understanding consumer sector using transaction data doug ... · 2018. 18. deal announced. rolling...
TRANSCRIPT
Understanding ConsumerSector Using Transaction Data
How to swim with sharks
DecaData: Transaction Data With Daily Delivery.
3
Manufacturers
InvestmentManagement
Retailers
DecaData Transaction
Data
Why Alternative Data? Informational Surprise.
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Obvious Features
Non-Obvious Features
Two Case Studies
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Public company B acquires public company C
Private Company IPO
Data Sources: Odyssey 2 Daily Transaction Data,Atlas Forward Looking Promotional Data
Case Study #1 Case Study #2
Sales growth is hard.● Dynamic Equilibrium: If it was easy, all would grow.
● Finite space: (shelf space or warehouse space).
● Behavioral Economics: Consumers tend to be habitual, hard to get them to try new things.
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Firms have to incentivize behavior change.
Obvious Features
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Increasing Distribution
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Increasing SKU counts
More products, more stores, higher TAM are obvious data features.
2017-02-10 2017-11-17 2018-08-26 2019-06-03
2017-02-10 2017-11-17 2018-08-26 2019-06-03
# SKU Listed In Any Store
# Stores Featuring Any Product
Source: Odyssey 2
Source: Odyssey 2
Case study #1: Pre-Post IPO $ Sales.
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IPO
Q1 Q3
1. Prior to IPO Q2 sales gap down.
Daily $ Sales
1
Source: Odyssey 2Q2
2019-01-01 2019-07-01
Case study #1: $ Sales hint at features.
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Q1 Earnings
Q2 Earnings
IPO
Q1 Q3
1. Prior to IPO Q2 sales gap down.
2. Q1 earnings: price rises.3. Q2 earnings: price tumbles.
Daily $ Sales
Share Price
1
2
3
Source: Odyssey 2Q2
Non-Obvious Features
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$2.50
$4.00
$5.50
$7.00
2016-01-01 2016-07-01 2016-12-31 2017-07-01 2017-12-31 2018-07-01 2019-01-01 2019-07-02
Case Study #1: Changing behavior through sustained price promotion.
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More Products Listed In Store, Sales Mix Changes AIP Moves
Price Promotion
Extended Promotion
Average Item Price
Source: Odyssey 2
2019-01-01 2019-01-31 2019-03-02 2019-04-01 2019-05-01 2019-05-31 2019-06-30 2019-07-30Q3
Case Study #1:Overlaying Average Item price.
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Share Price
Q2 Earnings
Q1 Q2
Source: Odyssey 2
Q1 Earnings
2
3
IPO
$5.29
$5.79
$6.29
2019-01-01 2019-01-31 2019-03-02 2019-04-01 2019-05-01 2019-05-31 2019-06-30 2019-07-30Q3
Case Study #1: 12% drop in Average Pricealters economics, at expense of share price.
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Average item Price
Share Price
Q2 Earnings
Q1 Q2
Source: Odyssey 2
Q1 Earnings
1
2
3
IPO
Case Study #1 Average item Price, a non-obvious indicative feature.
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2014 2015 2016 2017 2018 20192013
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Rolling 4 Weekly $
Case Study #2: 5 year sales ramp-up prior to M&A news. Sales falls post announcement.
Source: Odyssey 2
Deal Announced
Earnings Call
wk1
wk14
wk27
wk40
wk53
wk13
wk26
wk39
wk52
wk12
wk25
wk38
wk51
wk11
wk24
wk37
wk50
wk10
wk23
wk36
wk49
wk9
wk22
wk35
wk48
wk8
wk21
Case Study #2: Sales ramp-up linked to price promotions increasing.
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Number of Products On Promotion Per Week
Deal Announced
2013 2014 2015 2016 2017 2018 2019
Source: Odyssey 2 / Atlas
4-wkly $ Sales
Earnings Call
2018
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Rolling 4 Weekly $Deal Announced
Price promos cause H1 margin hit (H1 prices -7% vs H2) & H2 sales hit as price corrected.
2019
Source: Odyssey 2 / Atlas
H1 $2.69 H2 $2.902018 Average Item Price
CEO described these deals as “highly inefficient…acquired firm was “chasing volume over value”
Earnings Call
Case Study #2 Weekly Promotions, non-obvious indicative features.
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Indicators of informational surprise in consumer TX data:
• Sustained Price Changes.
• Increased Store Distribution.
• Better Quality Distribution.
• Increased UPC count.
• Reduced shelf voids / Out-of-stocks.
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Setting up the radar.
Thank You