Tr. Boniface Ngunjiri.

Teacher by profession.
Aspiring Data analyst|SQL, Python|Open to new opportunities and roles.
Building projects and sharing what I learn
Github | Linkedin

[Tr. Boniface Ngunjiri. @ngunjiri01]

Day 1 of my Data Analytics journey
Today, I built a mini data pipeline by connecting MySQL with Python and using Pandas to extract and analyze employee salary data. Connected MySQL to Python and used Pandas to analyze employee salary data from a CSV/database.
I calculated:

[Tr. Boniface Ngunjiri. @ngunjiri01]

@OLUWATOMI0202 Repetition and consistency is the key for data analysis

[Tr. Boniface Ngunjiri. @ngunjiri01]

@RealBenjizo Instead of having, he should use where clause since he wants to filter on each individual row

[Tr. Boniface Ngunjiri. @ngunjiri01]

@AzuraETH She's a real heroin

[Tr. Boniface Ngunjiri. @ngunjiri01]

@AzuraETH Very helpful in business question formulation

[Tr. Boniface Ngunjiri. @ngunjiri01]

Back at it again.

Todays lesson is on a very simple metric known as LTV(Lifetime Value). This is the expected total revenue a customer will generate over a given period of time.

LTV is used in conjunction with CAC to determine LTV : CAC ratio.

To put it into prospect, you have a SaaS company that spends $90 to acquire a single customer. The customer subscription per month is $15 and it is expected that their subscription runs for a year.

Therefore, LTV of customer
=$15×12 months
Which gives us $180.

LTV : CAC ratio;

180 : 90 = 2 : 1

From this finding the company is experiencing a positive growth signal.

I have learnt that this metric is important because it helps determine a company's growth signal.

Still learning. Still building.

[Tr. Boniface Ngunjiri. @ngunjiri01]

AI integrated in data analysis may be a curse or a blessing in disguise. This heavily relies on the type of data analyst you are or aspire to be. Data analysts who will be able to use AI to handle technical parts of data will have more time to understand the data and generate accurate insights. I think stakeholders might go for those who will help save time and generate useful insights. As the saying goes, " Time is Money."

What is your take on use of AI in data analysis?

[Tr. Boniface Ngunjiri. @ngunjiri01]

A stakeholder asked:

Why are we experiencing such a low rate of new customers despite allocating huge amounts in customer acquisition?

To determine this, we should base this on the metric CAC which means Customer Acquisition Cost.

I would start by defining CAC:

CAC = Total Acquisition Spend ÷ No. of new customers acquired.

Depending on the business model, you determine what counts as spend. These may include:

1. Team salaries.
2. Tools and software.
3. Events and Conferences.
4. Paid advertisements.

During my current online food orders analysis, I have found that New Customer rate is only 6.19%.

Therefore, I would investigate whether the business is investing heavily in customer acquisition and also compare it to acquisition channels to determine:

1. Conversion rate.
2. New customers acquired.
3. Customer churn
4. Cost per acquisition.

This will help move analysis from;

" We have a low New customer rate." to " What is driving the low New Customer rate."

Next we shall look at Customer behaviour where we shall look at metrics such as Lifetime Value(LTV), Number of Customers and Net Promoter Score(NPS)

Still learning, still growing, still building. 📊

[Tr. Boniface Ngunjiri. @ngunjiri01]

@BukolaSalau2 I'd start by demand patterns and location then compare this with the sales data to identify the product to supply where demand is high.

[Tr. Boniface Ngunjiri. @ngunjiri01]

What piece of advice can you give a data analyst who is just starting out?

[Tr. Boniface Ngunjiri. @ngunjiri01]

@hespee_ Its what i've been using all along

[Tr. Boniface Ngunjiri. @ngunjiri01]

Troubles of using a probook hp laptop 4gb ram been waiting for a whole hour.🥲
I'm literally crashing out😡🤬

[Tr. Boniface Ngunjiri. @ngunjiri01]

@hespee_ I have left it....i try again tomorrow

[Tr. Boniface Ngunjiri. @ngunjiri01]

@Brayohki Utamanage all the best

[Tr. Boniface Ngunjiri. @ngunjiri01]

@hespee_ Thanks bud. Happy it helped....looking forward to your project's progress

[Tr. Boniface Ngunjiri. @ngunjiri01]

@rajatjain1107 Interested

[Tr. Boniface Ngunjiri. @ngunjiri01]

@DataSecChron @bayyoo_ Well said nobody cares apart from say analyst learning from each other. Stake holders only care about the So what? and Now what? Questions.

[Tr. Boniface Ngunjiri. @ngunjiri01]

A stakeholder has asked you the following qudstion as a data analyst:

Why has revenue increased but gross margin is shrinking?

As a data analyst, start by defining the metric.

Gross margin = (Revenue - COGS) ÷ Revenue × 100.

To determine the problem, we must identify the main drivers that may include:
Discounting.
Promotions.
Cost of production.
Product mix.
Other factors affecting COGS depending on the business model.

Having a clear understanding will help because you need to know:
What happened?
Why it happened?
So what?
Now what?

The metric in this case helps you frame the question whereas the drivers help you investigate the answer.

Next we shall look at Customer Acquisition Cost (CAC) and why it falls under money coming out of the business.

Still learning. Still building.

[Tr. Boniface Ngunjiri. @ngunjiri01]

@tapkili_ I hope ushaanza transfer procedure for when dust arrives😂

[Tr. Boniface Ngunjiri. @ngunjiri01]

@MwangiBonnie Let us start by understanding what you will do differently.