4 Customer metrics your BI tool should have

Effective segmentation is the key to relevant marketing that scales sales. And nowadays, Customer Intelligence enables even more powerful segmentation. 

A company’s segmentation strategy can only be as effective as the data it has to leverage. Unfortunately, due to the overwhelming number of data points and sources for customer analytics, many small businesses struggle to harness that data to segment marketing campaigns. What many small businesses don’t know is their accounting platform has all the data they need to create powerful segmentation.

Read on for four simple, must-have customer metrics that can be pulled from your accounting platform for marketing success.

1. Customer LTV

What is It: The total amount a customer spent from their first purchase to present day is the Lifetime Value (LTV) for that customer.

Why It’s Important: The monetary value each customer adds to your revenue is an important benchmark that can help shape your approach when marketing to new customers.

How to Use it:  By using this metric for segmentation, marketers and salespeople can find their best and worst customers: customers with small LTV could be new or poor fits, and customers with high LTVs are often your very best fitting customers. Another segment strategy is to target customers with growing LTV’s with a loyalty campaign to generate more upsells and cross-sells.

2. Trailing twelve months sales (TTM)

Definition:  The total sales from a customer in the past 12 months.

Why It’s Important: While the total a customer has spent is a great metric, more recent performance — the trailing twelve months sales, or Total Sales over TTM — may be a bigger driver of sales and marketing strategies. For example, let’s say Company A spent $60,000 three years ago and Company B spent $40,000 last year and $20,000 this year. They both would have the same LTV of $60,000, but Company B looks more active and engaged.

Would you treat both companies the same way? TTM Sales helps marketing and sales focus their upsell strategies, and to rework acquisition campaigns to bring in more Company B’s than Company A’s.

Segment: You can use TTM Sales to put customers into segments based on how much they’ve spent more recently and who might be a better near-term opportunity. Comparing LTV to TTM Sales also helps find previously loyal customers with high LTVs but where sales have slowed down. 

3. Number of purchases

Definition: How many times did a customer make a purchase?

Why It’s Important: The number of purchases is pretty self-explanatory metric and useful when looking at changes in behavior. While LTV and TTM Sales tell you how customers’ spending changes over time, the number of purchases is a good measure of engagement. 

You can find patterns in buying behavior based on purchase dates and frequencies, and then run campaigns based on seasonality or particular events around their businesses. If you know a business always purchases at a specific time of year, you can contact them at the best times to offer complementary products or services.

Segment: Many segments using the number of purchases that can be used to build better customer experiences. For example, messaging can be changed based on the number of purchases a customer has made a year. You can also create segments leveraging past behaviors, such as customers who bought in December. If marketing and sales work together, they can increase the number of sales per year and grow upsells and cross-sells.

4. Average days to pay

Definition: How soon after the sale does the customer pay you?

Why It’s Important: Most B2B companies make some or all of their sales on credit, such as giving them 30 days to pay. Extending credit to customers greases the sales process, but customers who frequently pay late slow incoming cash flow, or worse, may not pay at all! For example, should you continue extending credit to a customer with big orders, but who is three to four months late making payments? Average days to pay has the answer!

Segment: A “Late Payer” segment can help sales and service teams manage how to sell and service problem customers. For example, sales teams might not want to sell more to customers who haven’t even paid for previous orders. Or accounting and customer service can adjust their collection efforts and credit policies based on past payment performance.

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