: what to sample first, and what to score.
Leadership wants support quality expressed in money and you have a percentage. How to convert quality findings into cost, risk, retention and capacity.