My Dashboard #1- Case Study: Analyzing Customer Churn in Power BI

Ron Markley
9 min readOct 17, 2023
My #1 Power BI Dashboard

Welcome back!
We’re on dashboard 1 out of 100 in this adventure. But a quick detour — let’s talk about my learning process.

My Learning Process

Traditional step-by-step guides? Yeah, for me they feel like they’re penned in Martian doodles.

So, what’s my strategy? Dive deep. I’m the kind of person who digs a hole, willingly jumps in, and then figures out how to climb back out. I’m all about diving straight into the fray, navigating through challenges as they pop up. It’s a journey of raw, thrill-packed problem-solving. And now? My rope is DataCamp. But, instead of merely skimming through standard lessons, I jazzed things up a bit. I took one of their sleek dashboards, deconstructed it, and then challenged myself to reconstruct it. Think of it as tackling a complex puzzle.

Picking My First Battle

For my first ride, I settled on the Databel dataset from DataCamp’s “Case Study: Analyzing Customer Churn in Power BI”.

Why? Because it was clean, no need for data scrubbing. Sure, the pros always go on about ‘cleaning up data makes up 80% of the work,’ but, I’ll admit — I’m not quite there yet.”

Let’s Get Ready to Rumble

Reading Metadata

"Big thanks to DataCamp for supplying this dataset description!”

“Metadata from the Case Study: Analyzing Customer Churn in Power BI on DataCamp.”

Now, let me dive into the data that’s catching my attention. We might just have a suspect on our hands.

“Churn: The Business Buzzword for Bye-Byes”

“Churn”? It’s when folks wave goodbye to one service and jump ship to another. You’ll hear this word buzzing around businesses a lot, especially with those monthly subscription things like phone plans or those binge-watch streaming sites.

Here’s the DAX

Case Study: Analyzing Customer Churn in Power BI

Churn Rate(%)

Dealing with churns on their own? Kinda tricky for most of us. And let’s be honest, not all of us are walking calculators. That’s why I came up with the ‘Churn Rate’. It changes those raw numbers into percentages, giving us a straight-up view of how massive this churn situation is.

Here’s the DAX

Case Study: Analyzing Customer Churn in Power BI

“Financial Impact of Churn: Counting the Real Cost”

Remembering an old boss of mine, every report was a novel episode. If it was full of figures without the dollar impact, he’d say, ‘Are we running a charity?’ To him, every cent painted a picture.

Reflecting on it, he had a point. In the business realm, it’s not just the departing customers that matter, but the dollars that depart with them. Hence, focusing on ‘Lost Revenue Due to Churn’ is crucial.

The catch? Merely looking at churn percentages can be misleading. It’s like seeing a jigsaw piece and guessing the whole picture. My boss believed, ‘While numbers might play hide-and-seek, the revenue story is always crystal clear.’”

Here’s the DAX

Case Study: Analyzing Customer Churn in Power BI
Case Study: Analyzing Customer Churn in Power BI

Check out the evidence I’ve uncovered

While seniors show a churn rate of 38.5%, they account for only 5.98% of our revenue loss. On the flip side, the 30–65 age bracket, with a churn rate of 24.5%, is hitting our pockets harder, causing a 9.76% dip in revenue. That’s almost twice the blow!

Case Study: Analyzing Customer Churn in Power BI

Shifting gears from churn and financial metrics, let’s dive into the world of customer demographics.

Understanding Customer Demographics

Age: Unpacking Phone Habits Across Generations

Age and phone habits? As closely related as peanut butter and jelly. The teens? Glued to their screens so much, I wonder if they even blink. And the wise old owls, 65 and above? Picture my grandma, squinting at her phone, trying to figure out how to mute that talk-back voice.

And the evidence, as the chart shows…

Case Study: Analyzing Customer Churn in Power BI

Spotting a pattern? The Over 30. Their data downloads are slowing down, like they’ve just spotted a speed camera.

For clarity in our analysis, I’ve categorized our customers into three distinct groups: below 30, 30–65, and seniors.

Here’s the DAX

And then delve deeper. Okay, check out the chart.

Case Study: Analyzing Customer Churn in Power BI

“The seniors? They’re throwing cash around as if they’re bankrolling their grandchildren’s shopping sprees — doling out 41% more in extra fees compared to the 30–65 group.”

And, hold on, a staggering 78% of our seniors have signed up for the Unlimited Data Plan.

Case Study: Analyzing Customer Churn in Power BI

Given these insights, I’ve got this niggling feeling in my gut that our pillar of wisdom might be hitting a few snags with our product.

Time to get our detective hats on and find out!

Our unlimited plan? More like an unlimited churn rate!

“Unlimited plan? Ha! More like the Unlimited ‘Bye-Bye’ plan!
If customers feel like they’re just tossing their cash into a black hole or getting slapped with charges for bytes they never bit into, trust me, they’ll be speed-dating other service providers in a heartbeat.

Need some juicy evidence?
Well, folks on the unlimited data plan are shelling out bigger bucks annually, but are they downloading more? Nope. It’s like paying for a buffet and just eating the salad. Crazy, right?

Case Study: Analyzing Customer Churn in Power BI

And hold onto your mugs because here’s the hot tea: a whopping 80.35% of our Unlimited Data Plan users are eyeing the exit.

“The reason? I guess most of them on the unlimited plan aren’t even making the most of their download allowance!”

