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Dashboard Examples
Looker Studio, Tableau, PowerBi, Domo, Looker, Grow
You want fancy?
→ As you will see in the chapters below, most clients opt for finding their most pressing business questions and then finding answers instantly instead of spending money on pretty dashboards ;). But this is possible in Tableau, e.g., and I have built this design with client data before. Domo is more limited in its fancy design. Looker Studio sits in the middle of both. The most critical driver for deciding which visualization tool to use should always be which business questions you need to answer and how much data volume will be pumped for that.
But what about PowerBI, Looker, AgencyAnalytics...
... Apache Superset, Dash, Grow, Chart, Google Sheets, Excel, QlikSense, Sisense, ThoughtSpot, Metabase, GoodData, Klipfolio, ... and the other 50 tools on the market?
They all work fairly similarly from a data engineer and a visualization expert’s perspective:
We gather user stories, define dimensions and metrics, apply best-practice chart types, and consult on design. The real difference lies less in what we build and more in the ecosystem the tool plugs into.
It often boils down to preference. For Microsoft-heavy enterprises, PowerBI integrates naturally, though we’ve seen use cases where Tableau was the preferred choice. Outside the Microsoft bubble, it tends to be a less cost-effective, less flexible option. Looker Studio is the best free tool on the market, with some surprisingly strong features, but it quickly hits limits with governance and data scale. Open-source and all-in-one platforms can look attractive, but they increase lock-in risks, which is especially critical for regulated industries like healthcare and wellness e-commerce.
At LazyAnalyst, we have worked with many of them and concluded that even with new players on the market all the time, the tools that consistently deliver reliable results across our client base are Looker Studio for e-commerce businesses up to $3M gross annual revenue, Tableau for $3-20M, and Domo for anybody above that.
Sales Performance
What’s our revenue year over year and month over month?
Domo version
Executive Summary
Year-to-date revenue is $130.4K, which is 195.8% higher than last year, a very strong year-over-year growth. Monthly revenue trends show that while some months outperform last year significantly, there are still dips in certain periods.
For the current month, revenue is $26.4K so far, which is down 10.5% compared to last month. Daily revenue trends show that while cumulative growth continues steadily, day-to-day revenue has been a bit weaker than the prior month.
Recommendations
How well does our sales team do?
Tableau version
Executive Summary
The sales team made 120 outbound calls in July, down 22% from the previous period, but nearly every call connected (98% contact rate). This led to 118 live conversations, with a 30% close rate, slightly down compared to before. In total, 36 deals were closed, but that’s 20% fewer than last time and only 44% of the monthly goal (100 sales).
Performance by rep shows clear differences: Jasmine is a star performer, making more calls and closing at a strong 39% rate in June, while Caleb makes fewer calls and closes at a lower rate (~6–7%). The coaching matrix places Jasmine in the top-right quadrant (high effort + high success), while Caleb falls in the low effort + low success quadrant, signaling the need for coaching and support.
Recommendations
How well did each event perform?
Looker Studio version
→ How is our event performance increasing over time?
→ How well are we converting event attendees?
Executive Summary
Event performance has been mixed across the year. Revenue peaked in June 2022 at $166K, with both strong attendance and conversion. Other months delivered significantly less ($6K–$38K). Attendee rates remain high, with 92% attendance in March and 74% in September, showing strong event engagement. Conversion from attendees to sales, however, has declined over time: 34% in March vs. 28% in June and 33% in September. The interview-to-sales conversion also dipped from 90% in March to 65% in September, suggesting reduced effectiveness in later events.
Recommendations
Are we hitting our sales call targets?
Looker Studio version
Executive Summary
Between Sept 1–20, 2022, the team made 192 calls, which led to 34 meaningful conversations and 13 new bookings. That’s a call conversion rate of 18% and a booking conversion rate of 38%. On average, reps are making 5.6 calls per hour, generating about 1 conversation per hour. While calls and conversations are happening, very few are translating into verified or confirmed bookings, and no sales have been closed yet.
From Typeform submissions, 19 total forms were completed, with 17 qualified (89%), showing strong lead quality. However, almost none progressed into booked sessions or sales. Paid Typeforms contributed the majority of leads, while organic Typeforms had fewer completions but a slightly higher qualification rate.
Recommendations
How do our two bestselling products fare across the regions?
