All the leading e-commerce and marketplace companies are obsessed with unit economics. And for a very good reason!
Unit economics is one of the fundamental financial building blocks of any business. It’s a barometer of your business health. Defined as “direct revenues and costs associated with a particular business model, expressed on a per-unit basis”, unit economics demonstrate how well your business model works and how scalable it can be.
In this article, we will explore how marketing and growth professionals use SQL and data tools to understand and optimize their unit economics which enables them to position the company for continuous growth.
Unit economics sounds very simple until you start digging deeper. In practice, understanding “true” unit economics can be a bit tricky - especially if your business model is somewhat innovative, your company has many product categories, and/or your pricing strategy is a bit “flexible”.
So what are the fundamentals of unit economics? Let’s find out.
Ask yourself a simple question – “How much money does my team have to invest in order to find and convert a prospect into a paying customer?”
Another simple question - “What is the total amount of revenue that my company is going to make from a customer over the next 3-4 years?”
Here’s the real brilliance of unit economics in a nutshell – by comparing the LTV vs CAC ratio, marketing professionals can make an educated guess if a specific product category or business avenue is feasible at least at some point in the future.
If your CAC is bigger than your LTV over a long time period: you’re either in a bad business or you raised too much venture capital.
Companies evolve over time, adding complexity to every aspect of their business. Think of new marketing channels, additional product categories, changes in product pricing – these are all necessary changes that most companies go through.
The calculations behind unit economics can get tricky very fast. Some of these improvements and changes are subtle and can’t be spotted using the high-level reports available from traditional business intelligence software, such as Looker or Tableau. Yet each one of these subtle changes can dramatically alter unit economics, and not always for the better.
Marketing and growth professionals use SQL to analyze raw data and estimate unit economics on the most granular per-unit level that is not otherwise accessible through traditional business intelligence software.
Customer acquisition costs are complicated, to say the least. Before purchasing a product or service, users interact with a combination of paid and free marketing channels, making it really hard to understand how each channel contributes individually.
One way to optimize acquisition costs in a scenario like this is to segment customers into buckets and optimize marketing channels based on their incremental contribution to that specific bucket.
For example, try segmenting your users based on their transaction value and take the top 10% spenders. If you were to isolate those users, what would their unit economics look like? Where do they come from and which channels do they use? What if you remove one of the channels from their mix, would they still make a purchase?
SQL makes raw data accessible, helping marketing and growth professionals to leverage their marketing channels and optimize acquisition costs in the best way possible.
Now let’s take a look at the bottom 10% spenders. Do these users purchase low transaction value products and services, or do they churn after the first transaction and never come back? What about their marketing channel mix? Do you pay the same acquisition price for bottom 10% spenders and for the top 10% spenders? Is that a good idea?
In this case, SQL and data tools help marketers get new insights into their customers and channels. This allows them to “fire” the least valuable ones, which reduces customer acquisition costs and enables them to reinvest the marketing budget in a smarter way.
Having looked at the transaction value, now let’s take a look at the frequency and recency of your customer purchases.
If you segment your customers by the number of purchases they make a year – that is their frequency. What is the average purchase frequency for your product or service? How does your unit economics look like for your most frequent customers?
Now, let’s zoom in on your top spenders and segment them by the number of days since their last purchase. Look at the cohort of your top spenders who are running late with their purchase. Did they disengage? Why? Losing a top spender is much worse for a business than losing an “average Joe”. Would it make sense to call them or send a personalized email to win them back?
SQL is a powerful segmentation tool that can provide you with unique transparency into the business, helping to prevent user churn and contribute to the company’s growth.
When you work for a marketplace or an e-commerce company, pricing errors happen. It is incredibly hard to keep everything in line when you sell thousands of items sourced from 50+ different vendors.
For example, I’ve seen a vendor miss-place a period and price their product $999.9 instead of $99.99...A pricing bug like this could dramatically affect unit economics and for companies that operate large catalogs of products - it might be a very labor-intensive task to find the source of the issue.
In this article, we explored five common ways marketing teams use SQL to improve their unit economics. Not only it helps to get a clear vision of the business and ask important questions, but it also helps to reduce wasteful marketing spend and reinvest resources into the most attractive business avenues.
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