Product management is about creating change. Metrics are the guideposts that help us ensure that the changes we make are leading to the results we want. They let us forecast, provide early warning signals, and create incentives for action.
In this talk Meghan Cochran talked about designing good metrics, gaining alignment among a broad range of stakeholders, and communicating progress effectively. She discussed the trade-offs of looking at rates & ratios vs absolute numbers, and talked about funnels, cohorts, and other fascinating and exciting measures of success.
14. Let’s take a brief moment to talk about
correlation & causality...
15. We have two variables, A & B.
Correlation
A & B move together historically
Causality
Change in A causes a change in B
Sometimes, it can be hard to tell the difference...
16. An online retail store has seen a seasonal dip in
January sales for the last three years.
The team decides to run a site-wide sale &
email campaign Jan 15-18, investing heavily in
compelling creative and messaging.
It’s a disaster: Email click rates are flat & sales
dip even lower than historical seasonality.
The team is surprised and disappointed.
They scrap the creative direction.
19. First, we need to
understand our
FUNNEL
series of
repeatable
actions leading to
observed action
Success = purchases
Click
#
%
%
%
Customers
Visit the site
Engage with site
Make purchase
21. There are two
levers in a
FUNNEL
(1) Increase volume
(2) Improve conversion rates
Click
Visit the site
Engage with site
Make purchase
#
%
%
%
22. SEGMENTATION
provides insight
into how to move
those levers
Examine the data for variations by
- Source
- Demographics
- Date & time
- Content (ads, landing pages, etc)
Click on an ad
%
#
23.
24. Communicate
outcomes
CONSISTENTLY
(1) We increased volume
Click
(2) We improved completion rates
# ↑ x%
% ↑ x%
% ↑ x%
% ↑ x%
Purchases # ↑ x%, with Revenue ↑ x%
Visit the site
Engage with site
Make purchase
25.
26. COHORTS
Show variations
between groups
at the same stage
in the customer
lifecycle over time
Purchases made by new customers
Nov Dec Jan
# New 250,000 400,000 225,000
Click rate 10% 17% 11%
Engage rate 35% 64% 37%
Purchase rate 3% 5% 3%
# Purchases 263 1,920 275
31. Concerned about acquisition costs, the team
made a Q1 goal to double organic traffic.
The new content strategy worked.
Organic traffic & purchases doubled.
Cost of acquisition remained flat.
ORGANIC monthly Before After
Organic as % traffic 3.6% 4.3%
# Organic unique users 9,026 17,818
Conversion rate 0.13% 0.12%
Organic purchases 12 21
32.
33. Product management is about creating change.
Metrics are the guideposts that help us ensure that
the changes we make are leading to the results we
want. They let us forecast, provide early warning
signals, and create incentives for action.
This talk is about designing good metrics, gaining
alignment among a broad range of stakeholders,
and communicating progress effectively. We'll
discuss the trade-offs of looking at rates & ratios vs
absolute numbers, and we'll talk about funnels,
cohorts, and other fascinating and exciting
measures of success.
Quotation attributed to W. Edwards Deming
Meghan Cochran
meghanpcochran@gmail.com
Product School - 10/4/17
34. Part-time Product Management Courses in
San Francisco, Silicon Valley, Los Angeles
and New York
www.productschool.com
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Sometimes it’s a few large changes, often it’s a large number of smaller one. The data will help determine the strategy.
Incentives are powerful, and metrics are a very public form of pressure. What we measure, we will move. When we have too many metrics, we lose focus. When we have too few for too long, we can lose perspective.
There are hundreds of metrics that *can* be important. But forget about all the noise and focus on clearly defining success. Example: flying a plane, pilot has dozens of dials to watch but the goal is landing the plane successfully - and there’s no dial for that.
In business this is hard to separate - are sales higher this month because of the advertising?
Or because of the change we made to merchandising?
In business this is hard to separate - are sales higher this month because of the advertising?
Or because of the change we made to merchandising?
Let’s say you work in retail...
A funnel is always a snapshot in time
Now you can make estimations about impact to the business.
Classic funnel is
Segmentation is cutting the data by WHO is going through the funnel or by variations of the experience
Now you can make estimations about impact to the business.
Note that this is showing a new snapshot in time, using % increases to show the net change
Now you can make estimations about impact to the business.
This cohort is by month, but the cohorts can be any shared data - e.g. new vs returning for same month.
Cohorts provide a meaningful comparison with actionable results.
Here we see that we have made progress with the funnel even though the volume has been wildly variable.
Like a smoke alarm, local metrics show variations in key business areas - but up or down doesn’t
When local metrics go up or down, sometime more research is needed to understand what levers will move it. They are like a control panel, showing where to dig deeper.
In business this is hard to separate - are sales higher this month because of the advertising?
Or because of the change we made to merchandising?
Stakeholders want to trust you to run your area - if they trust you to think clearly about the important metrics, they will trust you to make good decisions.