Sample analysis · Illustrative · Synthetic data · Fictional house · No real client data
ML

Maison Lumière · Boutique Team Intelligence Sample

0 client advisors · 6 boutiques · engagement, collaboration with head office, assessed competencies, selling styles, product knowledge · use the filters to change the view

EVA.ai · Workforce Decision Intelligence
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people in view 0 of 0

How to read this example. Filters explore a prepared synthetic snapshot. Recommendations, targets and timings are proposals to review, not measured outcomes or included delivery commitments. Self and manager ratings are assessment perspectives; access and visibility are agreed for each engagement.

What was measured

Five conversations with every client advisor, held by EVA in their own language over three weeks, plus one assessment pass by each boutique manager. Nothing was filled in on a form; everything keeps its reasoning in the workspace.

01
Engagement

30 questions across 8 themes, scored 1 to 10, plus one overall score for "my boutique".

02
Collaboration with head office

Boutiques rate 5 head-office departments on 4 statements; the departments rate the boutiques back.

03
Assessed competencies

9 selling competencies, self-rated 1 to 4, assessed separately by the boutique manager, with access set by the client’s role permissions, plus the 3 each advisor wants to grow.

04
Selling style

20 factual statements about how each advisor actually sells, placed on two axes: transactional to relational, new clients to existing clients.

05
Product knowledge

Short quizzes per category, scored 0 to 10, so training goes where the gap is.

Key results at a glance

·
engagement, average of 8 themes (out of 10)
·
weakest engagement theme
·
weakest boutique-to-head-office relationship
·
of self-ratings sit a full level above the manager's assessment
·
dominant selling style
·
lowest product-knowledge category (out of 10)

Three decisions this analysis puts on the table

Computed from the people in view. Each one names an owner and a 90-day test.

CHART 1 · THE HERO

Engagement, theme by theme, boutique by boutique

Example questions (1 = not at all, 10 = yes, absolutely): Are you motivated when you go to work in the morning? · Are your boutique leaders good at resolving problems? · Does the clienteling system help you do your job well? · Do you consider working hours are distributed fairly? · The leaders of the country keep me informed about what is going on. · I trust this house to be fair to everyone.
8.5 to 107.5 to 8.46.5 to 7.45.5 to 6.4under 5.5
SECTION 2

Collaboration between the boutiques and head office

The four statements (1 = do not agree, 10 = fully agree): I am satisfied with the day-to-day collaboration with this department · Exchanges are always cordial and productive · This department is effective at helping me solve issues · My requests are answered on time.
SECTION 3

Assessed competencies: what advisors say, what managers confirm

Scale: 1 Novice · 2 Practitioner · 3 Advanced · 4 Expert. Employees, managers, HR and other authorised viewers can see individual assessments according to the role permissions EVA and Customer Success configure for the client and use case.

Self-rating versus manager assessment, average per competency

SelfManager assessed

The three competencies advisors most want to grow

Share of advisors in view who named each competency among their three.

Manager-assessed level by boutique

SECTION 4

Selling styles: how each boutique actually sells

Example statements (agree or disagree): You dine with clients at least once a month · You use messaging apps daily with clients · You prefer developing an existing client to finding a new one · You are comfortable handling after-sales with a client you meet for the first time · You have made a home visit to a client in the last quarter.

Every advisor in view, placed by style

Hunter: new clients, transactionalConnector: new clients, relationalCloser: existing clients, transactionalConfidant: existing clients, relational

Style mix by boutique

SECTION 5

Product knowledge by category

Example: a short quiz per category, five questions, in the advisor's language, scored 0 to 10. Which house introduced the first water-resistant case, and in what decade? What is the name of the stitching technique used on the signature bag?
8.5 to 107.5 to 8.46.5 to 7.45.5 to 6.4under 5.5
SECTION 6

One advisor, one page

One possible individual view, using synthetic advisor profiles. EVA and Customer Success configure access for employees, managers, HR and other authorised viewers according to each client’s wishes and use case.

NEXT 90 DAYS

From the analysis to the decisions

Weeks 1 to 4

Fix the loudest signal

  • The weakest engagement theme in the weakest boutique gets a named owner and a visible change within 30 days.
  • The worst boutique-to-head-office pair meets in person, with the four statements on the table.
  • Each advisor's three chosen competencies go into their development plan as written.
Weeks 5 to 8

Train where the gap is

  • Product training rebuilt by category and boutique from the quiz results, not from the catalogue.
  • Manager-assessed levels drive who coaches whom inside each boutique.
  • Style mix used to plan the floor: a Hunter on the door, a Confidant on the top-client appointments.
Weeks 9 to 12

Measure again

  • Re-run the engagement conversation only; six questions, ten minutes.
  • Re-ask the collaboration statements for the pair that was fixed.
  • Match the style and competency profiles of the top performers against the recruiting brief for the next hires.

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