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How to use Web Analytics to leverage seasonality and grow

your business?

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AGENDA

1. What & Why?

2. Where in Google Analytics?

3. How to leverage (Marketing & Business)?

4. Automate with technology

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1. What is

seasonality? Why does it

matter?

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Recurring trend on a given period

Week

Month

Year

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Unique for each sector & business

Gift:

Travel:

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Opportunities?

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Opportunities?

Time Revenue

High Sea-sonality

Low Sea-sonality

€

€€€

1. Maximize & get prepared for high seasonality periods

2. Increase revenue by understanding micro-seasonalities

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2. Where to find seasonality in web analytics?

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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

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A. Sector trends

Industry seasonality?

What about your own seasonality?

Key events?

Events’ dynamics (start/end)?

...

A. Sector trends

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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

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B. Searches, Visits and Time Lag

Evolution of branded traffic?

Key peaks/downs in visits/searches?

Duration of peaks?

Gap between visits and sales?

...

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B. Searches, Visits and Time Lag

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C. Sales and Goals

Key vs. long-tail products?

Key periods per product?

Share of revenue during high seasonality?

Increase of conversion rate?

...

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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

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D. Crossing online interactions with offline sales

Visits Online, Purchase Offline (VOPO)?

Time between Online and Offline visits?

Similar trends online/offline?

Product placement?

...

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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?

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3. How to leverage

seasonality data?

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A few concrete applicationsMARKETING Considerations

Adapt online & offline media planning

Influence communication strategy

Product placement (online+offline)

Better allocate marketing budgets

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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

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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%

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4. Can it all be simplified or automated?

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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

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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

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Use the API to create seasonality apps

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Use the API to create trends apps

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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