Better Referral Program for Better Growth

REFERRING YOU A NEW
MODEL FOR GROWTH
TIME BASED REFERRAL SYSTEM
WEBINAR

CURRENT REFERRAL PROGRAM MODEL
PROS
▸ WOM
▸ Scalable
▸ Tracking
▸ Directly related to CAC
▸ Dual sided

PROS
▸ WOM
• one of the best forms of organic traffic there is, it’s low cost, and trackable with given technologies, so you can identify key influencers.

▸ Scalable
• having a referral program is a scalable solution for growth, for example if you are doing inbound methods such as blogging, you would need more content, and thus
need to hire more content creators. or if you are doing outbound such as sales team, then you would need to hire more sales reps. However being a scalable solution
like a referral program, all that is required is a well engineered solution deployed on a server and then the referral program will require O(1) extra employees in
manpower.

▸ Tracking
• having the data of your converted refers is fantastic, but also make sure you are tracking the total referrals sent, referrals opened, referrals landed, referrals signed up,
referrals converted, or other important user events. and also track the medium that these referrals are being conducted (i.e. facebook, email, txt msg, raven scrolls
etc…)
▸ Directly related to CAC
• your cost of acquisition for this particular channel can be calculated by the reward incentive that you give to your referrers/referrees, making it easy to determine
profitability or other related business decisions.

▸ Dual sided
• one of the most important aspect is the focus on user experience/behavior psychology, taking away the feeling that users might believe they are taking advantage of
their friends by introducing rewards for both sides instead of just the referrer. Paying attention to user behavior psychology is utmost critical in designing a referral
program.

CONS
▸ frigid incentive reward structure
• this doesn’t leave enough room to raise perceived value. Perceived value is extremely important because lowering your perceived value
is HORRIBLE and anti referral best practices. When people refer products, they only want to refer you to product that’ll raise their own
value in the eye of the recipient. which makes them unlikely to organically share your product if they perceive that you oﬀer has inferior/
lowly perceived value. things startups do that lowers perceive value, handing out discounts, lack of price comparison, low value, lack
of anchor, focused on cost competitiveness.

▸ dual sided
• dual sided is fantastic, but is there more to it? can we yield higher conversions of referrals?

▸ referral passivity
▸ discovery
▸ re-engage re-engage- re-engage

CONS
▸ referral passivity
• Word of mouth referral method can be categorized as proactive or passive.

• proactive: people who are actively seeking out to maximize the amount of referral rewards

• passive: people who are aware of your product but are not actively trying to refer people due to lack of awareness, lack of
initiative, lack of attractive incentive, lack of referee to product fit, etc….An effective Referral program needs to attempt to convert
this passive cohort into proactive via raising awareness of the referral program, increase incentive attractiveness, break apathy
inertia, and have a consistent message on brand value. Awareness is often done with on site notifications or email newsletters. In
the case of emails, this leaves the possibility of your key message of raising awareness of your referral program have to cross the
“gauntlet of attention distractors” to be read.
▸ discovery
• referral programs that are not embedded into the product itself often need to be discovered by the user. if you have a referral
program, it needs to be advertised to your user base so that they become aware of it. Which means there is a possibility that a
percentage of your user base may not have been reached, thus curbing your growth potential.
▸ re-engage re-engage- re-engage
• even if you do make them aware, an effective referral program would need to constantly remind people of its existence, as long as
there is still contacts yet to be invited, there is still opportunity left on table for growth. This can be solved by using push
notification and/or email reminders, but you have to be extremely careful to not cross the line and become a nuisance instead
with spam.

• So could an alternative exist where we can directly imbed the referral into the product, by linking the usage of the product directly to
the product’s growth? Thus solving the awareness problem while also increasing incentive attractiveness, break apathy inertia, an have
a consistent brand value to better find referee to product fit?

NEW REFERRAL PROGRAM MODEL
KEY FEATURES
▸ ecosystem referral
▸ compound incentives
▸ time interval as main unit of currency
▸ All You Can Eat (AYCE)
▸ reimbursement instead of free trials

HOW ECOSYSTEM REFERRALS AND COMPOUNDED INCENTIVE WORK
CB
User
A D

B
User
A DPAID

B
User
A DPAID
+1N
+1N
where N is the unit of currency rewarded to the most adjacent referral

B
User
A DPAID
F G

B
User
A DPAID
F GPAID
+1N
+1N
+0.5N
+0.5N

User refer C C refer F Total per user
User 1N 0.5N 1.5N
Referral C 1N 1N 2N
Referral F NaN 1N +0.5N 1.5N
Total payout 2N 3N 5N

PAYOUT FORMULA/ACQUISITION COST SUM
Total payout for a chain of invites
d is depth of the chain in the referral tree at each level, m is
the maximum depth(degree/level) of the chain
the multiply by 2 in the front is because double sided
reward

WHAT ABOUT THE ENTIRE COST OF THE WHOLE REFERRAL
ECOSYSTEM TREE ? NOT JUST THE CHAIN OF INVITES?

