What’s the most useful report or metric for understanding your customers?
Great question @jasonh. For me, the most useful metric really depends on the stage of the business, so it’s hard to pick just one. But if we twist the question a bit to “the most interesting metric,” I’d go with LTV (or CLV — customer lifetime value).
I think many merchants can relate to this one because it’s not only important but also practical in many cases. What makes it interesting is how much insight you can actually uncover just from this single metric.
CLV = AOV × Purchase Frequency × Lifespan
By breaking it down into its components, you can answer questions like:
- Is a customer truly loyal or just one-time?
- If loyal, how much are they willing to spend over time?
- How often do they come back?
- Is your customer acquisition cost justified? (using the CLV:CAC ratio, with a healthy benchmark around 3:1 to 4:1)
That’s my perspective, but I’d love to hear other angles from the community too.
Cohort analysis is very useful.
From what I know in the team, we seldomly use one report or metric to determine or understand our customers immediately. The result usually arises from the combinations of different metrics like DAU/MAU, NPS, Google Analytics or Retention Rate.
When putting these reports and metrics together, we will obtain a comprehensive outcome that minimizes uncertainty and instability in decision-making as much as possible.
Sounds interesting. Care to share a bit more?
For quite a few reasons, really. It helps understand retention/churn on a cohort basis. So you can see when users are dropping off, letting you understand the customer more (which is very important).
Another aspect, weirdly enough, relates to sales attribution. Sometimes it’s quite hard to understand where sales should be attributed, as everything seems to take credit for it. But when you look at cohort retention, if you’re a small business, you’re often able to see which months your best users are coming from. And, since you can often remember which marketing channels you pushed most that month, you can figure out which channels are performing best, which lets you lean into those channels.
Obviously it helps massively with you understanding what the LTV/CAC is, but it also lets you understand, in any particular month, which users are actually spending money with you. So if you turn off all your ad campaigns you can see at what point will your sales drop significantly.
Take a deep look at your customer strategy - No one would know your customer better than you do - What metrics or insights are useful should purely depend on where you are on your customer journey?
Before deciding on the metrics you want to use, reflect on following questions that will help shape your CX strategy
Who are your most valuable customers — and what do they value most?
How does your product or service make the customer feel?
Where in your customer journey are you seeing the most friction – do you know why? Are you working on fixing?
Do you know the value of delivering a good or a bad customer experience?
Are your customers turning into advocates? – Referrals, Reviews, Community
Love to hear thoughts and wish you the best for your business.
Love the idea of merchant journey going with the reporting. How do you define a good user experience and a not-so-ideal one?
This is a good one @jasonh . We typically approach this for our clients by helping them define perfect order. It starts by understanding the following pillars of a perfect order:
| Pillar | Simple definition | Benchmarks (targets) |
|---|---|---|
| Find it | Shoppers can quickly discover a relevant product without dead-ends. | • Zero-result rate ≤ 5% • CTR ≥ 30% |
| Price it | Pricing and delivery promise are clear and behave exactly as expected. | • Conversion rate ≥ 70% of ATC items • Promo error rate ≤ 1% |
| Order it | Checkout is smooth, payments succeed, and customers don’t need to chase. | • Payment success ≥ 95% • contact rate ≤ 10% |
| Fulfill it | Orders are picked right, shipped on time, proactively communicated, and easy to resolve. | • On-time delivery ≥ 97% • Refund/Exchange ≤ 5 business days • poor qulaity returns ≤ 2% |
We tune this for each customer to create a perfect order Index and map it to merchant journey clearly identifying opportunities for growth and improvements by comparing a perfect order with not so perfect one.
Let me know your thoughts and any specific challenges in merchant journey if you have in mind.
For us, cohort analysis has been a game changer. Looking at how different groups of customers behave over time gives way more insight than just surface-level metrics like total sales. I can see which acquisition channels bring in the customers who actually stick around and spend more, not just the ones who convert once and disappear.
I also keep a close eye on AOV and repeat purchase rate together. One without the other doesn’t tell the full story. High AOV but low repeat rate might mean great upsells but poor retention, and the opposite might mean you’re not maximizing order value. Combining those gives a clear picture of customer quality.
Popular tool is Google Analytic 4, you can customize the cohort or journey report to see. But to track user behaviors, I aslo use tool like Hotjar and Clarity to see how they react with my web