Driving Higher ARPU at Signup with Value Metrics
This episode might reference ProfitWell and ProfitWell Recur, which following the acquisition by Paddle is now Paddle Studios. Some information may be out of date.
Originally published: May 9, 2018
Value metrics increase ARPU across all-sized subscription companies including those in both B2B and B2C. As the data suggests, if you aren't using a value metric you're losing out on some of your key revenue growth potential.
On this episode of the ProfitWell Report, John Bonini, Director of Marketing at Databox asks us to look at how value metrics can drive higher ARPU (average revenue per user) at signup. To answer his question, let’s look at the data from just over 5,000 recurring revenue companies.
But first, if you like this kind of content and want to learn more, subscribe to get in the know when we release new episodes.
Value metrics' impact on ARPU
Love this question John - value metrics as a lot of you know are one of my favorite topics in the world of recurring revenue and pricing. To answer your question, we looked at just over five thousand recurring revenue companies.
To get right to the point - value metrics are the most effective way for you to drive ARPU. A value metric is what you charge for - per user, per dashboards, per 100 visits, etc.
Those companies deploying a value metric tend to have much higher ARPUs than their feature differentiated counterparts in both B2B and B2C with each blended category seeing over 20% higher ARPU.
We’re seeing this trend, mainly because expansion revenue is baked directly into the pricing model where as a customer consumes more and more of what you’re selling, he or she is more than happy to pay more.
In fact, when looking at expansion revenue based on pricing model, those companies deploying a value metric are seeing 40 to 100% higher expansion revenue as a percentage of their revenue than those simply using feature differentiation.
Higher conversion rates at signup
So value metrics are great for ARPU and expansion revenue, but what about the signup element John asked us about? Well, value metrics are actually extremely useful for conversion.
Those individuals encountering a value metric based pricing model are also converting at a much higher rate.
Across different ARPU levels, conversion rates for value metric models tend to be a minimum of 10% better with some interquartile ranges extending to nearly 40% higher.
That’s pretty impressive and the efficiency stems from greater flexibility in upgrading those users over time. You’re not trying to push the user up to a plan they aren’t ready for, because they’re presumably only getting charged for the value they’re using.
Plus, if you throw a free plan into the mix, then a user can be nurtured while using a low amount of your value metric until triggered through increased usage, indicating they’re ready to convert as a customer.
Ultimately, value metrics are the way to go, because they get right to the very root of the recurring revenue model, which is the relationship. If you price based on a value metric, you’re essentially creating a symbiotic relationship with your customer, giving them and charging them for exactly the amount of product they’re looking for - no more and no less.
Want to learn more? Check out our recent episode: Starting in SMB, Mid Market or Enterprise and subscribe to the show to get new episodes.
1
00:00:00,320 --> 00:00:03,520
You've got the questions,
and we have the data.
2
00:00:03,520 --> 00:00:06,620
This is the ProfitWell Report.
3
00:00:09,135 --> 00:00:11,855
Hey, Patrick. Loving the
ProfitWell Report so far.
4
00:00:11,855 --> 00:00:13,135
Keep up the great work.
5
00:00:13,135 --> 00:00:16,635
My question is around value
metrics and more specifically,
6
00:00:16,655 --> 00:00:20,480
how brands drive higher ARPU
at the point of sign up or how
7
00:00:20,480 --> 00:00:23,920
they drive more value out of
free users or lower ARPU users.
8
00:00:23,920 --> 00:00:25,795
Looking forward to your answer.
9
00:00:25,815 --> 00:00:27,335
Love this question, John.
10
00:00:27,335 --> 00:00:29,255
Value metrics, as
a lot of you know,
11
00:00:29,255 --> 00:00:32,295
are one of my favorite topics in
the world of recurring revenue.
12
00:00:32,295 --> 00:00:33,290
So to answer your question,
13
00:00:33,290 --> 00:00:36,490
we looked at just over five thousand
recurring revenue companies.
14
00:00:36,490 --> 00:00:37,530
To get right to the point,
15
00:00:37,530 --> 00:00:40,250
value metrics are the most
effective way for you to drive
16
00:00:40,250 --> 00:00:42,555
ARPU. A value metric
is what you charge for.
17
00:00:42,555 --> 00:00:45,995
It's per user, per
dashboard, per hundred visits, etcetera.
