A bittersweet aspect of Product Management: which metrics to work with
80,000 subscribers, 800 downloads and 700 likes — these are numbers that are pleasant to wave around to everyone from leadership to customers. But what is hidden behind such an analysis?
Metrics such as the number of registrations, views, the size of the subscriber base and the volume of the email contact database are all “Vanity metrics”, or metrics that describe only themselves.
Everyone loves to use them in analysis: from company executives to line managers. These types of metrics are especially appreciated in bureaucratic structures. Anything that is non-objective and resembles a hockey stick in a presentation is considered to be a “vanity” metric. They are often the counterweighted by Actionable Metrics or metrics that you can actually trust and use as a basis for making decisions.
What is the difference between these two types of metrics? Let’s take a look at the primary ones.
Trial Users shows how many people are logged in to the service. This metric should not be taken seriously, considering:
1) these users may not bring in any money
2) the company’s service may not actually be interesting to them (a “pumped-in” audience).
Trial Users — is a key indicator for platforms that earn their revenue through advertising. But recently, the importance of views are beginning to fade into the background — what’s more important is the pay-per-action metric. The Trial Users metric is a shortfall of technology that doesn’t allow you to see the site’s real activity.
Actionable Metric: Converting Users shows how many people have converted views into a useful action or purchase.
Page Views — not indicative: it is not necessarily known whether bots or actual people are viewing the page.
Actionable metric: Conversion Rate — going to the site and buying, etc.
If the user made a purchase 2 days after visiting the site — the Conversion Rate needs to be measured while simultaneously taking such factors into account. For example, you can put a tracker on a banner and immediately see if there are any conversions from it. Brand traffic can work differently and takes longer to calculate.
The Product Manager must be able to distinguish between the “vanity” metric from the real ones, so as not to jeopardize the company’s money and his or her own career. “Vanity” metrics are a great way to cherry-pick and go into the red.
The PM’s main friends and enemies in analytics
Social Media Likes — everyone loves getting likes on social networks, but the PM is not a teenage girl sitting on their phone in Florida: the indicator that is important to a PM is Social Media Engagement/Referrals — how many people followed the referral link and how these people interacted with the service (left a request, etc.) The former metric is irrelevant because likes are difficult to translate into payments.
Email Subscribers — the number of subscribers, of which there may be millions in the database, for which the company also pays.
To PM cares about: Email Opt-In Conversion Rate — users who open emails and click on its contents.
Leads in Sales Funnel — a deceptive metric of users who are “pumped in” by marketers. The irony is that out of 10,000 “pumped in” users, not even one makes a purchase.
Cohort Analysis of Sales Funnel — instead, the metric “daily changes in the sales funnel” is used, where only a high-quality audience is taken as the basis.
Marketing Spend — is money spent, and Return on Marketing Investment — how much money a PM has brought in to the company.
You can get a lot of money from the user but spend twice as much to get there.
How to count the “recouped” budget spending after marketing activities?
Let’s say, for example, a conference is held for teachers in Skyeng — the cost of attracting the teachers and the revenue from the event itself is known. We need to study the number of leads and the time that the teachers stayed in the company because those who leave Skyeng in two weeks are not important for this calculation.
How do you check the Leads in Sales Funnel metric when money is allocated to the marketing budget in order to attract an audience, but users don’t actually buy anything?
If the marketing department brings in an inquiry to the system, then this can be tracked. Some analytics systems can show different audience parameters. For example, if a company offers services in Moscow, then in the Leads in Sales Funnel, you can see that there is unnecessary traffic coming in from regions outside the city.
Tracking users in the funnel:
Х people go to the landing page
Х people submit inquiries
Х people agree to something.
If Х suddenly drops — look for a problem in the traffic — most likely the marketing department is “pumping in” irrelevant users.
Another “vanity” metric is the Monthly Revenue per Customer — the monthly revenue generated from one user, which is useful only if you look at as part of the ratio of money invested in the user and the remaining profit.
In contrast, there is the Customer Lifetime Value — the metric that shows the “lifetime” value of the client.
How do you calculate the LTV (Lifetime Value) and understand that the user has become obsolete, but if he could just as easily have just taken a break?
By analyzing the dynamics: you accumulate a certain number of users, then create a graph and look at the progression/regression. If the service is designed for weekly visits, pay attention to how long a person didn’t use it. If the service is more complex, for example, Aviasales or a site for real estate purchases, then the user can refrain from accessing it for over a year.
LTV is a long-term metric. You can wait an entire year to see if Lifetime Value has changed. For example, the average customer lifespan (Lifetime) in Skyeng is 2–3 years. Product Managers analyze leading metrics to see if the user bought a subscription for a second time or not.
If 70% of people have made repeat purchases, then their behavior will remain approximately the same.
If next month the figure drops to 50%, then the percentage of repeat purchases will probably continue to decrease even further.
How do you measure the performance of internal products?
- With money: how useful was the internal product to the outside service and how much profit has it brought in?
- In terms of quality indicators: how satisfied are customers with the product — for example, in NPS (Net Promoter Score).
Use the proper (actionable) metrics and may you be happy and wealthy!
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