Tableau version
Executive Summary
Neither of the two bestselling products - Turmeric Chai Latte and Cacao & Cardamom - consistently hits the weekly sales target of 12 units in any region. The strongest performance is in Greater London, where both products sell above average compared to other regions, followed by the South West and Scotland. Other regions like Wales, East Midlands, and Yorkshire & Humber show much lower sales volumes.
Overall, sales are spread thin across regions, with no standout market consistently driving the highest volumes.
Recommendations
Where do we sell the most?
Tableau version
Executive Summary
Sales are concentrated heavily in a few key states, led by New York ($1.29M) and New Jersey ($782K). Other notable states include Florida, California, Ohio, and Pennsylvania, but their sales volumes are much smaller in comparison.
At the city level, Brooklyn, NY alone generates $732K, making it the single biggest city contributor. Other strong cities include Lakewood, NJ and Monsey, NY, though their totals are far lower. Many other states and cities contribute only small amounts, showing a sharp concentration of sales in the Northeast.
Recommendations
What’s our sales trend among all products?
Tableau version
Executive Summary
Sales have grown steadily from 2008 through 2017, with peaks in later years. The overall trend shows a consistent upward trajectory, though there are noticeable seasonal spikes, likely tied to specific campaigns or seasonal demand.
Breaking sales down by product category, a few categories (such as Category1, Category2, and Category3) show consistent sales momentum over the years, while others have more sporadic or declining activity. This suggests that while the portfolio overall is healthy, not every product is contributing equally to growth.
Recommendations
What’s our average order value over time?
Domo version
Executive Summary
The average order value over the tracked months is $19.75 overall. AOV peaked between Nov and Jan at around $24–$26 per order, before declining sharply by March. Customer counts follow a similar seasonal trend, with the largest number of customers in December, which coincides with the highest spending per order.
This indicates that holiday or seasonal peaks (Nov–Dec) not only bring in more customers but also higher-value orders, while early spring sees both order volume and value decline.
Recommendations
Paid Ads Performance
What is our live monthly ad budget pacing?
Looker Studio version
Executive Summary
Ad spend is far behind planned pacing. Against a monthly budget of £30,000, only £1,420 has been spent so far (5%), leaving £28,580 unspent. The daily spend target was £1,071, but the actual daily spend is averaging only £68, putting pacing at -94% behind plan.
Looking at the current month’s budget in dollars, the situation is inverted: $8,215 budgeted, with $1,474 already spent (118%), leaving the campaign overspent by $1,515. Average daily pacing is more than 1,100% above plan, signaling a mismatch between planned and actual campaign delivery.
Recommendations
How much engagement are our campaigns driving?
Looker Studio version
→ Are our campaigns converting?
Executive Summary
Campaigns generated 29,231 impressions with a cost per thousand (CPM) of £49. This resulted in 251 clicks, giving a click-through rate of 1%, which is on the lower side for typical ad benchmarks.
However, despite impressions and clicks, no conversions were recorded. This means cost per conversion, conversion value, and return on ad spend (ROAS) all remain at zero. The campaigns are not currently generating measurable sales or leads.
Recommendations
What are our best and worst performing campaigns?
Looker Studio version
Executive Summary
The Facebook ad campaigns for Centre Open From 12th April are performing well based on click-through rate.
Recommendations
Which of our video ads performed best across all KPIs?
Tableau version
Executive Summary
Among the top 20 videos ranked by minutes watched, the clear leader is “ImiFMab4-eY” with 1,164 minutes watched and over 6,000 views, making it the strongest performer overall. Other notable videos include nvGxwMkZKnk (429 minutes, 10,068 views) and pWrquJV2G3G (415 minutes, 9,391 views).
Engagement quality varies: while some videos attract high views, their watch duration per view stays short (~1 minute average). Playlist activity also highlights which videos are being saved for rewatching: “a2otfuakFVQ” and “tla3ditC0dA” had thousands of playlist adds, signaling strong long-term interest.
Recommendations
Subscription Performance
What are our net subscriptions this month?
Looker Studio version
→ Have we improved subscriptions over the last 90 days?
→ When do people typically cancel in their cycle?
Executive Summary
For October 2020, there were 578 new sales and 577 cancellations, leaving net subscriptions flat for the month. Subscription sales generated £141,387, up 72.7% from last year, contributing to a YTD total of £2M.
