How to Use Data to Increase Your Revenue
With the various day-to-day tasks involved in running a small business, it can be difficult to find the time to make data-driven decisions. Oftentimes, business owners are forced to make decisions quickly, often relying solely on their business intuition and gut instincts. However, gut instincts can only take you so far--it’s also important to take the time to analyze your business’s data, in order to make smarter, more informed decisions.
The most common type of analysis is customer segmentation. This simply means breaking customers down into various groups, and identifying the profitability of each group. Though it may sound simple, customer segmentation is one of the most powerful ways to leverage your data and discover not-so-obvious ways to increase your bottom line.
Here’s a common example:
As a new business, you decide to offer an introductory deal to attract new customers. The introductory offer is such a great deal that you end up losing a small amount of money on each deal purchase, yet you see a sharp increase in the number of customers. All things considered, has offering the deal been profitable for your business?
Without data, we would have no way of answering this; we would have to rely on our intuition and make a guess as to “what feels right.”
With data, we can be a lot smarter than that.
A simple way to answer this question is to analyze the number of customers brought in by the introductory offer, and compare the revenue from those customers vs. the cost of the introductory offer. In this scenario, this is slightly negative, which may lead you to initially conclude that the deal is losing you money.
However, even if you lose money on those new customers during the duration of the introductory offer, it may still be profitable for you to offer introductory deals if you factor in the customer lifetime value (CLTV), which refers to the amount of net profit that the customer generates in the long run. This provides a more accurate measurement of the success of your introductory offer, since it accounts for each customer’s subsequent visits after the offer expires. By focusing your CLTV analysis on only customers who were brought in by the introductory offer, you’re performing customer segmentation.
You may also want to compare two groups to assess the quality of the customers brought in by the introductory offer. Let’s say that Group A is the percentage of customers who participated in the deal and came back within a two-week period, while Group B is the percentage of all other (non-introductory-offer) customers who made repeat visits within the same two-week period. If Group A’s return visit percentage is smaller than Group B’s, it may indicate that the offer attracts people who are simply looking for a deal, not people who are likely to convert into repeat, quality customers. This may indicate that the deal is not as effective as you would like it to be.
How does software help you analyze your data?
The first step of analyzing your data is collecting it. Without software, collecting all of the data that you’d want to analyze would take a lot of time and require an enormous amount of manual data entry (which can often result inaccurate data). Software enables you to collect the data without any additional effort, and organizes it into an easily digestible manner for you.
The best part is that you don’t have to be a math whiz in order to leverage data -- many software solutions will handle this for you by providing a suite of standard reports that their other customers have found useful, and automatically perform customer segmentation for you. Of course, being intellectually curious and having some savviness with numbers will enable you to analyze your data and create custom reports that are particularly useful for your specific use case. If this is important to you, then we highly recommend that you seek software that provides you with the flexibility to analyze and explore the data on your own, rather than limiting you to pre-configured reports.
Examples of other questions you can answer with your data
- Is it worthwhile for your business to stay open on weekends?
- What’s the optimal time for your business to close on Fridays?
- What’s the best price to charge for your services?
- What are the top sources of referrals for your business?
- What are your most profitable marketing channels?
With the many day-to-day issues you face as a small business owner, it can be tempting to make decisions based on a mixture of instincts and past experiences, and move on. However, by making data-driven decisions, you can hone your intuition and become even more confident that you’re making the best possible decisions to ensure the continued success of your business.