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Week 5: Product management 3 - Coggle Diagram
Week 5: Product management 3
Test market (p.4)
Trial and repeat model
used to
predict new product sales
in an
existing category
sales depend on
Timing of the first purchase
Repeat
purchase rate
(in %)
Trial rate
: proportion of
target population
who eventually
try
the new product
Repeat
purchase frequency
(how many times customers purchase/ year)
Quantity purchased
trial and repeat rate
trial rate
= number of
first time buyers
/ target population size
repeat rate
= number of triers who
repurchase
the product/ trial population size
trial rate
are estimated by asking customers about their
likelihood of purchasing the product
trial and repeat volumes (
p.8
):
total volume = trial volume + repeat volume
trial rate adjustment
follow- through adjustment
: not all respondents follow through on their stated purchase intentions
awareness adjustment
: refers to the proportion of customers who
know
the product
availability adjustment
: measured using proportion of
stores
that carry the product
adjusted trial rate = trial rate x awareness x availability
Calculation
Trial volume calculation (
p.9
)
Calculate adjusted trial rate
Trial population = Target population x Adjusted trial rate
Calculate trial rate
Trial volume = Trial population x Units per purchase
Repeat volume calculation (
p.10
)
Repeat volume = No. of repeat buyers x
Repeat units per purchase x Repeat purchase frequency
Total volume = Trial volume + Repeat volume
No. of repeat buyers = Trial population x
Repeat rate
New product diffusion
New product diffusion curve (
p.12
)
Early adopters
Early majority
Innovators
Late majority
Laggards
Bass Diffusion Model (BDM or Bass Model)
used to predict
how many people will adopt new product
in each time period
can be used for brand level forecasting when
no close alternative
exists in the market
doesn't take
repeat purchases
into account
doesn't take
competitive behavior
into account
more suitable for
durable goods
2 types of consumers
Innovators
adopt the product on their own
adoption behavior does not depend on
product penetration
Imitators
adoption behavior is influenced by
prior adopters
adoption behavior depends on
product penetration
(
proportion of customers have adopted product
)
formula:
page 18
example:
page 19
estimation
imputation
: estimates using closely related product (p.20)
regression
quadratic equation: p.21
intuition: p.22
insights (
p.23 & 25
)
applications (p.24)