Membership levels currently sit at 16,763, down 20.7% year-over-year, with about 4,501 accounts frozen. On average, customers stay subscribed for 18.3 months, and cancellations show noticeable spikes mid-month. Average yield per customer in the last 30 days is £19.75.
Recommendations
When do customers cancel in their lifecycle?
Domo version
Executive Summary
Most cancellations happen very early in the customer lifecycle. The highest spikes occur within the first few days after joining, with over 100 cancellations on day 1 alone. A second noticeable peak appears around day 20–30, before tapering off gradually over the following months.
This suggests that cancellations are clustered at the very start of a subscription (possibly linked to trial periods or onboarding issues) and again shortly after the first billing cycle. After that, cancellations continue but at much lower, steadier levels.
Recommendations
What’s our net subscription change?
Domo version
Executive Summary
Net subscriptions increased by 231 during the period shown. The green bars indicate new subscriptions, while the red bars represent cancellations. The black line shows the overall net growth — starting small in early January 2019, spiking around mid-January with a surge in sign-ups, and then steadily climbing through February.
Although cancellations continue throughout the period, the volume of new sign-ups consistently outpaces them, keeping the overall trend positive.
Recommendations
How quickly do our cohorts repurchase with us?
Domo version
Executive Summary
This chart shows how quickly different customer cohorts (by first purchase month) return for repeat orders. Most cohorts repurchase within 20–30 days after their first order. For example:
Overall, the earlier cohorts repurchased more frequently and consistently than the later ones.
Recommendations
What’s our cohort retention rate? How quickly does each cohort re-order?
Domo version
Executive Summary
This chart shows how many customers from each monthly cohort return to make another purchase, and how quickly they do so.
Overall, retention is relatively steady but not high, with about one-third of customers repurchasing within two months.
Recommendations
Which cohorts stay subscribed longer? What’s the drop-off rate?
Domo version
Executive Summary
This table shows how long customers from each starting month stay subscribed and when they drop off.
Overall, most cohorts lose half their subscribers by 60 days, with only the stronger months (Nov-Dec 2018) showing meaningful retention past 90 days.
Recommendations
Funnel Performance
How is our funnel performing?
Looker Studio version
→ Did we increase top and/or bottom of the funnel in the last month?
Executive Summary
This page shows how well your sales funnel is moving leads through each stage: from new leads to paying customers.
Recommendations
Customer LTV & Retention
Which channels are driving LTV and retention?
Looker Studio version
Executive Summary
Retention this month sits at 9%, down 7% compared to last month, with 9K returning users (a -15.9% drop). Overall traffic also declined slightly (-5.8%), showing both fewer total users and fewer repeat visits.
When it comes to channels, Organic Search is the clear leader, bringing in nearly half of all users (47%) and driving the highest revenue overall ($24B). Direct traffic ranks second with $7B in revenue, while Paid Search delivers fewer users (10K) but very high value per user ($350K each, $3B total). Social, referral, and affiliates contribute smaller shares with lower revenue per user.
Recommendations
Who is churning in which order?
Tableau version
Executive Summary
Most of our customers are churning quickly, around 89–95% drop-off each quarter across the years shown. Only a small portion reactivate, and even fewer are retained consistently from one period to the next. For example, in Q1, while 17,990 customers churned, only 534 were retained and 301 reactivated. The pattern is consistent across years: churn dominates, retention is small, and reactivation is even smaller.
Recommendations
What does LTV look like per discount that brought our customers in?
Domo version
Executive Summary
Customer lifetime value varies significantly depending on the discount that brought them in. Customers who used no discount code or specific product coupons (Product-B, Product-C) delivered the highest LTV, averaging up to $100+ per customer. In contrast, deep discounts like 50JAVA or FREESHIPPING produce very low or even negative LTV (around -$15 to -$40). This shows that not all promotions attract valuable customers. Some drive one-time bargain hunters who don’t return.
Recommendations
What does the LTV look like for our different cohorts?
Executive Summary
Customer lifetime value varies depending on when a customer first joined. Cohorts from mid-2018 show relatively stable LTV, ranging from $41 to $52 after 6 months, with September 2018 being the strongest cohort ($52). Later cohorts (end of 2018 into early 2019) brought in more customers overall, but their LTV growth is more modest over the same timeframes. This suggests that while acquisition volume increased, the average quality or spend per customer may have dropped slightly.
