As an ecommerce business owner, fluctuating sales might be one of your primary concerns.
According to etailinsights, there will be almost 7.9 million ecommerce stores in 2021. That means online shoppers have a lot of options.
Does that mean you can’t improve your sales? Absolutely not. According to Statista, there’ll be over 2.14 billion online shoppers in 2021. To tap into such a vast market, you need a solid retail sales strategy.
Instead of strategies based on guesswork, you need a data-driven sales approach to ensure sustainable sales. Let’s look at the steps to improve sales by utilizing your ecommerce sales data.
Here’s what we’ll cover:
Data-Driven Sales Approach 101
Easy access to data is one of the significant advantages of an ecommerce store. As you sell online, it’s easy to gather sales reports. However, many ecommerce sales teams are unaware of the power of data.
“If you cannot measure it, you cannot improve it.”
Your digital sales data can shed light on various aspects of your sales process.
- Problems in selling
- Market opportunities
- Sales forecasting
- Profitable sales activities
- Top and underperforming products
A data-driven sales approach uses your ecommerce data to make crucial business decisions. With this strategy, you can make well-informed decisions rather than relying on guesswork.
Even though implementing a data-driven sales approach isn’t easy, you will achieve it with the correct method and tools.
Let’s look at the steps to analyze your sales data to enable data-driven sales.
How To Analyze Sales Data
- Define your sales goals and Key Performance Indicators (KPIs).
- Choose a sales dataset that will help you measure KPIs.
- Monitor your sales performance and collect data.
- Analyze the sales data and derive insights.
- Translate your data insights into sales decisions.
Please note you may need to apply these steps repeatedly until you achieve an optimum sales strategy.
Step 1: Define Your Sales Goals and KPIs
To start, you should clearly define your business goals. What are your priorities? For example, you might want to hit a specific revenue in a quarter. Alternatively, you might want to generate more leads or improve your conversion rate.
KPIs or sales metrics are data points that you can easily capture. They will help you measure your performance against your goals.Businesses use various KPIs to measure their sales performance:
- Total revenue over a year or quarter
- Conversion rate
- Average transaction value
- Customer lifetime value
Step 2: Choose a Sales Dataset That Will Help You Measure KPIs
The issue with ecommerce is not the lack of data but the abundance of it. Here are some ecommerce sales data metrics you may recognize and are relevant to your business:
- Month/year to date revenue
- Revenue by product/category
- Revenue by demographics
- Customer-specific data
It’s tempting to collect and analyze all your retail sales data. At least, in the beginning, you need to prioritize certain types of sales data.
Don’t be overwhelmed with massive amounts of data. Stick to data points that might make sense to your KPIs. For example, gathering the number of purchases a customer made will help you calculate the average transaction value.
Step 3: Monitor Your Sales Performance and Collect Data
There are many ways to collect ecommerce data, including website cookies, online sales ledgers, and Customer Relationship Management (CRM) systems. You should choose a method to record sales data based on the size of your business.
For example, small businesses can look at sales transactions and collect data using simple tools like Microsoft Excel or Google Sheets.
Step 4: Analyze the Sales Data and Derive Insights
The real power of ecommerce data comes from analytics. Sales data analytics performs various operations to collate and correlate your data.
Sales analytics can help your sales process by:
- Uncovering sales patterns and trends
- Measuring the performance of current sales strategy
- Creating sales forecasts
- Providing insights into the sales funnel
Ecommerce data analytics also helps you diagnose issues in your sales process. It might help you recognize patterns that you might not otherwise notice. For example, it might correlate customer churn with the lack of inventory.
Data analytics also help you learn customer behavior like their favorite products and frequency of shopping.
Sales analytics, along with market data, will help your lead generation and content marketing strategies.
There are several types of sales analytics for you to try, including:
Step 5: Translate Your Data Insights Into Sales Decisions
Once you have insights into your sales patterns and customer behavior, you need to convert them into actionable strategies. That is where you implement a data-driven sales approach.
Using the insights from data analytics, you can create a data-driven sales approach that includes:
- Better inventory planning
- Accurate sales forecast
- Optimum product placement on your website
- Compelling offers and sales campaigns
Here are a few examples of how to translate data analysis into sales decisions.
|Data analytics insight||Sales strategy|
|Sales by product category/department||Allocate more space for best selling products on your website’s landing page|
|Top selling products analysis||Plan inventory, cross-selling and upselling|
|Underperforming products analysis||Adjust pricing and offer deals|
|Sales revenue analysis||Allocate marketing and sales budget|
Final Thoughts: How To Create a Data-Driven Sales Approach for Ecommerce
Ecommerce sales data is a powerful resource that you should exploit to achieve sustainable sales. A data-driven sales approach facilitates fully-informed decision-making. It provides deep insights into your sales process to improve future sales.
To implement a data-driven sales approach, you need to:
- Define your goals and KPIs
- Choose data points related to your KPIs
- Monitor and collect sales reports
- Analyze ecommerce data
- Translate the data analytics insights into sales strategy.
Creating a data-driven sales approach might seem overwhelming, especially if you are planning to implement it manually. But you don’t have to do it alone.
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