The Importance of Data in a Small Startup
It’s common knowledge that data-driven thinking is important. But what happens when you’re a small startup with small data? As trivial as it may seem, early-stage data is crucial to informing smart decisions to propel your business to the next level.
As a small startup, Brandfolder has faced these daunting data dilemmas first-hand. Fortunately, we were able to establish a few formalized processes for collecting pertinent marketing and growth information. In this post, we’ll share our process for determining key statistics, and share a few lessons learned that any company can benefit from.
Tracking Inbound Leads
A core goal of the marketing team is to drive sales leads, and ultimately attract new customers. So, we needed a way to track which marketing channels were driving which leads. Not only would these numbers be crucial information for our Board of Directors, but it would also inform our marketing spend and help us refine our overall marketing strategy.
To better track our inbound leads, we manually added all lead data into a spreadsheet, detailing: the date the leads came in, through which marketing channel, and what stage of the stage cycle they progressed through. From there, we could use a few simple excel formulas to quantify the quality and number of leads from each marketing channel. This information allows us to attribute closed-won deals to their appropriate channels, and identify which channels are most successful.
After doing this for a few months, we found that the lead spreadsheet was great for aggregating statistics of the sales funnel. However, it only offered a snapshot in time, and didn’t effectively show trends or historical progression. We’re still refining this process, and our new goal is to leverage Salesforce to capture lead details as it moves to a new stage in the funnel. Using real-time data from Salesforce will allow us to report both local trends, as well as month-over-month trends.
Calculating Key Performance Indicators
In addition to gathering data around inbound lead sources, we also wanted to calculate important key performance indicators (KPIs). In order to figure out how do this, we started where many search queries start: Google! After a bit of investigation, we chose a few KPIs to focus on:
- Cost of Customer Acquisition (CAC): The cost to acquire a new customer; defined as all sales and marketing spend divided by the number of customers acquired in a specific time period..
- Lifetime Value (LTV): A prediction of the net profit attributed to the entire future relationship with a customer.
- Average Revenue Generated per Customer (ARPA): Defined as total revenue divided by number of customers acquired in a specific time period.
- Months to Recover CAC: The total number of months to recover the cost of acquiring a new customer, given your average revenue per account.
In order to calculate these success metrics, we first needed some important numbers:
- Total expenses for marketing in sales on a monthly basis. This included all wages, commissions, and spend on software.
- Total number of new bookings and expansion revenue on a monthly and quarterly basis.
- Total number of new customers on a monthly and quarterly basis.
- Total number of customers canceling or not renewing their subscriptions.
Then, we did a few simple calculations to get our final data points. Here’s how you can calculate them for your own organization (replace the letters with the numbers from above):
- To calculate CAC, divide (A) by the number of new customers in a given time period.
- To calculate ARPU, divide (B) by 12 (to get a monthly figure).
- To calculate Months to Recover CAC, divide CAC by ARPA.
- To calculate LTV, multiply the ARPA by the average customer lifetime (how long they’re a customer).
We now use these KPIs to make sure our business is on track and growing. We also use them to evaluate ourselves against industry benchmarks, and against other companies we may be competing with.
Takeaway Tips For Your Data Journey
Brandfolder faced a few challenges while setting up our data gathering processes. Firstly, it was very manual. One person had to diligently input data from Slack into a Google sheet. We’ve since then replaced the manual spreadsheet with a few integrations between Slack and Salesforce, and will continue to automate more steps to save time in the future. Our product also moved from a monthly subscription model to a yearly subscription model. This shift required us to change our data analysis to account for those changes.
Data analysis is something we’ll keep refining in order to make sure we have the most efficient, accurate, and useful processes in place. In the meantime, here are a few key takeaways that you can learn for your own data journey.
Tip 1: Start small.
Start with a simple process, and iterate. Don’t try to perfect your entire process the first go-around, because things are bound to change. At the very least, you’ll have a few helpful numbers to work with while you refine your data analysis.
Tip 2: Chip away.
Find your cadence for measuring your data and follow your ritual routinely. Gathering useful data requires you to consistently pull numbers over time, and in order to make informed, timely decisions, you’ll need to analyze those numbers in real-time. Retroactively updating your metrics may cause you to miss opportunities for growth.
Tip 3: Make your data actionable.
To make your data actually mean something significant, tie it to an important goal. By finding something to improve on each month, quarter, or year, your team will be more motivated, and you’ll achieve smarter growth.
Tip 4: Be transparent.
Don’t confine your data or metrics to only a select group of people. Instead, share the information and allow others to ponder it, question its implications, and offer constructive feedback. By sharing early and often, you’ll coax out the gaps in your data sooner rather than later.
Whether you’re a marketer at a large corporation, or a startup employee looking to put your own processes in place, we hope you found a few helpful nuggets of wisdom in this post. Data is incredibly important for any business, at any stage — so make sure you have some helpful numbers to boost you to success. Good luck!