Recommendations
Product Performance
→ What is our repeat purchase timing?
→ Which products are bought in the same cart?
Promote or bundle these products to increase average order value.
→ Which products are typically bought in the next order?
Include these products in post-purchase flows to drive customer lifetime value.
What’s our product sentiment on Amazon?
Tableau version
→ How’s the sentiment trend developing over time?
Executive Summary
This dashboard shows how customers feel about your products on Amazon based on reviews.
Recommendations
What do customers say about our product?
Tableau version
Executive Summary
This word cloud highlights the most common themes customers mention in reviews.
Recommendations
RFM Analysis
Executive Summary
Our top customers are those who buy often, spend significantly, and have purchased recently. A handful stand out, spending between $4K–$9K with 40-60+ purchases each. At the other end, we see customers who buy often but spend very little, and a group of once-valuable customers who haven’t purchased in over 1.5 years (churned best customers).
The RFM scores show:
Recommendations
Email Performance
How do our Klaviyo email campaigns perform in improving our onboarding process?
Looker Studio & Domo version
→ Is our Klaviyo event tracking set up properly?
Executive Overview
Recommendations
Looker Studio
Domo
Customer Segmentation Analysis
Tableau version
What is the age and gender of our audience?
Executive Summary
Our audience is primarily young adult men (ages 25–34), with the strongest viewership in India and the US. While engagement is high, we’re also seeing notable subscriber losses in the US and Indonesia, signaling areas to review our content strategy.
Recommendations
We should tailor more content toward young adult male interests while testing localized campaigns for India and the US to deepen engagement. At the same time, reviewing the types of videos causing drop-offs in the US and Indonesia can help us adjust tone, format, or frequency to reduce churn. Expanding female-targeted or younger audience content could also diversify our reach and open new growth opportunities.
Who are our most profitable customers?
Executive Summary
Our most profitable customers are repeat buyers, with a handful generating significantly higher profit than the rest. The darker and larger blocks on the chart highlight these “VIP” customers who not only spend more but also order more frequently. The list below shows the top repeat customers by profit, with most of them being male.
Recommendations
We should consider building a loyalty or exclusive perks program to strengthen retention with these high-value customers. At the same time, identifying patterns in what these customers buy and how often they purchase can help us design marketing campaigns to grow more customers like them. Finally, outreach from sales or customer success could ensure these top customers feel valued and remain loyal.
Which of our products are more loved by male/female customers?
Executive Summary
Our product preferences differ noticeably by gender. Female customers show a clear favorite in Category 2, which strongly dominates their purchases. Male customers, in contrast, spread their purchases more evenly, with Categories 6, 10, and 4 being their top choices. Overall sales per customer are similar between genders, but the split by product category highlights important differences in buying behavior.
Recommendations
We should double down on Category 2 with female-focused marketing, bundles, or loyalty campaigns to further grow that strong preference. For male customers, positioning a “top 3 favorites” package or tailored cross-selling strategy could increase basket size. Finally, using these insights to refine product messaging, promotions, and segmentation can help us maximize sales by gender-specific appeal.
Customer Support Performance
Are we hitting our support KPIs?
Tableau version
Executive Overview
Support volume is healthy, with 429 conversations in the observed period, of which 427 are closed and only 2 remain open. Most customers (393) only needed one interaction, and repeat contacts are rare (14 chatted twice, 3 chatted 3–5 times). Average replies per case are 10, which suggests conversations sometimes require lengthy back-and-forth.
Recommendation
Customer support is resolving issues promptly, but efficiency could improve by reducing the number of replies needed per case. Invest in clearer first responses (templates, knowledge base links) and proactive communication to cut down conversation length. This will improve both agent productivity and customer satisfaction.
Professional Services Performance
Are we on target in our projects?
Looker Studio version
Executive Overview
Professional Services projects show an 82% remaining budget across fixed fee engagements, with 465 hours logged out of 2,531 total. Most projects are operating under blended rates, which allows for flexible resource allocation and billing. While this indicates good control over budget utilization, the relatively low percentage of hours logged suggests that project delivery is either early-stage or delayed in execution pacing.
Recommendations
Which projects are costing us the most time?
Looker Studio version
→ Are project efforts aligned with our original estimates?
