Customer analytics is a subset of business analytics that focuses on metrics that tell you more about your customers. Where traditional forms of financial and operations analysis only tell the story of what's happening inside your business, customer analysis tells the story of what's going on outside your offices — where your customers come from and how they make decisions.
What Are the Benefits of Customer Analysis?
Customer analytics isn't just one of the latest business buzzwords. It has a direct impact on your bottom line. According to a McKinsey DataMatics survey, businesses using customer analysis to make decisions are:
- 126 percent more likely to be ahead of the market in profits.
- 131 percent more likely to be ahead of the market in sales.
- 186 percent more likely to be ahead of the market in sales growth.
Customer analytics can help you improve your business in the following areas:
1. Marketing Efficiency
Focusing on the individual customer takes your marketing analysis beyond just knowing your spend and the eyeballs you received in return. Knowing which marketing channels bring the highest value customers in terms of order size, retention rate and profitability allows you to either cut marketing costs or expand your reach more efficiently.
2. Customer Retention
Customer acquisition is expensive, so it's important to understand what causes customers to leave. Customer analysis can help you identify common denominators among lost customers and give you an early warning that existing customers may be in danger of leaving if you don't take corrective action.
3. Increased Sales
Understanding customer purchasing decisions is the key to increasing sales. Use customer analysis to identify factors that have both a positive and negative impact on sales. This could include shipping times, how customer service interactions are handled, whether you have a minimum order or bundled discount, or the customer's location or income.
4. Improved Profit Margins
Not all customers are equal. Some customers are more profitable than others, and some may even cost you money. Factors that affect customer profitability include order size, cost of handling the order, time spent servicing the account and returns.
Amazon has gained notoriety for issuing lifetime bans to customers who cost the company money by returning too many items. Customer service representatives at banks have varying discretion to waive fees and grant other policy exceptions depending on how profitable a customer is.
If you don't want to take direct action against unprofitable customers, you can learn what attracts these customers versus more profitable ones so you can shift your focus to attracting higher-value customers.
How Do You Implement a Customer Analytics Strategy?
Customer analytics requires a combination of data collection, sound management decisions based on the data and a willingness to experiment with alternative strategies to create new data. Your controller services can help you generate customer analysis reports. Key measures to track and try to improve on include the following:
1. Customer AcquisitionCustomer acquisition measures include cost, conversion rates, and breakdowns by marketing channel and campaign. According to the DataMatics survey, businesses tracking customer acquisition KPIs are 23 times more likely to say they are outperforming their competitors in this area.
2. Migration to Profitable Segments
Many businesses offer service or product tiers where the lower tiers may have lower margins or even be unprofitable. The goal is to move customers up to a higher tier.
To find out if this strategy is working, you need to know the number of new versus migrated customers in each tier, how long it took a migrated customer to do move, what causes customers to migrate, and if any of your sales or marketing efforts make migration more or less likely.
Companies tracking these measures are 21 times more likely to report as outperforming on migration to profitable segments.
3. Customer Profitability
Tracking customer profitability measures leads to being 18.8 times more likely to report as outperforming competitors on profitability per customer. Income metrics should include total sales to the customer, average sale size, time between purchases, and what specific goods or services the customer purchases.
Expense metrics should include both direct and indirect expenses. Direct expenses include things such as the cost of goods sold, shipping costs and losses due to returns. Indirect expenses include hidden costs such as the time sales reps have to spend with each customer or the need to divert resources to fulfill unusual requests.
4. Customer Loyalty and Retention
Customer loyalty and retention is divided into two parts — identification and tracking.
First, you must be able to identify individual customers. This is easy when you have service accounts or collect shipping information for online orders, but it becomes more difficult in a retail setting. One of the easiest and most common ways to track retail customers is through loyalty or discount cards.
Once you know your customer, tracking retention is a matter of determining the average amount of time between a customer's first and last order and how many customers don't place a second order. To improve your retention rates and times, you can mine the data to look for trends that separate customers retained for a long versus a short period.
Loyalty can be tracked through the average time between orders and what specific items the customer purchases. This can help you determine whether a customer is loyal to your brand, price shops between competitors or finds you inconvenient to deal with due to distance or long shipping times.
The more you understand your customers, the better you'll be able to predict and meet their needs, and increased sales will naturally follow.
Setting up accurate reporting is a big step in understanding your customers and a key component of comprehensive controller services.