Total payout formula for entire tree
w is total number of node to child connection with single side reward
x is total number of node to grandchild connection with n/2single side reward
y is total number of node to great grandchild connection with single side reward
z is total number of node to great great grandchild connection with single side reward
ε is total number of node to grandchild connection with single side reward
.
.
.
*note: i is degree of connection

EXAMPLE

w = 1

w = 2

w = 3

w = 4

w = 5

w = 6

w = 7

w = 12

x is total number of node to grandchild connection with n/ single side reward
.
.
.

w = 12
x = 1

w = 12
x = 2

w = 12
x = 3

w = 12
x = 4

w = 12
x = 5

w = 12
x = 6

w = 12
x = 7

w = 12
x = 8

w = 12
x = 8
w = 12
x = 8

w = 12
x = 8
y = 1
w = 12
x = 8
y = 1

w = 12
x = 8
y = 1

w = 12
x = 8
y = 1
w = 12
x = 8
y = 2

w = 12
x = 8
y = 2

w = 12
x = 8
y = 2
w = 12
x = 8
y = 3

w = 12
x = 8
y = 3

w = 12
x = 8
y = 3
w = 12
x = 8
y = 4

w = 12
x = 8
y = 4

w = 12
x = 8
y = 4
w = 12
x = 8
y = 5

w = 12
x = 8
y = 5

w = 12
x = 8
y = 5
w = 12
x = 8
y = 5

w = 12
x = 8
y = 5
z = 1
w = 12
x = 8
y = 5
z = 1

w = 12
x = 8
y = 5
z = 1

w = 12
x = 8
y = 5
z = 1
w = 12
x = 8
y = 5
z = 2

w = 12
x = 8
y = 5
z = 2

w = 12
x = 8
y = 5
z = 2
w = 12
x = 8
y = 5
z = 3

w = 12
x = 8
y = 5
z = 3

w = 12
x = 8
y = 5
z = 3
w = 12
x = 8
y = 5
z = 4

w = 12
x = 8
y = 5
z = 3
w = 12
x = 8
y = 5
z = 4
w = 12
x = 8
y = 5
z = 4

w = 12
x = 8
y = 5
z = 4

.
.
.
= 4

.
.
.
= 4 == great great great grandchild

.
.
.
= 4 == great great great grandchild d = 4

.
.
.
= 4 == great great great grandchild d = 4 = n/16 single side reward

w = 12
x = 8
y = 5
z = 4
=0w = 12
x = 8
y = 5
z = 4
=1

w = 12
x = 8
y = 5
z = 4
=1

w = 12
x = 8
y = 5
z = 4
=0w = 12
x = 8
y = 5
z = 4
=2

w = 12
x = 8
y = 5
z = 4
=0w = 12
x = 8
y = 5
z = 4
=2w = 12
x = 8
y = 5
z = 4
=2

y = 5 z = 4 =2w = 12 x = 8

Total Payout New referral model :

Total Payout New referral model :
Compare with the old traditional referral model

traditional total payout for a double sided incentive referral
where w is the number of referrals conﬁrmed

so for our example
you are looking at 12 conﬁrmed referrals
2 ∗ 12 ∗n = 24n units of reward

Total Payout New Referral Model :
Total payout old referral model:

Total Payout New Referral Model :
Total payout old referral model:
new about 1.5 times more than old

but what is the growth curve of the total payout? is it going to spiral out of control?
am I going to bankrupt my product paying too much?

converges at a deﬁned number, does not grow out of control

costs about 1.5 times more than traditional model

costs about 1.5 times more than traditional model
ONLY
in worst case

best case worst case
no additional compound incentives
need to be paid
additional compound incentives need to be paid
and compounds for every additional node in chain

ECOSYSTEM REFERRAL ADVANTAGES
adds feedback loop for the referral program: referrers invite more people and build bigger reward network for all ->
more referrals go out because bigger reward network -> more people join because more invites -> builds bigger
reward network -> more invites ….
people who refer would benefit not only from their immediate friend but also each degree of additional connections as
well
a system which benefits everyone symbiotically, each node’s edge will provide value for the root node, and subsequent
node will provide value for the root node as well, thus increasing referral yield
thus making people more willing to invite in favor of not only benefitting yourself but also other friends and their
friends, friend’s friends… make your friends look good among his/her peers
network benefits instead of just mutual benefits, potential to be bigger drive and better incentive to more invites and
higher conversions
having ecosystem reward is stronger incentive for people to refer using the channel you provide, that way it’ll provide
better metrics and tracking than when people use the generic word of mouth channel, which cause issues in attribution

