Configuring your coaching assistant

AI for Sales

Jody Geiger

Co-Founder, AI Sales Studio

From messy text to structured coaching data

$$ Split screen showing raw transcript on left as dense unformatted text, and structured transcript on right with clear speaker labels and color-coded tags

Why structure matters:

Raw transcripts are hard to analyze
Parsing separates speakers and turns
Tags identify coaching moments
Clean data enables sharper insights

Tagging responses for coaching intelligence

Examples

Three discovery questions in a row, tag it as a strength
An objection that is skipped or rushed past, tag it as a coaching opportunity
If the call ends without a clear next step, tag it as a missed closing action

Structured tagging gives the agent the context it needs to evaluate tone, objection handling, and closing effectiveness

Better tags = sharper coaching

Designing your coaching prompt template

Prompt structure:

Instructions: turn this transcript into actionable coaching

Analyze tone, objection handling, discovery quality, and closing effectiveness

Output as two strengths, two improvements, and one key takeaway

Match my coaching style: make it sound <encouraging/direct/analytical>

Interpreting coaching notes with transcript evidence

structured output

Output

Specific, evidence-based, actionable
Acknowledged customer concern directly

Improvements:

Rushed through pricing without pausing
Missed follow-up on budget objection

Takeaway:

Slow down on value moments and confirm understanding before moving forward

Let's practice!

AI for Sales