From the SMX Advanced Conference in Seattle, Washington, June 22-23, 2016. SESSION: The Mad Scientists of Paid Search. PRESENTATION: Advanced Google Shopping - Given by Andreas Reiffen, @crealytics - Crealytics, CEO. #SMX #11B

1. #SMX #11B @AndreasReiffen
Data Insights from Behind the Scenes
Advanced
Google Shopping

2. #SMX #11B @AndreasReiffen
About…
• Data-driven online advertising strategist
• Online retail expert
• Entrepreneur
• €3 billion in customer revenues this year
• SaaS product for Google Shopping &
Search
• 130 true experts in their field
• Offices in Germany & UK, new office in
NYC
… me … crealytics & camato

3. #SMX #11B @AndreasReiffen
Using Shopping to manage inventory
Topics we‘ll cover today …
How does price influence
performance?
Will pricing and bidding become one in
the future?
Can you use Shopping to push
slow sellers?
How to avoid common pitfalls?
The role of price in Google Shopping

4. #SMX #11B @AndreasReiffen
Google Shopping spending already surpasses text ads in
in the US and UK
DE
spending share
US
spending share
UK
spending share
72% 67%
57%
H1 16
43%
90%
H2 14
23%
77%
H2 15
28%
H1 15 H1 14
33%
10%
Shopping Text Ads
36%
H2 14
59%
H1 14
64%
41%
56%
H2 15 H1 15
44% 46%
54%
H1 16
44%
56%
34%
H1 16
49%
56%
H2 15
51%46%
H2 14
44%
44%
H1 15
54% 56%
66%
H1 14
Analysis based on crealytics data from retail campaigns in Fashion, Luxury, Outdoor and Sports; 20M clicks in total

5. #SMX #11B @AndreasReiffen
Using Shopping to manage inventory

6. #SMX #11B @AndreasReiffen
You want to push slow sellers while saving budget for products
which are almost sold out
Product Stock level over time Action
Week 1 Mark down!
Week 1 Sold Out!

7. #SMX #11B @AndreasReiffen
40% of budget is allocated to products that will sell on their own
within 3 weeks
Comment
PPC budget should be
allocated to inventory
that is high in stock or
sells slowly
At the moment 40% of all
budget is spent on quick
sellers while only 21% is
spent on products that
will be in stock after 3
months time
PPC budget allocation
by stock projection for top 100 products
* top 100 products, at least 1500 clicks per week / product
40% of budget 21% of budget
10
21161413121110
15
24
20
0
2017 18 23
5
22191521 6 84 7 953
Spend

8. #SMX #11B @AndreasReiffen
Most people do not buy what they are looking for
Only 34% of
conversions
match the
product that
was clicked

9. #SMX #11B @AndreasReiffen
Same Designer Different Designer
purchaseclick
34%
16%
14%
15%
21%
64%
36%
Different
Category
SameCategory
We analysed what people actually bought when they clicked on
a product ad

10. #SMX #11B @AndreasReiffen
If people don’t buy what they are looking for, how can you
manage inventory via Shopping?

11. #SMX #11B @AndreasReiffen
With yield we refer to the real value contribution of selling a
product via paid advertising
How-to Example
$80
Product
$80
$0
Stock level over time Yield Action
Week 1 Mark down!
Week 1 Sold Out!
$90

12. #SMX #11B @AndreasReiffen
Track all products which were sold after a click on a product ad
How-to Example
1,000 clicks
11 Items sold
x 4
x 4
x 2
x 1
ConversionsProduct clicked

13. #SMX #11B @AndreasReiffen
Normally you take your margin values to inform the bidding
about the value of an advertisement
How-to Example
Products purchased
4
4
2
1
$120
$80
$8
$22
Total Margin = $230
Product Clicked Quantity Margin totals
$150
Margin
$30
$20
$4
$22

14. #SMX #11B @AndreasReiffen
Based on this data the bidding calculates a value per click and
suggests a bid
Clicks = 1000
Value per click: $230 / 1000
Existing value per click
= $0.23
How-to Example

15. #SMX #11B @AndreasReiffen
The blue sneaker is a slow seller which we want to push
How-to Example
Products purchased
4
4
2
1
$120
$320
$8
$22
Total Margin/ Yield = $470
Product Clicked Quantity Margin/Yield TotalsMargin/Yield
$30
$80
$4
$22$150

16. #SMX #11B @AndreasReiffen
New bid takes yield into account and will be higher
Clicks = 1000
Value per click: $470 / 1000
Updated value per click
= $0.47
Value per click increases $0.47 which will be reflected in a
higher bid and more sales of the black sneaker
How-to Example

17. #SMX #11B @AndreasReiffen
What people buy after a click on a product ad is often very
random. Does our approach work anyhow?
1) Brands and Categories have specific
stock level profiles
2) Stock level profiles per brands and
categories stay consistent over time
Our approach will work if …
64%
same designer
65%
same category
Clicked to bought

18. #SMX #11B @AndreasReiffen
Designers (and categories) have specific stock level profiles
which are stable over time
QUAY AUSTRALIAInventory average NEW LOOK
41% 45% 38%
30%
31%
35%
29% 24% 26%
week 3week 2week 1
39%
22%
avg
38%
21% 26% 31%
76% 70% 67%
2%
week 2
5%
week 1
2%
week 3
normal
low stock
high stock
Low stock = sold
out within 2
weeks
High stock = will
last 3 months