18
00:00:45,995 --> 00:00:48,315
Those companies deploying a value
metric tend to have a
19
00:00:48,315 --> 00:00:50,715
much higher ARPU than their
feature differentiated
20
00:00:50,715 --> 00:00:53,420
counterparts in both
b to b and b to c,
21
00:00:53,420 --> 00:00:57,100
with each blended category seeing
over twenty percent higher ARPU.
22
00:00:57,100 --> 00:00:59,900
We're seeing this trend mainly
because expansion revenue is
23
00:00:59,900 --> 00:01:02,205
baked directly into
the pricing model.
24
00:01:02,205 --> 00:01:04,685
Whereas a customer consumes
more and more of what you're
25
00:01:04,685 --> 00:01:07,965
selling, he or she is more
than happy to pay more.
26
00:01:07,965 --> 00:01:11,170
In fact, when looking at expansion
revenue based on pricing model,
27
00:01:11,170 --> 00:01:13,890
those companies deploying a
value metric are seeing forty
28
00:01:13,890 --> 00:01:17,090
to a hundred percent higher
expansion revenue as percentage
29
00:01:17,090 --> 00:01:20,485
of their revenue than those simply
using feature differentiation.
30
00:01:20,585 --> 00:01:23,465
So value metrics are great for
ARPU and expansion revenue,
31
00:01:23,465 --> 00:01:26,350
but what about the sign up
element John asked us about?
32
00:01:26,350 --> 00:01:30,430
Well, value metrics are actually
extremely useful for conversion.
33
00:01:30,430 --> 00:01:33,390
Those individuals encountering
a value metric based pricing
34
00:01:33,390 --> 00:01:36,535
model are also converting
at a much higher rate.
35
00:01:36,535 --> 00:01:37,975
Across different ARPU levels,
36
00:01:37,975 --> 00:01:40,535
conversion rates for value metric
models tend to be a
37
00:01:40,535 --> 00:01:43,815
minimum of ten percent better
with some interquartile ranges
38
00:01:43,815 --> 00:01:46,290
extending to nearly
forty percent higher.
39
00:01:46,290 --> 00:01:47,410
That's pretty impressive,
40
00:01:47,410 --> 00:01:50,210
and the efficiency stems
from greater flexibility in
41
00:01:50,210 --> 00:01:52,130
upgrading those users over time.
42
00:01:52,130 --> 00:01:54,875
You're not trying to push the
user up to a plan they aren't
43
00:01:54,875 --> 00:01:57,675
ready for because they're
presumably only getting charged
44
00:01:57,675 --> 00:01:59,515
for the value that
they're using.
45
00:01:59,515 --> 00:02:01,435
Plus, if you throw a
free plan into the mix,
46
00:02:01,435 --> 00:02:04,050
then a user can be nurtured
while while using a low amount
47
00:02:04,050 --> 00:02:06,770
of your value metric until
triggered through increased
48
00:02:06,770 --> 00:02:10,745
usage, indicating that they're
ready to convert as a customer.
49
00:02:10,745 --> 00:02:13,865
Ultimately, value metrics are the way
to go because they get right to the
50
00:02:13,865 --> 00:02:15,865
very root of the
recurring revenue model,
51
00:02:15,865 --> 00:02:17,465
which is the relationship.
52
00:02:17,465 --> 00:02:19,570
If you price based
on a value metric,
53
00:02:19,570 --> 00:02:23,330
you're essentially creating a symbiotic
relationship with your customer,
54
00:02:23,330 --> 00:02:26,130
giving them and charging them
for the exact amount of product
55
00:02:26,130 --> 00:02:29,355
that they need, no
more and no less.
56
00:02:29,355 --> 00:02:30,315
Well, that's all for now.
57
00:02:30,315 --> 00:02:31,195
If you have a question,
58
00:02:31,195 --> 00:02:33,835
shoot me an email or video to
p c at profit well dot com.
59
00:02:33,835 --> 00:02:36,315
And let's also thank John
from DataBox for sparking this
60
00:02:36,315 --> 00:02:38,550
research by by clicking the
link below to give him a nice
61
00:02:38,550 --> 00:02:39,510
little shout out.
62
00:02:39,510 --> 00:02:41,330
We'll see you next week.
