Dashboard מלא בdata = dashboard לא משתמשים בו. הנה מה שלמדנו על עיצוב dashboards שעובד.

הבעיה – Everything Dashboards

Bad pattern: 20 widgets on one screen. Numbers, charts, tables, lists.

Result: cognitive overload. Users close it after first look.

הגישה – Job to be Done

שאלה: למה המשתמש פותח את ה-dashboard?

Answers: (1) check if all OK, (2) find anomalies, (3) make a decision.

עיצבו לתשובות אלה. לא לshow-off דאטה.

Hierarchy – Above the Fold

Top of screen: 2-4 numbers שהמשתמש הכי חשוב לו.

Below: trends, breakdowns.

Bottom: raw data, tables.

User יראה top במבט אחד. Rest אם צריך.

Numbers vs Charts

Single number: ‘MRR: $42,300’. Simple, memorable.

Number with change: ‘MRR: $42,300 (+5.2% MoM)’. Context.

Sparkline: mini trend chart next to number. Direction visible.

Full chart: only if user needs to compare periods or investigate.

Charts – When

Line chart: trends over time. Best for time series.

Bar chart: comparing categories. Best for discrete data.

Pie chart: only for 2-3 items showing composition. Otherwise use bars.

Heatmap: intensity across two dimensions.

Table: exact numbers matter, comparison of many attributes.

Empty States

New user just signed up – dashboard empty.

Bad: ‘0’ everywhere. Depressing.

Good: sample data with ‘demo mode’ badge. Show what dashboard looks like when populated.

Better: interactive tutorial guiding to first data point.

Filters and Time Ranges

Default: last 30 days (usually right for most).

Prominent: last 7d, 30d, 90d, custom.

Compare periods: ‘vs previous period’ toggle.

Filters: powerful but hidden until needed.

Actionable Insights

Not just showing data – suggesting actions.

‘Churn spiked in the last week. 3 customers cancelled. See who.’

‘MRR growing 5%/week. On track to hit annual goal.’

AI/algorithms detect anomalies and highlight them.

Personalization

Different users care about different things.

Sales: pipeline, deals closed.

Support: tickets open, response time.

Product: feature usage, active users.

Custom dashboards or role-based views.

Real-time vs Cached

Not everything needs real-time.

Business metrics (MRR, users): daily/hourly cache is fine.

Operations (uptime, current requests): real-time critical.

Balance: user expectation vs infrastructure cost.

Mobile Consideration

Users check dashboards on phone too.

Priority: top 4 numbers, most critical charts.

Full details: link to specific report.

Not everything from desktop translates – be selective.

Tools

Metabase: open source, easy to use. Great for internal.

Tableau, Looker: enterprise BI.

Custom (React + Recharts): for embedded dashboards in product.

Grafana: infrastructure/operational dashboards.

מבוסס על פרויקטים אמיתיים

המדריך הזה מבוסס על עבודה עם:

• Platforma365
• Podd

קריאה נוספת

אם המדריך הזה עזר לכם, אולי תרצו לקרוא גם על עיצוב UX/UI – המדריך המקיף שלנו לתחום.