19. #SMX #11B @AndreasReiffen
When we simulate the effects on CPC, clicks and conversions, we
see a more effective acquisition
Account result
change
Product acquisition
change
100%
Yield
100% 100%
171%
147%
190%
Cost Revenue
Margin acquisition
Yield acquisition
Comment
Our simulation shows
that by incorporating
yield values more high
stock level products and
less low stock level
products will be sold
Yield grows faster than
revenue as yield is the
KPI we are optimizing
towards
low stock
high stock
normal
+87%
-32%
+20%

20. #SMX #11B @AndreasReiffen
Pro-actively
managing
inventory is
possible
People usually
don’t buy what
they click on
Incorporate
yield values to
manage
inventory
$.47
Your key takeaways

21. #SMX #11B @AndreasReiffen
The role of price in Google Shopping

22. #SMX #11B @AndreasReiffen
Impressions and clicks in Google Shopping are often very
sensitive to price changes
Clicks drop off after product price increase Chart Info
5% price increase
coincides with a 60%
decrease in clicks
0
20
40
60
80
100
120
0
10
20
30
40
50
60
Price in £
+5%
clicks own price Google product
category:
Apparel & Accessories >
Shoes > Sneakers
Brand:
Days
Clicks
Price

23. #SMX #11B @AndreasReiffen
Google will take traffic away from you if your product prices
exceed the average market price
Product price
change
to avg market price Sum of Imps Sum of clicks Result
+43%
After
106%
Before
74%
-70%
30,002
Before After
100,239
683
-79%
After
3,222
Before
Google takes
away 70% of traffic
Result: to maintain
traffic, you will
need to bid much
higher
*based on 700 products
Product pricing is key to success in Google shopping

24. #SMX #11B @AndreasReiffen
We compared cheap vs. expensive products and used a test
setup to guarantee meaningful results
We compared
cheap products
(below avg. price)
with expensive products
(above avg. price)
The Idea
• At least six competitors
• Available at all times
• Similar products (all
sneakers)
The Criteria The Test
• Products were
excluded from normal
shopping activity
• Results were not
influenced by regular
bidding activities

25. #SMX #11B @AndreasReiffen
For all products we often see S-shaped curves, but cheap
products generate traffic much earlier
There is a direct relationship between product price,
maxCPC bid and impressions Key insights
Impression volume for
expensive products
significantly lower
Cheap products hit
Impression limit after 5
days
1.2
1,000 0.6
1.0
0.4
0.2
0 0.0
500
0.8
1,500
2,000
5-13-16 5-11-16 5-12-16 5-15-16 5-17-16 5-16-16 5-14-16
Max CPC
Impressions
per product
Max CPC
expensive products
cheap products

26. #SMX #11B @AndreasReiffen
Average CPC is higher for products
with prices above average market price
Max CPC bid, Avg CPC while bidding up Key insights
Avg. CPCs of expensive
products is about 15%
higher despite same bids
5-16-16 5-17-16
0.25
5-11-16
0.43
0.75
0.65
0.71
0.65
5-15-16
0.58 0.54
5-14-16
0.48
0.35
5-13-16
0.33
5-12-16
0.18 0.14
cheap products
Max CPC
expensive products

27. #SMX #11B @AndreasReiffen
Cheap products generate the lion‘s share of total traffic
Traffic of similar products within one shop Key insights
Cheap products
generated much more
traffic despite similar
number of products in
both groups
Imps
134%
4.282.611
1.828.412
103.803
135%
Clicks
44.122
2.047
9%
# of
products
1.876
expensive products cheap products

28. #SMX #11B @AndreasReiffen
Despite getting more traffic, the performance of the
cheaper products is much more efficient
Performance of similar products within one shop Key insights
Number of orders
through cheap products
almost 3 times higher
Higher CR resulting in
CPO being ~30% lower
Cheap products
generate 280% more
conversion
40
28
-29%
CPO Conversions
1,042
+280%
274
+61%
0,6%
CR
1,0%
expensive products cheap products

29. #SMX #11B @AndreasReiffen
180
55
0
5
45
15
50
40
10
There is not really a long tail:
A small number of products drive the majority of the sales
Conversions per product
multi brander UK Key insights
More significantly than
in search, shopping
conversions are driven
by just a few products
Concentrate on those
products for account
optimisation.
Top 10% products = 58% conversions
*Chart displays all products with conversions (448)
Expensive
Cheap

30. #SMX #11B @AndreasReiffen
Cheap products are converting significantly better than
expensive ones
Key insights
Only a few products are
responsible for more
than half of all
conversions
Selling only a few
products at a cheap
price can make a big
difference
Total conversions of similar products within one shop
Conversion
Distribution
3%
38%
58%
Top 10%
Middle 80%
Bottom 10%
20%
Share of
top 10%
converting
products
80%
Cheap
Expensive

31. #SMX #11B @AndreasReiffen
Your key takeaways
Don’t overbid on
expensive
products, rather
consider price
changes
Price and bid
management
will be merged
one day
Discounting only a
few select
products could be
a killer strategy
$.47$.47-50%

32. #SMX #11B @AndreasReiffen
SEE YOU AT THE NEXT #SMX!
Thank you!
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