The document discusses the concept of ROPO (Research Online, Purchase Offline) and how it influences customer purchase decisions. It provides examples of how different companies have used data analysis to evaluate the ROPO effect and its impact on offline sales. Key findings include that online research can drive 40% of offline purchases, and ROPO customers on average spend 36% more. Integrating online and offline customer data through tools like Google BigQuery allows for a more complete understanding of the customer journey and how to optimize it.

1. By Mariia Bocheva, OWOX BI
ROPO effect:
How does it influence your decisions?

2. Ahoj!
Mariia Bocheva
Head of Sales and Marketing
5 years @ OWOX
Ecommerce, Analytics, BI, CRO
m.bocheva@owox.com
@BochevaMariia
@mariia.bocheva

3. 1. Developing unique services based on Google Cloud Platform since 2013
1. Implementing Google Analytics 360 (20+ GA 360 projects)
1. Helping overcome analytics challenges
12,000
users
200
clients
90
countries

4. Let’s talk ROPO

5. What does customer journey look like?
A typical customer purchase journey

6. Website Physical store
Call center
Online sales
Online traffic
Sales caused by online activity
Google Analytics
Touchpoints on the way
Mobile apps

7. Shopping behavior

8. What’s ROPO

9. Ropo figures per sector

10. What the numbers are for Czech Republic

11. Customer behavior in Czech Republic
38% 10%
33% 32%

12. Opinion
“33% of offline buyers in Czech
Republic research products
online before a purchase.”

13. What drives ROPO?
1. Shopper wants to view the item up close
2. Shopper needs the item sooner than it can ship
3. Shopper wants to avoid shipping fees
4. Shopper believes it’s easier to find product offline (website UX)
5. Shopper needs an advice (has a lack of experience)
6. Shopper is not okay with an online payment
7. Shopper finds better discounts offline
8. Shopper finds the online checkout process complicated

14. Analytics blind spots

15. How does ROPO influence ROAS

16. Opinion
“ROPO customers on average
spend 36% more than
customers who haven’t done
online research.”

17. Success Stories

18. CASE 1:
ROPO Analysis Proves that 40%
of Customers Visit the Company’s
Website before Buying Offline

19. About Darjeeling
1. Founded in 1876
2. 7 lingerie brands
3. ~6,000 employees
4. ~€400 million annual
turnover
5. 155 retail stores
6. 8.7 million offline visitors
per year

20. Main goal for 2017
Increase the global Digital budget of the Group
Problems on the way
1. Darjeeling uses different systems to collect, store and process data
2. They’ve never combined online and offline users
3. The data in the system is in French, while the data collected in Google
Analytics is in English

21. Executive board opinion: offline vs. online
95% vs. 5%
offline online

22. But the real picture should be...
X% Y% 5%
offline ROPO online

23. Quiz: how many sizes does this product have?

24. Quiz: how many sizes does this product have?
33!

25. What executive board sees now?
60% 35%! 5%
offline ROPO online

26. Data flow

27. Combine online & offline data
This is how the data was merged:
1. The analysts used the following
keys from the table: transaction_id,
user_id, and time.
2. Next, they selected the data about
all online user interactions before
the selected date, taking account of
the order completion rates.
3. Finally, they identified the channel
groupings for the sessions that
were closest in time to the
transaction date.
Table with fulfilled Orders

28. Customers’ Shopping Journey
It turned out that 85% of
all ROPO purchases are
made within 14 days.

29. How revenue is distributed considering ROPO

30. How ARPO changes over time & touch-points?

31. How ARPU changes over time & touch-points?

32. Results
1. +30% Digital budget increase for 2018
2. 25% of Digital Analytics budget saved (DMP replaced by GCP)
Сomplete success story – here

33. CASE 2:
Evaluating the Impact of Online
Advertising on Offline Sales

34. About M.Video
1. Leading consumer
electronics and home
appliances retail chain in
Russia
2. M.video has more than
400 stores in 165 cities
across Russia
3. Reaching an annual
turnover of more than
200 billion rubles.

35. The main goal was to
Evaluate the impact online channels have on offline sales
Problems on the way
M.video collects, stores and processes all the data in different
systems:
● The data about user interactions with the website is collected in
Google Analytics 360.
● The data about offline purchases and order returns is collected
in the company’s CRM system (SAP).

36. Data Flow Chart

37. Data about each order

38. Number of online, offline, and ROPO purchases
Moscow Saint Petersburg Moscow Saint Petersburg

39. Additional revenue from ROPO purchases

40. ROPO for UX insights
1. Improved the customer experience with discount coupons on the
website.
2. Simplified the online credit application form so that customers don’t
have to go to a brick-and-mortar store to buy on credit.

41. Results
1. The company found out that online channels contributed to about 10% of
offline revenue
2. Discovered the reasons why these customers choose to shop offline
Complete success story – here

42. CASE 4:
How to evaluate the ROPO-effect

43. About Citrus
1. A retail chain for gadgets
and accessories
2. Founded in 2000
3. Over 50 physical stores,
11 services centers and
5 electric vehicle centers

44. The main goals were to
1. Evaluate ROPO
2. Calculate ROI ROAS considering offline data
3. Increase advertising efficiency
What did they do:
1. Export complete data about revenue including data from call center and
brick and mortar stores into GBQ
2. Export all order statuses, including refunds, payments and fulfilment
3. Export data about users missing in Google Analytics
4. Import data about advertising costs
5. Considered data about offline orders for remarketing

45. What did they do to evaluate ROPO impact
1. Generated unique code for each Google Client_ID

46. What did they do to evaluate ROPO impact
2. Track all attempts to enter a phone number (as it’s a unique
identifier)

47. Measure ROPO effect for each category

48. ROAS evaluation results

49. Online retargeting for offline customers
1. Customized CRM system in order to “understand” where a call center
customer came from

50. Online retargeting for offline customers
2. Sent data about products viewed by this particular customer

51. Online retargeting for offline customers
3. Created remarketing lists with the relevant products

52. How about SOPO?

53. See Offline Buy Online (ROPO reversed)
1. QR codes and Snap tags
2. Mobile apps (Sephora case study)

54. The way we shop changes

55. Customers research online while buying offline
1. Compare Prices
2. Download Coupons
3. Check Sales/Redeem Exclusive Offers
4. Scan QR Codes
5. Research Products

56. Opinion
“80% of people out shopping
used their smartphone inside a
physical store.”

57. Strategies to track ROPO

58. How you can connect online and offline
1. Online apps (VOX case study)
2. Beacons
3. Loyalty cards
4. Lead magnets (content, promotion, special conditions)
5. Soft conversions to measure the intent (implement event tracking)
6. Connect Website, Applications, CRM and POS with a User ID

59. Merge data together for the analysis

60. Data Flow
Google BigQuery
1 2
3
Onboard online visit &
collect unsampled data
(GA IDs <=> CRM ID)
Import transaction
data from CRM/ERP
Website
Calculate ROPO
& build reports
4
Join session data
retroactively

61. Takeaways

62. TL;DR
1. Internet has a significant impact on driving offline sales
2. Create lead magnets to identify users
3. Take time to implement proper tracking system
4. Consider ROPO while evaluating ROAS – rethink your attribution
strategy
5. Differentiate ROPO effect between categories
6. ROPO analysis can help you eliminate UX friction
7. You have to adopt omnichannel approach

63. Download the presentation here
www.owox.com/c/performance2020/
m.bocheva@owox.com

64. Otázky?
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