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My strategy for using data to attract, acquire and retain more customers
Use data people.
Thomas Varekamp
November 25, 2022
Mike Greenfield & co-started Circle Of Friends in September 2007.
It was a simple idea: an application on Facebook that allowed you to organize your friends for content sharing.
The timing was perfect: Facebook just went viral and gained users quickly.
By mid-2008, Circle of Friends had 10.000.000 users.
Mike focused on growth above everything else.
But there was a problem...
Less than 20% of circles showed any activity whatsoever.
Mike went digging.
He started looking through the data of users and what they were doing.
Here’s what he found:
Moms were:
115% more likely to attach a picture to a post they wrote.
110% more likely to engage in a threaded conversation.
180% more likely to click on Facebook news feed items.
Friends were 50% more likely to become engaged users after invitation.
The numbers were so good that in June 2008 Mike switched focus completely.
Circle of Moms launched on Facebook.
By 2009 the team grew its community to 4.500.000 active users. Later, the company moved off Facebook, grew independently, and sold for a large sum of money.
The point of the story above is that analyzing data can lead to new opportunities that can propel your company to new heights of profitability.
I’m an ex-management consultant with 4+ years experience in data science serving large corporates. Over the years I gained a lot of insights into how data is used to get a great advantage over competitors.
Below I give some tips on how you can leverage data to attract more clients, increase profits and reduce customer churn. The use cases are aimed at SaaS, but can also be used in other digital products, such as mobile apps, marketplaces, or e-commerce.
1. Getting more customers
The main goal is to understand where your customers come from and where you should focus your attention. Putting your time and energy into the most effective channels can save you a lot of money and help you gain more customers. The easiest way to get these insights is to install a web analytics tool such as Google Analytics or Plausible.
Implementing these tools on your website is extremely easy and fast. If you haven’t done so already, I would suggest to do it right away so you can start collecting this data.
Next to the standard reporting on pages, these tools also offer ‘tags’ that you can implement in your website to record certain actions. For example, button clicks, page navigation, form input etc.
Attribution modeling is also a big benefit of these tools. Attribution modeling means that you can add attributes to links, so you can check exactly from which sources your customers come.
For example, if you launch a paid campaign on Reddit, but simultaneously go viral with a post on Reddit, you have no idea what actually got your customers to your product. With these attributes, you can separate the data and know how much traffic comes from your paid campaign, and how much comes from the Reddit post. This helps in making better decisions for the future.
Tip: Don't fall into the trap of "putting all your eggs” in one marketing channel. Test, iterate, and compare a variety of channels to know which channel is driving the best leads for the lowest cost.
Questions that data can answer:
What channels drive the most website visits?
Why do they drive the most visits?
How can we leverage this information to get more customers?
2. Increase profits
Exploring your customer data can provide extremely valuable insights into which types of customers generate the most revenue.
An example would be the Circle Of Moms case described above.
Dividing your customers into groups based on demographics, income and industry is called customer segmentation. Ideally, you want to identify customers that generate the most profit for your business. You can use this in 3 ways:
Focus your marketing on the most profitable customers.
Develop specific features for this customer in order to attract more of them and keep them using your product for a longer period of time.
Pivot your product to only serve this type of customer.
Machine learning can also be applied to identify the groups for you, but this takes more experience.
Tip: RFM is a well-known method to do customer segmentation. RFM modeling is a type of customer value modeling that uses transaction data to segment your customers based on 3 pieces of data:
Recency: the period of time since their last purchase.
Frequency: the total number of transactions over a given period.
Monetary: the total value of their purchases.
Doing this type of analysis helps in understanding and prioritizing the most valuable customers.
Questions that data can answer:
Which customer type drives the most profit?
Why do they drive the most profit?
How can we leverage this information to drive more profit per customer?
3. Decrease customer churn
Customer churn is the number of customers that stop using your product. Generally, it is more expensive to attract a new customer than it is to keep one. To maximize your business growth potential, you should not only focus on bringing in new customers but also retaining existing ones.
You should try to understand what types of customers are more likely to churn and why, so you can take action. For example, you could contact the customers and offer a discount code if they think the price is too high, or you could create a new feature that many churning customers are missing.
Questions that data can answer:
Which customers have the highest potential of churning?
Why do they have the highest potential of churning?
How can we leverage this information to reduce customer churn?
Tip: Send an email to churned customers asking why they left. This type of qualitative data can provide a lot of information about your company's weaknesses. Applying these insights helps in retaining your customers longer.
I've noticed that many aren't doing the simple things, which can have a lot of benefits for little investment. Try to think of questions that when answered would improve your business, and then find the data to answer these questions. Leveraging analytics can be the difference between bankruptcy and extreme profitability.
Hopefully, this was useful for you. If you have any questions, let me know by replying to this mail.
If you enjoyed it, please forward this email to friends who want to know more about data in business.
See you next week!
Thomas