Simplifying analytics: The Customer Life Cycle

Added on by Alan McGee.

When most people think about web analytics it's in the context of pageviews, visits, or bounce rates. While such metrics are certainly important components of online measurement, they are very small brushstrokes in the painting that is your customers lifetime. Good analyses may require elements of goal setting, lean testing, segmentation, or iteration. But the most critical element is the relationship between what you're measuring and the customer life cycle of your business.

The concept of the customer life cycle funnel was first discussed in a white paper by Jim Sterne and Matt Cutler, as a method to "quickly determine the roadblocks and bottlenecks that your customers encounter." You may have different phases in your own funnel, but the message is the same: in everything that you measure, ask yourself how it influences your customer life cycle.

Customer Life Cycle Funnel

Customer Life Cycle Funnel

This is true if your focus is growth, revenue, or any other top-line metric that can be tied to your digital presence. Considering your customers in these stages will help simplify your measurement, and help your team create products and marketing initiatives to address challenges indicated by your customers behavior.

A brief overview of each stage in this funnel:

Acquisition

This is the "top of the funnel" where customers first experience your online presence. The more work you put in, the wider the funnel. But acquisition is useless unless you've activated a customer by providing value in some form. If you have enough money you can drive infinite traffic, but do those visitors continue down the funnel? Probably not. No matter how visitors arrive on your site, you can always optimize value over time by measuring each channel's ability to break into the next stage of the funnel.

Activation

Think of this as persuasion; can you persuade a visitor to accomplish what you'd like them to? This stage will help you evaluate both the acquisition sources and the tools you have in place to convert those visitors into customers.

Retention/Engagement

There's a saying that it's cheaper to retain a customer than to acquire a new one. I don't universally agree, but the lower your retention rate falls the more effort you have to put into acquisition & activation to break even. This ultimately comes down to the value you provide to your customers. The greater the value, the more likely they are to return. And depending on how "sticky" your brand is, you may need to tactically remind your customers that you're still there.

Resurrection

Just because they're gone, doesn't mean they won't return. When a customer churns, it's a learning moment. Understand why they left, and attempt to bring them back to the activation stage.

With the mountains of data available these days, it's easy to get lost in minutia. The customer life cycle funnel exists to maintain focus on the big picture. As you create experiments, set goals, or just start to review a new site feature, keep this framework in mind to simplify your analyses.

Simplify analytics with the customer life cycle. Big picture context means more effective measurement. [tweet this]

Three steps to earn your colleagues respect for data

Added on by Alan McGee.

Not every team is accustomed to consulting metrics in the decision-making process. It takes a lot for a team leader to set aside their own feelings about customers, especially in the presence of data revealing a different viewpoint. Data is also likely competing against existing product roadmaps, marketing campaigns, or egos -- each of which carry a lot of weight in ignoring the numbers and carrying on business as usual. So how can you improve organizational confidence in data? It takes time, and a serious commitment to identifying those actionable metrics worthy of decision-making conversations. Here are three steps to moving your team closer to respecting data:

Don't spam your colleagues with data

Simply distributing data without context is a guaranteed way to land your email in the trash can, and will ultimately damage any chance of building respect for metrics within your organization. Instead, consider each recipient a customer in your internal audience and work with them to understand what metrics will support their work. This may mean multiple reports, dashboards, or one-off emails, but the end result is you adding valuable support that has a direct affect on your colleagues and your customers. Your marketing department can't do much with the number of pageviews from last week, but they will want to know how the new landing page affected the customer acquisition funnel.

Stay relevant, and setup time to discuss metrics

Let's say that you and the marketing lead decide the best reporting schedule is month-over-month for acquisition and retention metrics. This means month-over-month; do not miss deadlines. Setup an optional recurring meeting where you'll discuss metrics a few days after they've been sent, so there's adequate time for them to digest. So long as the metrics are timely and valuable, these meetings won't be cancelled. If they are, question why and re-evaluate their priorities so that your customers continue to be a part of the conversation. When your colleagues can see their work reflected in improving metrics over time, the value of metrics will soon become indispensable.

Let the metrics do the talking

In creating a culture that respects metrics, this is arguably the most important. Deliver information, insights, and outcomes in a way that's both depersonalized and focused on the customer. In decision making, you're much more likely to be overruled if it's your ego vs. someone who carries more influence than you. Present information from the customer's perspective, and you can change the discussion from debating confidence in the metrics to supporting your customers.

Three steps to earn your colleagues respect for data: Don't spam data, stay relevant, and let the metrics do the talking. [tweet this]

What to think about when you think about metrics

Added on by Alan McGee.

 It's easy to get into a cycle of following metrics that don't help you evaluate your business. They're what most analytics platforms serve up first, and are likely what your team asks about. How many visits did we get last month? How many total users do we have? If they're better than they were last time you checked, the team must be doing something right. But what, exactly? These are vanity metrics. Fun to look at, easy to understand, and more likely to defocus you from what really influences your product or business. So, what metrics are deserving of your attention? There's no one-size-fits-all answer, but here are a few things to keep in mind before you dig into the data:

What drives your business?

There's a reason you have a web presence. You may sell widgets, run a content site, or receive donations. Ultimately, there are fundamental business metrics that need to change over time in order for you to exist. Identify these, and make sure that your website functions primarily to influence those metrics. It sounds simple, but it's incredibly common for teams to push product that doesn't support their business goals.

Work backwards from your core business metrics

In an ideal world, a customer lands on your website ready to convert. That's rare. Your visitors may need education, guidance, or some type of nudge before they contribute to those fundamental metrics that you care about. Work in reverse to isolate the influencers of your most meaningful metrics, and to identify where to focus your attention.

Test hypotheses, iterate, and learn to love failure

As you introduce a feature (or product, or campaign), you should know it's reason for introduction and constrain your evaluation to that hypothesis. Collateral improvements to other metrics are great, but aren't the reason you expended time and resources. If your hypothesis was wrong, understand why and then iterate. It's easy to claim success using metrics that you hadn't designed for; avoid this and embrace failure as feedback.

Only evaluate metrics that are actionable

If you don't know what moves the needle on a particular metric, ignore it. An actionable metric is one that you clearly understand, both in it's relationship to your business and what causes it to move. These evaluations are best in the form of funnels, split tests, or goals that identify when a valuable outcome has been reached.

Not all customers are equal

Segmentation is critical to understanding your metrics, and how they're influenced by external factors. There's a big difference between a returning customer who's been loyal for months, and one who just stumbled in from paid search -- both in onsite activity and in lifetime value. The deeper you segment your customers into cohorts, the better you'll understand them.

(This post title was inspired by one of my favorite books, and credit to Eric Ries for creatively coining the "vanity metric".)