What Does a Business Analyst Actually Do Every Day?

Business Analyst — Typical Day:

9:00 AM — Daily standup (15 min)
9:15 AM — Emails, Slack, ticket triage
9:30 AM — Review KPIs & dashboards for anomalies
11:00 AM — Stakeholder meeting 1 (requirements)
12:00 PM — Stakeholder meeting 2 (status / prioritisation)
1:00 PM — Lunch
2:00 PM — SQL queries for the new analysis request
3:30 PM — Update dashboard in Power BI / Tableau
4:30 PM — Ad-hoc questions from product or ops
5:00 PM — Write up findings + summary email
6:00 PM — Plan tomorrow's priorities
6:30 PM — Log off

End-of-Day Checklist:
□ Did I answer every stakeholder question I promised?
□ Are my requirement notes up to date in Confluence?
□ Is the dashboard published / refreshed?
□ Did I document any data quality issues?
□ Is tomorrow's calendar blocked for deep work?
□ Did I write down tomorrow's top 3 priorities?

Standup update — template:

Yesterday:
  - Completed churn analysis for Q4
  - Shared dashboard update with product

Today:
  - Start requirement gathering for checkout flow
  - Build funnel query for marketing

Blockers:
  - Waiting on data access for the orders table
  - Need confirmation on the KPI definition for "active user"

Priority triage — how to decide:

P1 — Blocking someone else's work OR C-level asks
P2 — Time-sensitive stakeholder request (deadline this week)
P3 — Ongoing analysis / dashboard improvement
P4 — Nice-to-have, exploratory work

Rule of thumb: no more than ONE P1 at a time.
If you have more than 3 asks, escalate to your manager
to negotiate priorities rather than silently dropping work.

-- Typical afternoon query: weekly active users
-- by acquisition channel
SELECT
    DATE_TRUNC('week', u.signup_date) AS week,
    u.acquisition_channel,
    COUNT(DISTINCT CASE
        WHEN a.event_date >= u.signup_date
         AND a.event_date <  u.signup_date + INTERVAL '7 day'
        THEN a.user_id
    END) AS wau
FROM users u
LEFT JOIN app_events a ON a.user_id = u.user_id
WHERE u.signup_date >= CURRENT_DATE - INTERVAL '12 week'
GROUP BY 1, 2
ORDER BY 1 DESC, 3 DESC;

User story — checkout flow example:

As a returning customer,
I want to see my saved payment methods on checkout,
So that I don't have to re-enter card details each time.

Acceptance criteria:
- Saved cards appear above "add new card" option
- Only cards used in the last 24 months are shown
- Users can delete a saved card from checkout
- If no saved cards exist, section is hidden

→ This is what a BA produces — not just "improve checkout".

Validation checklist before sharing numbers:

□ Does the total row equal the sum of the parts?
□ Do the numbers match finance / ops dashboards?
□ Are nulls handled explicitly, not silently?
□ Are dates in the right timezone?
□ Did I check a known edge case (e.g. refunded orders)?
□ Do I know what "active user" means here — and is it
  the same definition the stakeholder expects?

If any answer is "no", don't ship the number yet.

Analysis Summary — template:

1. Question
   Why did checkout conversion drop from 4.2% to 3.1%
   between Oct 1 and Oct 20?

2. Method
   Segmented conversion by device, payment method, and
   region. Cross-checked with web analytics.

3. Finding
   The drop is almost entirely on Android (down 38%).
   iOS conversion is flat. Correlation with the Oct 12
   app release.

4. Recommendation
   Roll back the Oct 12 Android release and re-test.
   Investigate the payment SDK version bumped in that release.

5. Next steps
   Eng: rollback plan due Wed. Me: re-run analysis post-rollback.

Weekly status email — template:

Subject: [BA Update] Checkout analysis — week of Oct 14

Status: 🟢 On track

Shipped:
- Delivered checkout drop analysis (Android-specific, correlated with Oct 12 release)
- Refreshed weekly acquisition dashboard

In progress:
- Requirement gathering for saved payment methods
- Waiting on data access for orders table (blocker)

Decisions needed:
- Confirm rollback of Oct 12 Android release
  (need decision by Thu EOD to land before weekend traffic)

Next week:
- Post-rollback analysis
- Ship v1 of saved-cards requirement doc

Meeting notes — template:

Date: Oct 15, 2026
Attendees: BA, PM, Eng lead, Marketing lead

Decisions:
1. Rollback Android release on Oct 16 (owner: Eng lead)
2. Postpone saved-cards feature to next sprint
3. Use existing "active user" definition; revisit in Q1

Open questions:
- Which payment SDK version was in the Oct 12 release? (Eng)

Next meeting: Oct 22, 10:00 AM

-- Simple check BA runs most days: last 7 days revenue
SELECT
    DATE(order_date) AS day,
    SUM(revenue) AS revenue,
    COUNT(*) AS orders
FROM orders
WHERE order_date >= CURRENT_DATE - INTERVAL '7 day'
GROUP BY 1
ORDER BY 1;

Excel / Sheets — most-used formulas for BAs:

=VLOOKUP(A2, Master!A:C, 3, FALSE)   // look up a value
=SUMIFS(D:D, B:B, "India", C:C, ">2025-01-01")
=IFERROR(C2/B2, 0)                    // safe division
=COUNTIF(E:E, "Churn")                // count category
=PIVOT TABLE → group by channel, sum revenue
=CONDITIONAL FORMATTING → highlight outliers

Jira ticket — BA style:

Type:    Story
Title:   Saved payment methods on checkout
Epic:    Checkout v2

Description:
As a returning customer,
I want to see saved payment methods,
So that I don't have to re-enter card details.

Acceptance Criteria:
- Saved cards appear above "add new card"
- Only cards used in last 24 months
- Users can delete a saved card from checkout

Attachments: checkout-flow-v3.png
Linked:     DATA-142 (schema changes required)