Case Study: Analyzing Customer Churn in Power BI

So, across the board, no matter the age, the ‘Unlimited’ seems to be the highway to ‘Churn City’.

Case Study: Analyzing Customer Churn in Power BI

Next, let’s play with the call plan!

Are Calls the Culprit Behind the Churn?

Going off what the charts are showing, it looks like most folks aren’t really vibing with the internal call plan. Guess it’s not the big reason they’re jumping ship!

Case Study: Analyzing Customer Churn in Power BI

Month-to-month users? Well, their bags are packed and they’re ready to go

Okay, real talk: I’m that guy always on the prowl for a juicier deal. If I’m coasting on a month-to-month and some other telecom superstar flashes a sparklier offer, why stay loyal?

This is the exact drama we need to unravel. What’s up with contract types and our disappearing customer act? The data’s spilling all the secrets.

Just take a gander at that donut chart — see that big chunk? That’s our month-to-month folks heading for the door way faster than the long-term contract crew.

Case Study: Analyzing Customer Churn in Power BI

So, what kind of sorcery are our competitors using to woo our dear customers away? Alright, let’s whip out our magnifying glasses and zoom in on the churn reason!

Only 5 Calls, Then It’s Sayonara

On my detective trail to solve the riddle of our disappearing customers, I zeroed in on the usual suspect: Competitors. Though, to be honest, I’m still piecing together that puzzle.

Case Study: Analyzing Customer Churn in Power BI

But hold onto your hats because the second biggest culprit is… drum roll, please… our own support team’s attitude! Yep, you heard it right. Our customers’ feedback? It’s louder and clearer than my alarm on a Monday morning!

This got me thinking: how’s our customer service team doing? And guess what I found? If a customer calls up to five times, it’s basically ‘Sayonara’ for them! (For those not in the know, ‘Sayonara’ means goodbye in Japanese.)

Case Study: Analyzing Customer Churn in Power BI

Really makes you wonder, right? If I didn’t know any better, I’d think they’re teaching them the secret art of sushi making over the phone by the fifth call!

State: The California Statistics Shenanigans

Every state has its own internet pace. Some stroll, some sprint, and others? Well, they might just be limping. And in certain spots, rival phone companies are setting up lemonade stands, trying to offer the sweetest deal. But here’s the twist: after digging deep into the data, things aren’t as zesty as I initially thought.

Take California (CA), for instance — a whopping 63.2% churn rate! Sounds alarming, right? But in raw numbers, that’s 43 Californians in a sea of 1796 customers. So, what’s the real story behind the Golden State’s numbers? Is it just a summer fling, or is there more to this West Coast drama? I don’t know.

Case Study: Analyzing Customer Churn in Power BI

After piecing together all these intriguing puzzles, I’ve been busy whipping up my dashboard. And now,…

Ta-da! Here’s my first dashboard

Front page clarity? Think “snap-and-know!” Just one look, and the top brass should get the gist. And, honestly, it’s high time they get a grip on this because things aren’t looking too rosy.

Front page clarity? Think “snap-and-know!” Just one look, and the top brass should get the gist.

Homepage

Our unlimited plan? More like “Unlimited Bye-Bye!” 80% users? Gone with the wind.

Kudos to Ron for the deep dive. Forget the high senior churn; it’s the 30–65 squad that’s the real MVP here. Time to zoom in!

Month-to-month peeps? They’ve got one foot out the door already.

The main reason our clients are jumping ship? Could be those crafty competitors. What are they doing right? Or is there an issue with our services?

What about the deeper dives?

“When stakeholders glimpse that first page, they’re in for a hot-seat moment, thinking, ‘What the heck’s going on with our customers?’ So, I’ve got the remedy lined up — extra pages brimming with the crucial details they’re eager to uncover.”

So, here’s what I’m drawing on the other pages.

Case Study: Analyzing Customer Churn in Power BI
Age Segmentation Page
Case Study: Analyzing Customer Churn in Power BI
Contract Type Page
Case Study: Analyzing Customer Churn in Power BI
Unlimited-Plan Page
Case Study: Analyzing Customer Churn in Power BI
Churn Reason Page
Case Study: Analyzing Customer Churn in Power BI
State Page

Wrapping it up, if I were playing Sherlock Holmes, here’s what I’d scribble on my notepad for Databel:

  • More data, please! Let’s truly get to know our customers.
  • Time for a revamp of the Unlimited plan.
  • Dream up products tailored for the 30–65 crew and our seasoned citizens.
  • Yearly contracts? A win-win to keep our customers close and our cash flow steady.
  • What’s the chatter between our call center and our clientele? Let’s find out!

This was my first time diving into Power BI, and it was quite the learning curve.

Alright, here’s the lowdown: Power BI and I? Our first dance, and boy, did it make me shuffle!

Wracking my brain on the story to weave, dreaming up a snazzy dashboard that screams ‘Get this in 5 seconds, pal!’ — trust me, it’s harder than it looks.

After that mental marathon, assembling the pieces? Phew, felt like running a second marathon.

Here’s my game plan for the next round:

  • Hustle more on the dashboard speed.
  • This write-up? Yep, it’s a bit lengthy. It reminds me of Mark Twain’s words: “I didn’t have time to write a short letter, so I wrote a long one instead.”
  • Presentation’s king. No matter how genius the insights, if it ain’t pretty, it ain’t selling. And yeah, missing a header on each page? Rookie mistake. My bad, totally.

See ya on my 2/100 dashboards!

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