July 3rd, 2024
Data-Driven Marketing: 3 Key Metrics for SMEs on the Road to Success
By Lili Marocsik · 6 min read
Introduction
By now, it’s common knowledge: Data is gold. The biggest companies of our times center their attention not around food, shelter or transportation; their business is data. According to ConsultPort, Amazon, Google, Tesla, and Netflix alone generated revenue of $907 billion in 2022.
Do you know how to dig into your company's data to uncover the treasure trove underneath? How often do you take a helicopter view to find the real levers for your business growth?
I’m Lili Marocsik, I run the website www.aitoolssme.com, and in this post, I’ll discuss the most important marketing metrics for small businesses. As a professional video marketer, I have worked for big companies like HelloFresh and Revolut and spent much time digging through numbers to reach company KPIs. I wish we had the same AI tools for data analysis when I started out as we do now.
The new technology makes gaining insights so easy. Even if you are not naturally gifted with a talent for numbers, thanks to AI for data analysis, in 2024 there are no more excuses.
So, let’s look at the three most important metrics for data-driven marketing. All three will help you to make the right decisions while scaling up your business.
Let’s start the alphabet with A:
CAC (Customer Acquisition Cost) aka CPA (Cost per Acquisition)
This is the most common marketing metric and will help you determine success in the short run. Simply put: How much money must you invest to acquire one customer?
The formula:
When to look at this metric?
- To determine the success of each marketing channel
- To compare new marketing channels to established ones
- To test different ads against each other
- To compare different markets (locations) etc.
Pro-tip for CPA:
- Set conversion tracking up in a way that allows you to determine the CPA at least on the channel level. Admittedly, this is quite challenging nowadays, but a solid tracking setup will save you headaches in the future.
- Even though data analytics AI tools like Julius AI will allow looking at a daily CPA, it makes much more sense to only look at weekly averages.
- Some marketing channels are harder to measure and influence others. For example: If you have added YouTube ads recently to the mix, you might see an overall uplift in revenue, but not necessarily on channel level.
How to determine success?:
If the CPA exceeds customer lifetime value, you will lose money in the long run. In this case you must either lower your CPA or raise your CLV.
This leads us straight to the CLV:
Customer Lifetime Value
The total revenue you can expect to earn from a single customer over the entire duration of the relationship with you. In short: How much money do you make with a customer in total?
The formula:
CLV = Average Purchase Value × Purchase Frequency × Customer Lifespan
All big brands I worked for prioritize CLV over CPA. While one channel may offer easy acquisition, if those customers spend less than others, your investment becomes unreasonable.
When to look at this metric?
- If you’ve been running your marketing initiatives for at least one year (especially for longer sales cycles).
- To determine the actual value of each channel (if your conversion tracking is granular enough)
Pro-Tip CLV:
- If you clarify your value proposition to customers and ensure they understand your product's benefits, your CLV should increase and reflect it.
- If your average customer lifespan is long, don’t use this metric for A/B testing. The results will take too long to show.
How to determine success?:
CLV should ideally be at least 3-5 times your CAC.
Conversion Rate (CVR)
How many people have taken your desired action (e.g. a sale) relative to the overall size of the audience?
The formula
Conversion rate = Audience who performed your desired action / Total audience
Pro-Tip for CVR:
You can look at the CVR on various levels to understand hiccups in your user journey.
In our example scenario, let's assume you are running display ads and that your desired conversion is a sale on your website.
These are the steps you should keep an eye on (a) and the ways of measurement (b):
1. Display ad -> Check CTR as a first quality measure for your ad
2. Landing Page -> Create a ‘page view’ conversion
3. Shopping Cart -> Create a ‘shopping cart’ conversion
4. Purchase -> Create a conversion for the thank you page
Now, you can break down the full user journey by dividing the full audience size by the customers who have taken the next step.
When to look at this metric:
Whenever you change a step within your user journey, use AI for data analytics to compare the values of each step with the new numbers.
How to determine success?:
Conversion rates vary by industry, but examining the average conversion rate for each step will help determine which changes will have the biggest impact.
1. CTR: Varies a lot, depending on marketing channel and ad content (ChatGPT can help)
2. Landing Page: Conversion averages typically range from 20% to 60%
3. Shopping Cart: Conversion averages are around 10% to 30%
4. Purchase: Conversion rates for purchases commonly range from 1% to 5% of total website visitors
Let AI for data analytics become your companion throughout the data-driven marketing process. Julius will allow you to get a better understanding of the underlying user behavior (e.g., with providing insights into convoluted conversion funnel datasets) and communicate your wins (e.g., with very detailed visualizations).
But first and foremost, create dashboards to easily check the three marketing metrics mentioned. And remember to return to your helicopter cockpit at least once a month to track progress and watch your business grow.
Author Bio
Lili Marocsik, a video marketing expert based in Berlin, calls ChatGPT her new best friend. She runs the ‘AI Enthusiasts’ Meetup in Berlin and shares her insights about AI daily on her websites. For www.thepanoramai.com, she interviews industry leaders about AI and examines all the implications of this new technology. On www.aitoolssme.com, she provides non-techie, user-friendly reviews for AI tools that are especially helpful for small businesses.
