Panel Details & Columns

Question 1

When did the C Panel start?

How many US cobrands does it contain?

Answer 1

1/1/2011

40 Cobrands (“Open Panel”)

Question 2

How many users are in US cobrand universe?

Answer 2

As of Dec 2022 - 57 cobrands

77MM Users. (“50 Million + Users”)
15MM Active (“Monthly”), Min 10MM

Question 3

How is X Panel different from C Panel?

Answer 3

Both started 1/1/2011

X is a subset of C (X Prime is another derivation, all the legacy cobrands are gone, only active) X has 5 cobrands.

69MM Users.
9.5MM Active, Min 8MM

Question 4

What are key features of RTP Panel?

Answer 4

Started Sept 2020

Bank and Card delivered hourly. Just incremental. Go forward, no history.

Question 5

How are X Panel files accessible?

Answer 5

The X Panel files are available in both text and parquet formats for bank and card
transactions. S3 & Amazon Redshift

Question 6

What UVS compound score is considered “Stable”?

Answer 6

Compound scores are ranked 1-10, 10 being the best users. A score of 6.5 and above is considered of strong stability.

Question 7

[X PANEL COLUMNS]

What is UNIQUE_MEM_ID?

What is LENGTH_OF_HISTORY?

What is AVG_TRANSACTION_VOLUME?

Answer 7

UNIQUE_MEM_ID is a unique ID for the user across the panel.

LENGTH_OF_HISTORY is # of years where a unique_mem_id has transacted in the panel.

AVG_TRANSACTION_VOLUME is the average number of debit transactions (i.e., excluding refunds or deposits) over the prior 24-month period

Question 8

[X PANEL COLUMNS]

What is CONSISTENCY?

What is VOLATILITY?

What is DISTINCT_MERCHANT_COUNT?

Answer 8

CONSISTENCY is a binary flag. A value of 1 means that a user has had a minimum of 15
transactions per month in at least 18 of the previous 24 months.

VOLATILITY is categorization of users into low/medium/high volatility based on the
number of transactions and dollar amounts.

DISTINCT_MERCHANT_COUNT is the number of unique merchants at which a user has transacted during the previous 24 months.

Question 9

[X PANEL COLUMNS]

What is DISTINCT_MERCHANT_COUNT?

What is LATEST_TRANSACTION_DATE?

What is SHARE_OF_WALLET?

Answer 9

DISTINCT_MERCHANT_COUNT - The number of unique merchants at which a user has transacted during the previous 24 months.

LATEST_TRANSACTION_DATE - Corresponds to the latest optimized_transaction_date in Yodlee panels for a given user in the past 24 months.

SHARE_OF_WALLET - Value from 0-1, representing the percentage of a given user’s financial transactions that are captured in Yodlee data.

Question 10

[X PANEL COLUMNS]

What does a SHARE_OF_WALLET value of 0.31 mean?

Answer 10

31% of a given user’s financial
transactions that are captured in Yodlee data.

Question 11

[X PANEL COLUMNS]

A user has a CONSISTENCY value of 1. What does that mean about the user?

Answer 11

It means the user has had a minimum of 15 transactions per month in at least 18 of the previous 24 months.

Question 12

[X PANEL COLUMNS]

What does a DISTINCT_MERCHANT_COUNT value of 35 mean?

Answer 12

The User transacted with 35 unique merchants during the previous 24 months

Question 13

[X PANEL COLUMNS]

What does a LENGTH_OF_HISTORY value of 4 mean?

Answer 13

The User transacted in the panel for 4 years under its unique ID

Question 14

[X PANEL COLUMNS]

What is CARD_ACCOUNT_COUNT?

What is BANK_ACCOUNT_COUNT?

What is LAG?

Answer 14

CARD_ACCOUNT_COUNT is the # of unique accounts in the credit card panels observed during the previous 24 months for a given user.

BANK_ACCOUNT_COUNT is the is the # of unique accounts in the bank panels observed during the previous 24 months for a given user.

LAG is the median transaction lag for a user in the previous 24 months.