Executive Overview
Customer support handled 429 conversations, with 427 successfully closed and only 2 left open. Most customers (393) needed just one chat to resolve their issue, while a small number required repeat follow-ups. The team averaged 10 replies per case, suggesting that while issues are generally resolved, some require extended back-and-forth.
Recommendations
How do our services score?
Tableau version
→ What’s the feedback we’re receiving?
→ Did we encounter any outliers in the team?
Executive Overview
The service score sits at 48, trailing behind peers with mixed results across criteria. Some strengths show up in Criteria 1, 5, and 8 (all scoring above 60), but weaknesses are evident in Criteria 3 and 4, pulling the overall score down. The trend shows slight improvement over time (from 43 in Q2 to 55 in Q4), though the overall slope remains modest at 18%. The boxplot highlights wide variation across criteria, with multiple outliers, suggesting inconsistent service quality within the team.
Recommendations
Focus efforts on the weaker service elements, particularly Criteria 3 and 4, to lift the baseline. Outlier analysis should be prioritized: teams with extremely low scores need targeted coaching, while consistently strong performers can share best practices. Finally, embed a quarterly review process to reduce variability across criteria and improve overall stability in service delivery.
Are we meeting our monthly work pacing per project?
Looker Studio version
Executive Overview
The retainer projects are under-pacing this month. Against a budget of 1,064 hours, only 799 hours have been logged (75%), leaving 265 hours (25%) unused. The pacing is currently at –13%, meaning the team is behind schedule in meeting the allocated workload. Some projects (e.g., Campaign Ops, Marketing Automation) are trending closer to expectations, but others are significantly under-utilized, pulling down overall pacing.
Recommendations
What are our average turnaround times for specific tasks and who is outperforming those?
Tableau version
Executive Overview
Turnaround times vary significantly across task types. Management Information production tasks take the largest share of time (around 25%), followed by root cause analysis (22%) and Management Information design (24%). Rule review and amendments are quicker at 11%. Performance outliers are evident, with some individuals completing tasks much faster or slower than the team average. This uneven spread suggests both efficiency opportunities and potential bottlenecks.
Recommendations
HR Performance
Have we hired according to our nationality diversity rules?
Tableau version
→ Which of our departments has the highest hiring needs?
Executive Overview
Hiring peaked in 2016 (63 hires) and has since declined to 48 in 2018. Diversity goals show room for improvement, as the majority of hires are from the United States, with smaller representation from Australia, Singapore, China, France, and Russia. Faculty roles dominate across Elementary, Middle, and High Schools (83% in Middle and High), while Support and Administrative roles are limited. Job titles are heavily weighted toward Teachers (50%), with the next largest group being Instructional Assistants (13%).
Recommendations
How well are we doing on male versus female diversity?
Tableau version
Executive Overview
The organization shows a clear gender imbalance across different levels and roles, with female staff heavily concentrated in Elementary School, Instructional Assistant, and Support roles, while male staff are more visible in departments such as Science, Math, and Community Sports/Activities. High School faculty and some grade levels display a closer gender balance, but overall staffing still leans female. When looking at job titles, Teachers and Instructional Assistants are predominantly female, whereas IT Support Engineers and Baseball Coaches skew male. A few departments, including Learning Support and Counseling, display near parity, but the overall trend highlights traditional gender clustering in both instructional and non-instructional roles.
Recommendations
Statistical Analysis
Hotel Risk vs. Customer Satisfaction Matrix
Tableau version
Executive Overview
The portfolio of properties is distributed across four risk quadrants, with several high-risk outliers.
Hostal Blanes La Barca and Hostel Mon Vie fall in the “Delist” quadrant, combining both high risk and high customer dissatisfaction, making them critical concerns. A cluster of properties, including Ocean View Motel, Prince Myshkin, and Alicante Hostal, sit close to the delist threshold and may warrant proactive intervention.
On the other side, properties such as BLC Design Hotel and Burj Al Arab appear in the “Low Risk” quadrant with low risk scores and relatively strong or neutral customer satisfaction. Some, like Amazon Clipper Premium and Cultural House, score poorly on risk while showing mixed customer sentiment, placing them in the “Monitor” category.
The overall distribution suggests a small number of urgent problem properties dragging portfolio performance, while most assets cluster in low-to-moderate risk zones.
Recommendations
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