Path A

A Garden of Forked Paths No More Using Clustering Algorithms To Identify the Optimal Path-to-Purchase in Consumer Electronics Yaakov Kimelfeld, Kantar Media Compete

1

w w w . c o m p e t e . c o m

How do we do it? •

•

2

Survey

•

Understand the motivators behind the events consumers perform during the shopping process

•

Triggers, resources, emotional stages, shopping stages (like early, middle, end), brand consideration, segments, etc.

Clickstream analysis

•

Shopping Path Analysis – which specific online touchpoint categories shoppers interact with, what order they use them in, how much time they spend on each category, etc.

•

Measure the extent to which Shoppers perform specific activities on websites or media they interact with during their research/shopping process

w w w . c o m p e t e . c o m

Compete’s approach to Path-to-Purchase analysis •

•

A study that identifies the resources Consumers used while researching a purchase

•

What online and offline touchpoints influence shoppers in their research and purchase process?

•

At what point during their shopping journey do consumers interact with those touchpoints?

•

What is the evolving role and impact of specific touchpoints throughout the shopping process?

•

How do brands enter and leave consumers’ consideration set?

An integrated solution that includes

• • •

3

Segmentation (defining the segments or testing existing segments) Clickstream Path to Purchase (defining the path as a whole or by segments) Look-a-like modeling (to enable us to take those segments and model the entire panel to do more analysis on smaller sample ad impacts, etc.)

w w w . c o m p e t e . c o m

Survey Data

4

w w w . c o m p e t e . c o m

Buying a TV is a complex process with a lengthy consideration process BEGINNING (n=245)

~ 4 weeks

Identifying what to look for, researching brands, determining the price range

MIDDLE (n=144)

~8 weeks

END (n=34)

~ 11 weeks

Determining which TV brands, models and features are the best fit

Sony Samsung LG Vizio Panasonic

68% 64% 54% 43% 37%

LG Samsung Vizio Sony Panasonic e

68% 68% 62% 53% 42%

Online Offline

3.78 3.16

Online Offline

4.23 3.86

Narrowing down the list of brands/models, searching for the best deals LG Samsung Vizio Sony Panasonic Online Offline

68% 68% 62% 53% 42% 2.72 3.29

Shoppers appear to rely heavily on digital in the Beginning and Middle stages and shift their attention to offline resources in the End stages of the process Source: Compete Path to Purchase Survey. Based on Intenders, n=423 5

w w w . c o m p e t e . c o m

Samsung has the highest conversion-to-purchase while Sony has the lowest Out of a 100 TV in-market Shoppers… Initial brand consideration

54 considered LG

62 considered Samsung

Shoppers lost/gained in the later stages

- 7 stopped considering brand +11 stared looking

Total brand consideration Shoppers purchasing the brand Total consideration conversion

67 considered Sony

47 considered Vizio

- 11 stopped considering brand +5 stared looking

- 25 stopped considering brand +5 stared looking

- 12 stopped considering brand +14 stared looking

54 + 11 = 65 considered LG

62 + 5 = 67 considered Samsung

67 + 5 = 72 considered Sony

47 + 14 = 61 considered Vizio

13 bought an LG TV

19 bought a Samsung TV

13 bought a Sony TV

16 bought a Vizio TV

13/65 = 20%

19/67 = 28%

13/72 = 18%

16/61 = 26%

Source: Compete Path to Purchase Survey. Based on both Intender and Purchaser brand consideration. N=948 6

w w w . c o m p e t e . c o m

Online retailers and CE store displays were more used resources in the early stages of the shopping process

•

OEM websites do not appear to be used extensively but those that do use them are satisfied with the experience

•

Opportunity: Leverage Amazon as a channel to reach early stage shoppers

R7,10: Resource Usage & Resource Usefulness (Beginning of Research) (Asked of respondents using the resources in the beginning of their research process, April 2012)

High Satisfaction Professional reviews Sales rep in a CE store Consumer reviews

Low Usage

Online only retailer Mass-merchant store display OEM website CE store display Flyers/brochures CE store website

Wholesale store display

Sales rep in a massmerchant store Source: Compete Path to Purchase Survey 7

w w w . c o m p e t e . c o m

Mass-merchant website

“High-performing” quadrant

High Usage

Search engines Friends/family

Wholesale store website

Low Satisfaction

“Opportunity” quadrant “Low-performing” quadrant “Improvement” quadrant

Clickstream

8

w w w . c o m p e t e . c o m

TV shopping is a complex process involving multiple steps and site categories Compete used dynamic algorithms to highlight patterns within the multitude of shopper path variations The following inputs covering three key areas of shopper activity were used to create the algorithmic model:

Activity

Intensity

Order 9

w w w . c o m p e t e . c o m

Reducing the complexity with clustering Consumer1 Consumer2 Consumer3

X

time from exposure to end state Exposure to social media Exposure to reviews Exposure to retailer End state

The following inputs covering three key areas of shopper activity were used to create the model: • Touch points used • # of steps in the process Activity • Order of touch points

10

Intensity

• • •

Total time on path Time on touch points Time between touch points

Order

• • •

First two touch points Last two touch points Sequence of touch points

w w w . c o m p e t e . c o m

X

•

•

•

X

X

Model integrates individual consumer behavior with overall path behavior to estimate relative importance of the touch points along a path. Using Latent relationships between the touch points and consumer behavior, relative similarity distances between the paths are estimated. A segmentation model using fuzzy clustering algorithm segments the paths in finite number of segments based on similarities between the paths.

