Tag: Customer Lifetime Value

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Who said that the customer is a king?

Lesson one in succeeding at customer management: don’t treat them all alike.

Whosoever said that the customer is a king, didn’t tell us which customer! And until you know which customer deserves your very best, you’re not likely to have a very effective customer management strategy. In this post, I want to share a framework which will allow you to understand how to holistically look at your customers and then decide where to start with managing your customers better.

But why is this even important? Well, it is. The competitive pressure that most of the organizations face today has compelled them to find ways to identify customers who deserve to be king and then treat them like one! There is a strong rationale to do so: most of the organizations report that less than 1/3rd of their customer base drives more than 2/3rd of their revenues. This number varies depending upon industries; for instance, a telecom operator may report less variation in per customer revenue contribution than a B2B software development company. This variation simply depends upon the upside potential of customer engagement. Remember, huge variations in a company’s customer engagement dynamics present attractive opportunities for (niche) competitors. Therefore, companies with higher upside customer potential need to have their ‘royal strategy’ ready soon before their king departs to rule elsewhere.

Now, there are two challenges: A) how to identify king customers B) how to design a royal treatment. Though there are numerous ways one can approach this issue, the framework I propose simultaneously takes into consideration the acquisition strategy and CRM strategy of an organization. The argument is, “if a company is not attracting the high potential customers (kings) in first place, no matter what CRM strategy (royal treatment) it pursues, it will never succeed”.

Housekeeping notes:

1) Acquisition decisions reflect in the profile of target customers, acquisition channel, and messaging / advertising strategy. The success of these decisions will reflect in the type of customers you attract. Before putting customer segments to either right customer or wrong customer type, take some time to identify any common patterns / characteristics / predictors of your most desirable customers.

2) CRM decisions broadly cover product selection, buying experience, incentives, personalization, and post-sales support. You succeed if your customers find your overall value proposition exciting on an ongoing basis! Before putting your customer in different buckets of value proposition, consider a combination of quantitative / qualitative factors which show how invested a customer is in this relationship. E.g.: Avg. Order Value, Number of Orders, Recency, Net Promoter Score (NPS), etc.

3) CLV (Customer Lifetime Value) is the sum total of expected profits from a customer. Companies should try to find CLV of each customer or small (but serviceable) customer segments, rather than identifying all the customers with one CLV.

4) King Customer is the one who has demonstrated either the potential (requisite characteristics) or the actual behavior (spend + mutual fit) to be your most desirable customer.

Segmenting an organization’s customers strictly across a 2X2 framework may not be that easy or even necessary. But if you look at a range of options on the spectrum of wrong customer to right customer or low value proposition to high value proposition, you’d be able to identify the levers you need to start playing with.

Key take away for a winning customer management strategy: you definitely want more of your customers in the top-right segment. These are the customers you have always wanted to attract, and now, all that you need to do is to keep these people constantly engaged with high value proposition.

I will even argue that an organization should look beyond Pareto’s Principle of 80-20. Why not have 80% of such customers who contribute the most to your revenue? I don’t think there is a reason for us to cap our kings at just 20%… Let everyone be a king, let it be an ultimate democracy!

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How to identify and track the right metric?

“To know how to measure the success, is to know how to achieve it”

A few days ago while discussing complexities of managing a product portfolio, Uday asked me a simple question: what is the most important metric one should use to measure product performance? I suddenly felt dumbfounded because I didn’t have a clear answer. Though I could have used my heuristics to throw suggestions such as ARPU (average revenue per user), engagement, and churn rate, I knew that the thought process was more important than the metric itself. A good metric allows taking action, a bad one only provides some data. So Uday and I decided to jointly answer this question by creating a framework, which Uday will illustrate with examples from his experience. So here are the four steps:

1) Define what the big success looks like

This is the most difficult step and perhaps half the work. This requires you to see the big picture and yet relate to all the parts. But you can perhaps do it much easily, if you start thinking of success in pure binary terms. So everything succeeds, if this one or two things happen right, else everything fails.

Uday: At my previous startup, I was looking at the dashboard which tracked conversion funnel. I knew that just looking at growth in number of visits, free users, and paid users would only paint a rosy picture, and not necessarily the most accurate one. Clearly, the single most important goal for my company to succeed at this stage was ‘growth in paid user’ and ‘longevity of paid users’.

2) Break down and prioritize on the basis of need and controllability

Now that you have one or two big metric from the first step, you need to start breaking them down. Once you break it down in different parts, start prioritizing on the basis of what answers your most pressing needs and what you can control. It’s okay to combine multiple variables to create a super metric.

Uday: I decided to steer away from vanity metrics like number of page views, which were simply non-actionable for me. I focused on 1)  (CLV), which captured engagement (longevity) and reflected whether we were on track to become a sustainable business (revenue/growth); I used cohort analysis for this. 2) Net subscribers (new paid subscribers – cancellations on a given day), which helped us capture change in two important things in one attempt – number of free users converting to paid users and cancellation (super metric).

3) Locate the right data and evaluate cost

Now you know what you want to track, you need to find information to do that. Remember, available information can be cheap, but retrieving it in desired format, not always. If some information is easily available and helps you answer ~85% of what you want to track, make adjustments in your metrics and go ahead.

Uday: Although all data was readily available, I had to make additional efforts for conducting cohort analysis with CLV (the cost!). Later on I got a dashboard developed to do the same, without having to resort to excel every time.

4) Develop, present, and revise

This is more like a hypothetical step, before you actually present the final metrics. Imagine that you’re presenting your metrics to someone important. Think the questions they would typically ask. If you are able to justify your choice of metrics and explain why you didn’t include a lot of other metrics, you’ve done a good job. Else, revise.

Uday: I made all the reports / dashboards simple, comprehensible, and differentiable. I was ready to answer questions like how I was already baking in conversion rate, active users, and paid subscribers in my choice of metrics. Sometimes I would separately include information for my marketing team which would typically ask for these baked-in metrics. Lastly, since cohort analysis was the basis of my analysis, I’d put a foot-note for those who didn’t understand it well.

Remember

  1. Understand the difference between absolute and relative terms. Often, we need a combination of both to create an accurate picture.
  2. See the forest for the trees. Your selection of information or metric should try to capture major trends, opportunities, or challenges.
  3. Don’t go online right away as you start brainstorming. You have to understand what answers your business questions, not someone else’s.
  4. Go online once you know what questions you’re trying to answer. Taking ideas from how others did it efficiently is good once you understand your problems better.
  5. Keep it simple. Does it require any explanation? 🙂

A well-thought metric allows us to deal better with uncertainty of decision making, with a precision of action. And the next time someone asks me to include another metric in my analysis, I don’t want to respond by saying ‘sure, I will include that next time’. Because everything which is necessary, would already be there!

(Co-author: Abhyuday “Uday” Chakravarthi, image credit: Dennis van Zuijlekom)