kelly halfin & gabriel goldberg - semetis - analyze and use product seasonality for your...
DESCRIPTION
TRANSCRIPT
1
How to use Web Analytics to leverage seasonality and grow
your business?
2
3
AGENDA
1. What & Why?
2. Where in Google Analytics?
3. How to leverage (Marketing & Business)?
4. Automate with technology
4
1. What is
seasonality? Why does it
matter?
5
Recurring trend on a given period
Week
Month
Year
6
Unique for each sector & business
Gift:
Travel:
7
Opportunities?
8
Opportunities?
Time Revenue
High Sea-sonality
Low Sea-sonality
€
€€€
1. Maximize & get prepared for high seasonality periods
2. Increase revenue by understanding micro-seasonalities
9
2. Where to find seasonality in web analytics?
10
4 main sources to understand seasonality
A. Sector trends
B. Searches, visits and time lag
C. Sales and goals
D. Crossing online interactions with offline sales
11
A. Sector trends
Industry seasonality?
What about your own seasonality?
Key events?
Events’ dynamics (start/end)?
...
A. Sector trends
12
28/02/2011
6/03/2011
12/03/2011
18/03/2011
24/03/2011
30/03/2011
5/04/2011
11/04/2011
17/04/2011
23/04/2011
29/04/2011
5/05/2011
11/05/2011
17/05/2011
23/05/2011
29/05/2011
4/06/2011
10/06/2011
16/06/2011
22/06/2011
28/06/2011
4/07/2011
10/07/2011
16/07/2011
22/07/2011
28/07/2011
3/08/2011
9/08/2011
15/08/2011
21/08/2011
27/08/2011
2/09/2011
8/09/2011
14/09/2011
20/09/2011
26/09/2011
2/10/2011
8/10/2011
14/10/2011
20/10/2011
26/10/2011
1/11/2011
7/11/2011
13/11/2011
19/11/2011
25/11/2011
1/12/2011
7/12/2011
13/12/2011
19/12/2011
25/12/2011
31/12/2011
6/01/2012
12/01/2012
18/01/2012
24/01/2012
30/01/2012
5/02/2012
11/02/2012
17/02/2012
23/02/2012
0
20000
40000
60000
80000
100000
120000
0
1000
2000
3000
4000
5000
6000
Visits Sales
higher conversion rate during high seasonality
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 160
5,000
10,000
15,000
20,000
25,000
0
100
200
300
400
500
600
700
800
900
1000
Visits & goals increase 2 to 3 weeks before influent event in the sector
Visits remain higher 3 weeks post-event but goals start decreasing right after the event
Case: Gift
Case: Retail
Key event
13
B. Searches, Visits and Time Lag
Evolution of branded traffic?
Key peaks/downs in visits/searches?
Duration of peaks?
Gap between visits and sales?
...
14
B. Searches, Visits and Time Lag
15
C. Sales and Goals
Key vs. long-tail products?
Key periods per product?
Share of revenue during high seasonality?
Increase of conversion rate?
...
16
C. Sales and GoalsKPI example: Weekly share of revenue from Product / revenue of all products
Product A
Week 19:Low seasonality for
product A
w1 w2 w3 w4w5
w6w7
w8w9
w10
w11
w12
w13
w14
w15
w16
w17
w18
w19w20
w21w22
w23w24w25w26w27w28w29w30
w31w32
w33w34
w35
w36
w37
w38
w39
w40
w41
w42
w43
w44
w45w46
w47w48
w49w50w51w52
0.0%
5.0%
10.0%
Good seasonality of product A: all around green circleLow seasonality of product A: all around red circle
Week 46: Product A sells well
compared to all other products
17
D. Crossing online interactions with offline sales
Visits Online, Purchase Offline (VOPO)?
Time between Online and Offline visits?
Similar trends online/offline?
Product placement?
...
18
D. Crossing online interactions with offline salesjanuary february march april may june july august september october november december
Hatspageviews on site
revenue in stores
Shirtspageviews on site
revenue in stores
Shoespageviews on site
revenue in stores
Sockspageviews on site
revenue in stores
T-Shirtspageviews on site
revenue in stores
Bagspageviews on site
revenue in stores
Investigate? Up-sell? Promote? Placement in store?
19
3. How to leverage
seasonality data?
20
A few concrete applicationsMARKETING Considerations
Adapt online & offline media planning
Influence communication strategy
Product placement (online+offline)
Better allocate marketing budgets
21
A few concrete applications BUSINESS Considerations
Optimize logistics and stock management
Avoid bottle-necks
Plan technical maintenance and new launch
Push specific products or up-sells
22
The financial impact of leveraging seasonalityA Semetis Client Success Story
revenue Y Revenue Y+10
200
400
600
800
1000
1200
1400
Set of products for which seasonality was leveraged
revenue Y Revenue Y+10
200
400
600
800
1000
1200
1400
Set of products for which seasonality was not lever-
aged
+10%+35%
23
4. Can it all be simplified or automated?
24
Bring a little tech in the process
Rising trends per product (visits + sales)
Automate alerts & dashboards
Integrate external BI data
Comparison/BI – links between patterns
25
Automate seasonality dashboards
w36w37w38w39w40w41w42w43w44w45w46w47w48w49w50w51w52w1w2w3w4w5w6w7w8w9w10w11w12w13w14w15w16w17w18w19w20w21w22w23w24w25w26w27w28w29w30w31w32w33w34w35w36w37w38w39w40w41w42w43w44w45w46w47w48w49w50w51w52w1w2w3w4w5w6w7w8w9w10w11w12w13w14w15w16w17w18w19w20
w21w22w23w24w25w26w27w28w29w30w31w32w33w34w35w36w37w38w39w40w41w42w43w44w45w46w47w48w49w50w51
0.0
1.5
3.0
4.5
6.0
Product 1w36 w37w38w39w40
w41w42
w43w44
w45w46w47w48
w49
w50w51
w52w1
w2w3
w4w5
w6w7w8w9w10w11w12w13w14w15
w16w17
w18w19
w20w21
w22
w23
w24w25w26
w27w28
w29w30
w31w32w33w34w35
0.0
1.0
2.0
3.0
4.0
5.0
6.0
Product 2
26
Use the API to create seasonality apps
27
Use the API to create trends apps
28
To conclude
1. Leverage web analytics data
2. Prepare for high seasonality periods
3. Leverage API’s to identify micro-seasonalities
4. Build dashboards to take action at all business levels