Shopper path “types” are defined based on distinct characteristics Pathing Characteristics Leading to End State Clickstream Analysis Window = 90 days leading up to the End State

Path A

Path B

Path C

Path D

Path E

% of All Paths

20%

4%

65%

7%

4%

Av. # of steps

8

10

3

8

15

Time on Path

2.6 weeks

5.6 weeks

4 weeks

8 weeks

10 weeks

Behaviors:

Most differentiated touchpoint(s) in each respective path

Time to End of Research Retailer category OEM category Review category Aggregator category Social Media category Search Time on T1* Time on T-1** 11

w w w . c o m p e t e . c o m

*T1 = time on first touchpoint **T-1 = time on last touchpoint

Model output generated five FPTV shopper path “groups” differentiated by size, time on path and use of touchpoints

Path C 65%

Path E 4% Path B 4%

Path A 20%

Path D 7%

5.6 weeks

2.6 weeks 4 weeks

10 weeks

Time

8 weeks

Over 80% of FPTV shoppers only used one touchpoint (predominantly Retailer) in their research process Source: Compete Clickstream data 12

w w w . c o m p e t e . c o m

Pathing data: how to read it End State

First touchpoint

Second touchpoint

% of shoppers on this path that started at a specific touchpoint

% of shoppers taking the next step

Retailer 13

w w w . c o m p e t e . c o m

Search

Second-tolast touchpoint *Intermittent steps are not detailed in this analysis due to the high number of path combinations

OEM

Review

% breakdown of touchpoints leading up to the last touchpoint prior to the End State

Aggregator Social-media

Last touchpoint % of shoppers that end at a specific touchpoint prior to reaching the End State

Path C: most-common, shortest path characterized by the importance of Retailer, OEM and Aggregator sites End State

37% 10%

92% 54%

21%

14%

22%

9%

49%

4%

12%

11%

11%

Reviews 5% SM 4%

32% 22%

21%

90% 98%

6% 18%

79%

2%

5%

11% 11%

Reviews 3% OEM 1% Aggregator 1%

Aggregator 7% Reviews 3% Search 1%

24%

70%

50% 28%

OEM 9% Aggregator 8% Reviews 7% SM 4% 14

32%

64%

28%

11% 9%

w w w . c o m p e t e . c o m

19%

16 %

50% 11%

10%

15%

5%

Retailer

38% Search

OEM

Review

12%

31% 21%

Aggregator Social-media

12%

Reviews 8% SM 4%

Path C: Key Takeaways

15

•

Over 80% of shoppers on this path had 3 or fewer steps; however the average time on path is not as short as average path length suggests, indicating in-depth research

•

Shoppers on Path C displayed the highest usage frequency of Aggregator and OEM sites

•

OEM sites played a more significant role for shoppers that did not start their path with Search, suggesting that Sony has an opportunity to insert itself into the consideration set with SEM strategies

•

Social media sites played a significant role in driving traffic to Retailer (but not OEM) sites for shoppers that didn’t start their research with Search or Retailers

•

Retailer sites played a paramount role in driving traffic to OEMs creating a high potential for “brand stores” (e.g. “Samsung” store on BestBuy.com)

w w w . c o m p e t e . c o m

Path A: quickest, second most-common path characterized by intense shopping & the dominating role of Retailer sites End State

37% 18%

45% 29%

31% 13%

22% 13%

11%

56%

27% 88% 10% 8%

Reviews 3% Aggregator 2% SM 2%

7%

82% 71%

45% 9%

8%

6%

5%

32%

7%

OEM 9% Reviews 7% Aggregator 5% SM 5%

5%

5%

10 %

Retailer 16

w w w . c o m p e t e . c o m

20 %

8% 5%

40%

39%

15%

17%

OEM 6% Aggregator 5% Reviews 6% SM 2%

35%

66%

26%

41%

9%

Search

OEM

Review

19 %

40% 17% 14% 9%

52%

Aggregator Social-media

9%

11%

Path A: Key Takeaways

17

•

Despite a relatively high number of touchpoints used this was the quickest path, indicating a gunshot approach

•

Even though most shoppers started with Search, Retailer was by far the most used and influential touchpoint

• •

OEM sites played a bigger role in the later stages of the process

•

Shoppers that didn’t start with Search or Retailer were significantly less likely to use search in subsequent steps, suggesting a higher importance of search in the earlier stages of the research process

•

Majority of shoppers that use OEM sites right before the End State came from Reviews sites, pointing to the importance of fostering that relationship

After Retailer Search was the second most-common touchpoint to be used prior to the End State with OEM being a distant third

w w w . c o m p e t e . c o m

Thank you! [email protected]

18

w w w . c o m p e t e . c o m