COMPOUND INCENTIVE PROS
‣ more reward than double sided incentive for all participants
‣ potentially be greeted with rewards when logging back in, thus incentivizing
frequent visits if reward deemed attractive enough, potentially raising
engagement and/or retention
‣ the demographics of those who are the social connection rich group, will be
better utilized
‣ variable reward - Nir Eyal
‣ making a good referral can yield passive residual rewards for no additional
labor

KEY FEATURES
▸ ecosystem referral
▸ compound incentives
▸ time interval as main unit of currency
▸ All You Can Eat (AYCE)
▸ reimbursement period

TIME INTERVAL AS MAIN CURRENCY
WHAT IS TIME INTERVAL AKA TIME CREDITS
▸ time interval as reward, tokens for unlimited spending in
units of hours/days/months will be awarded depending
upon actions converted for referral program provider’s
business logic.

action business logic
when a person you refer opens the invitation you sent.
increase open rate
when a person you refer clicks the link increase landing rate
when the cohort of people you refer converts at (5%) or more.
(how to get this number? write longer detailed reasons why you think its best fit for them,
do not spam people, it will lower your rate, etc)
when a person you refer signs up for the service
increase conversion rate
when a person you refer successfully implement the service increase on boarding success rate with goal at better retention, e.g. Facebook’s 10 friends in
14 days
when a person you refer to has signed up for the service, but have yet
to successfully linked peripheral apis etc.
increase user experience satisfaction rate, e.g. your service could save X amount of server
cost if your user uses dropbox instead of making you host
when a person you refer opens up the invite prompt
when a person you refer starts selecting people to refer
breaks the apathy inertia
when a person you refer has been active for x period increase retention&engagement. use as a way for users to think before they invite. e.g. who
amongst my friends is more likely to use this often. NOT a hack for metrics ! !
follow us on twitter/or whatever social media handle increase social media presence
when a person you refer has bought you a beer
when a person you refer has become an employee hire
be creative!

BENEFITS
▸ having time interval aka time credits will give you power of
unlimited spending as motivator
▸ All You Can Eat(AYCE) model, or BINGE as incentive/motivator, “percentage of users that binge
watch shows is 70%” -Deloitte Survey in March 2016
▸ enables compounded and ecosystem reward
▸ more fluid transition between basic and premium plans,
recurring to bill for time tokens

BENEFITS
▸ flexible in reward
▸ allows more influence on referral cycle
▸ loss aversion principle
once the user experiences the privilege and the access to the premium benefits during his usage of the time
credit he earned, both loss aversion affect and gains kicks in, in this case the fear of losing premium privilege
period subsidized by the business, “Some studies suggest that losses are as much as twice as psychologically
powerful as gains”, while I don’t personally hold studies for intangible affects as universal truth in practice, but
logically there is no wrong in implementing both loss version as well as gains effects in your incentive
motivators. which would motivate privileged user to invite more people in order to not lose the privileges or
decide to pay.

ALSO…
▸ since the data for each step of the referral cycle is already
being tracked, organize and display these data to your
users. Nurture them into pseudo growth marketers, give
them the insights, the tutorials, the advice that are
necessary so they can do a better job at what they are
already doing, which referring your product.

REIMBURSEMENT PERIOD
WHAT IS REIMBURSEMENT PERIOD
▸ all spending accrued during a speciﬁc interval of time will
be reimbursed ( at a cost of $0 ) to the user
▸ subsidized by provider of the referral program and
product
▸ equivalent to free trial ﬁnancial wise

WHY
▸ have more control of the perceived value of your product
▸ building high perceive value is more important than
charging the right price.
▸ removes the need for discount as incentive
▸ free is a form of discounting, and discounting is the fast
lane to low perceived value

KEY FEATURES
▸ the amount spent displayed
▸ this allows the anchoring of perceived value
▸ the amount reimbursement shown
▸ micro unit pricing
▸ auto adjustment for the time that has the most spending

REIMBURSEMENT
AUTO ADJUSTMENT
▸ depending on your business
▸ charge by unit consumed? or charge by time credits?
▸ if by unit consumed then auto adjustment
▸ goal is to build trust, put their interest(save) over
ours(proﬁt)

