During a recent data presentation, my stakeholder said to me "I don’t know what to do with this information". This statement lingered in my mind because I realized we can’t always assume our stakeholders are able to connect the dots between data and actionable insights. It’s our job as data analysts to help with this missing link. Today, I’ll discuss the process I use to translate data into insights and how you can apply this in your role.
Learn The Company Business Model
I start by answering three basic questions about the company’s Business.
- How does the company get prospective customers? – Depending on the business model, prospective customers can be visitors to a website, a lead to a sales team, or a user for a product or service. Marketing is typically responsible for bringing in prospective customers through various digital channels such as organic search, paid marketing, email, and so on. Knowing how the company gets its customers is important because this helps you figure out the business impact and where to investigate when there are KPI changes related to customer acquisition.
- What influences a prospective customer to make a purchase? – Again, depending on the business model, different factors influence a prospective customer’s likelihood to purchase. A company selling a service or product can offer a free trial to try before purchasing or an e-commerce company can offer a discount on a customer’s first purchase. The key is to know the factors affecting your company to understand how changes will impact the business. For example, what if a product company removes their free trial? This could mean fewer people will purchase because they can’t try for free and the company will make less money.
- How does the company retain customers? – Customer retention is the key to maintaining revenue. E-commerce companies have loyalty programs to give customers reward points on purchases that can be redeemed as discounts. Product companies release new features and continually improve the product experience to keep users engaged. Understanding the factors that impact customer retention is important to pinpoint issues related to retention KPIs.
Use Funnel Analysis To Map KPIs
After I understand the company’s business model, I use a funnel analysis to map relevant KPIs to each part of the customer acquisition funnel. This helps me identify the business impact of KPI changes.
Let’s use the e-commerce acquisition funnel example below to map a few e-commerce KPIs and discuss how a change in the KPI impacts the business.
- Visitors come to the website. – Total visitors and visitors by marketing channel. Fewer visitors means fewer purchases and lower revenue.
- Visitors browse products. – Average product page views. Less product page views can mean marketing is not driving the right visitors to the website.
- Visitors add products of interest to their shopping cart. – Average items added to cart. An increase in average items added to cart can translate to higher average order value and higher revenue.
- Visitor starts the checkout process. – Cart abandonment rate. Lower cart abandonment rate means more purchases and higher revenue.
- Visitor completes purchase. – Total purchases, average order value, and conversion rate. A higher conversion rate means more visitors are purchasing and higher revenue.
Note there are KPIs that span multiple parts of the funnel because the number by itself may not be meaningful. For example, cart abandonment rate and conversion rate are important KPIs calculated using data from different parts of the funnel. Find out the key KPIs at your company and map them to relevant areas of the customer acquisition funnel.
Translating Data Into Insights
Now we’ll review a couple of hypothetical KPI changes, the business impact, and how they translate to actionable insights.
- Daily purchases started to drop compared to the historical daily average. -Since purchases are the last stage in the customer acquisition funnel, we’ll need to look at different parts of the funnel to find the cause of the drop. Purchases are driven by visitors. Looking at daily total visitors we see no change in visitor volume on the website. We check the averages for product page views and items added to cart and there are no changes but we do see an increase in cart abandonment rate. After talking to product you discover there’s an A/B test running for the checkout flow and the test variant is performing worse versus control. The impact is a temporary decrease in revenue while the test is running. The actionable insight is to turn off the A/B test if it has reached statistical significance but if it hasn’t, discuss with product if it’s worthwhile to continue running the test if it’s impacting revenue.
- Conversion rate dropped compared to the historical average. – The conversion rate is calculated by taking the purchases divided by visitors. This means either visitors increased but they didn’t purchase at the same rate as before or the number of purchases went down. Breaking down conversion rates by channel we see the drop came from paid search. After talking to marketing, we discover they launched new paid campaigns that are converting at a lower rate compared to existing campaigns. The business impact is lower revenue and the actionable insight is to turn off the new campaigns for now and find out why visitors are converting at a lower rate compared to existing campaigns.
Final Thoughts
Understanding your company’s business model and customer acquisition funnel are the keys to learning how to translate data into actionable insights. I hope learning my process helps you develop this invaluable analytics skill sooner rather than later. Thanks for reading and happy data translating!