Question 15

[X PANEL COLUMNS]

How many months is the look-back for CARD_ACCOUNT_COUNT and BANK_ACCOUNT_COUNT datapoints?

Answer 15

24 Months

Question 16

[X PANEL COLUMNS]

How many months is the look-back for VG_TRANSACTION_VOLUME and DISTINCT_MERCHANT_COUNT datapoints?

Answer 16

24 Months

Question 17

[X PANEL COLUMNS]

What is HIGH_VALUE_TRANSACTION_
COUNT?

What is COMPOUND_SCORE?

What is AS_OF_DATE?

What is PANEL_FILE_CREATED_DATE?

Answer 17

HIGH_VALUE_TRANSACTION_
COUNT is # of transactions over USD $10,000 in the previous 84 months

COMPOUND_SCORE UVS from 0 -10, where 10 represents the best users.

AS_OF_DATE is until when data is being considered for generating the score.

PANEL_FILE_CREATED_DATE is when UVS was made available

Question 18

What are the two types of Geo Data available?

Answer 18

Household Geo & Monthly Geo

Question 19

What is the difference between Household Geo and Monthly Geo?

Answer 19

Household geo module identifies where the user lives by weighting transactions in
certain categories higher. (Rent, Utilities, Mgt)

vs.

Monthly is non-weighted, the module looks at the last 30 days of transactions together and identifies the most likely location of the user based on this data.

Question 20

What are the 7 Tiers of User Income Class?

Answer 20

1 $0 - 25k
2 $25 - 45k
3 $45 - 60k
4 $60 - 75k
5 $75k - 100k
6 $100 - 150k
7 $150k+

Question 21

What figures used to categorize User Income Class?

Answer 21

Spends, Payroll, Deposits, etc.

Question 22

What is the difference between Active and Lineage Files?

Answer 22

Active files only have active users, where an active user is defined as having at least 1 transaction during the period.

Lineage files include changes from previous files. USER_DEMO_RECORD_STATUS column will indicate:

N: new record
U: updated user record
D: deleted record

Question 23

[AGGREGATE PAYROLL]

When does the aggregate payroll historically start?

Answer 23

1/1/2016

Question 24

[AGGREGATE PAYROLL]

What do the following column headers describe?

ticker, periodicity, employees, deposit, panel_active_users

Answer 24

ticker- Stock ticker to which a given employer belongs.

periodicity- Cadence of payrolls received (weekly, bi-weekly, bi-monthly, monthly…)

employees- The total number of employees receiving paychecks

deposit- The total $ amount of paychecks deposited.

panel_active_users - The total number of employees (users) in the base panel during period

Question 25

In the Aggregate Payroll Product, what are some KPI’s to help identify change?

Answer 25

1. New and existing employee counts,
2. New and existing deposit amounts,
3. Employee churn.

Question 26

What are examples of “Enrichment”?

Answer 26

Geography, Sales Channel

Question 27

[AGGREGATE PRODUCT]

How are brands & tickers mapped in the aggregate product?

Answer 27

Most tickers available in the Aggregate Product are US-listed (on the NYSE, NASDAQ, etc.) and have alphabetical one to four-letter ticker symbols (e.g., A, GOOG, WMT). At the same time, some are non-US listed and have numerical ticker symbols (e.g., 1910, 9983, etc.)

Question 28

[AGGREGATE PRODUCT]

What are the types of Aggregate Files?

Answer 28

1. “Brand-level” files – This aggregate files contain the brand-level aggregate metrics.
   The brands are also mapped to their corresponding tickers
2. “Ticker-level” files – Transactions for all brands within a ticker are rolled up as
   aggregates into constituent tickers and are not aggregated separately. For example,
   GAP (ticker: GPS) also owns Banana Republic, Old Navy, and other brands. The ticker level aggregate files will have all brands’ metrics rolled under the GPS ticker.
3. “User count” files – User counts are provided at the panel level in this file. These counts are provided so that a customer can perform a custom normalization of spends or
   transactions at the ticker or brand-level.