WHAT FLEXIBILITY IN PRICING WITH REIMBURSEMENT CAN DO FOR ELEVATING PERCEIVED VALUE
▸ for example, a startup Arambay, has spent 50,000 micro units (in this case api requests) on its
account.
▸ at the end of the month you display $10,000 value(at $0.2/request) in Arambay’s account
dashboard, this $10,000 will be reimbursed so Arambay will receive no charge
▸ then when it’s time to start the next month billing cycle, give a notification that states “you’ve
done an excellent job in using our service and sending us valuable data and giving us quality
referrals to perfect our product. we’ve qualified you for a premium rate at $0.1/request” so
next month for 50,000 requests it’ll cost only $0.1/request $5000, which is half of the original
▸ just like that , you maintained your brand perceived value as a premium product, and were
still able to offer your loyal customer a discount without risking lowering perceived value.
now the reception by Arambay will be similar to gaining admittance to an exclusive club
▸ where as if it was just a free trial. the sentiment received by the Aramabay would be
something similar to “you have finished free trial, now it’s going to cost you $5000”, now
that’ll feel like a cheap shot

OTHER BENEFITS OF REIMBURSEMENT + TIME CREDIT
▸ you can run endless pricing experiments without
commitment or risk of price discrimination
▸ bad pr if you get caught split testing to charge different
prices to same customer, you’ll get caught for price
discrimination
▸ And it’s harder to iterate on pricing than other elements
of your business. Once you set a price, coming down is
usually easier than going up.

OTHER BENEFITS OF REIMBURSEMENT + TIME CREDIT
▸ leveraged to gain momentum into critical mass
▸ for startups with network effects, it is often ideal to reach critical mass as quickly as possible in
order for network effect to function in full throttle. coordinating your big launches with a referral
program that has compound incentives will motivate people to work harder to invite due to the
residual rewards
▸ since you are also offering unlimited AYCE model, you can use that as a value proposition to
generate buzz to build onto of your momentum to reach critical mass
▸ provide analytics
▸ ﬁnd clusters, sub clusters or star nodes to identify demographics groups or individuals of
certain cliques inside the referral graph
▸ identify the power referrers
▸ coordinate with other marketing efforts

IMPLEMENTATION
HOW TO IMPLEMENT
▸ product analysis
▸ current business model or planned business model
▸ cost limitations
▸ reward scalability
▸ network effect in place
▸ pick and choose features

IMPLEMENTATION
HOW TO IMPLEMENT CAVEATS
▸ some features have to be adjusted, 10k versus 10mil daily
request is unsustainable
▸ ecosystem referral and compound incentive are fundamental
▸ AYCE only apply to certain services, where you know your
spending ceiling is not easily reached, or there is network
effect in place where you get exponential value from growth
versus spending
▸ recommend at least network effect to use AYCE

REFERRAL HISTORY TABLE
username your reward their reward message
tutorial +1 days +1 days when a person you refer reads the invitation
tutorial +5 days +5 days when a person you refer visits our site
tutorial + 10 days +10 days when a person you refer signs up
tutorial +30 days +30 days when a person you refer purchased our product
patrick.y.xie@gmail.com + 1 day + 1 day invitation sent
patrick.y.xie@gmail.com +5 days +5 days website visited
patrickxie2016 +10 days + 10 days signed up as patrickxie2016
patrickxie2016 +30 days +30 days subscribed for our Premier Tier 1 plan
joey +15 days +15 days subscribed Tier 1 *courtesy of Patrickxie2016’s referral
monica +7.5 days +7.5 days subscribed Tier 1 *courtesy of joey’s referral
phoebe +3.25days +3.25 days subscribed Tier 1 *courtesy of monica’s referral
chandler +1.625 days +1.625 days subscribed Tier 1 *courtesy of phoebe’s referral
you + 5 days + 5 days twitter mention
you + 6 days + 6 days uploaded your data
you + 5 hours + 5 hours 3 month consecutive sign-in

EXAMPLE IMPLEMENTATION
INVENGINE.IO
▸ mvp stage, very very raw
▸ vision is a api/distributable engine inside apps to help
apps grow
▸ by giving smart recommendation to the app’s invite more
people page, we can the users in your apps exposed to
more curated contacts, thus higher conversions, and
higher lead counts.

EXAMPLE IMPLEMENTATION
INVENGINE.IO
▸ set up api, when apps access api, they trade in contacts data,
after we calculate through data signals, such as invite history, the
medium you are inviting on, the content type, keywords we will
return you a list of contacts that we recommend in highest
probability to low order
▸ api usage unlimited
▸ time interval credits are handed out based on ecosystem referrals
▸ when a client(A) refers a new client(B), A, and B will gain
unlimited api data usage for 30 days

QUESTIONS?
contact info: patrick.y.xie@gmail.com
checkout my startup’s mvp: invengine.io
interested in building a new referral model to
enhance growth for your startup feel free to chat

Better Referral Program for Better Growth

Recommended

Recommended

More Related Content

Viewers also liked

Viewers also liked (8)

Recently uploaded

Recently uploaded (20)

Better Referral Program for Better Growth