Acting as digital analyst for RestorationHardware.com, 2016 sales have been forecasted based on the previous 4-years of data from the web analytics provider.
Scenario:
▪ In order to save money in the down economy, RestorationHardware.com has reduced marketing spending and cut inventory buys.
▪ This strategy caused for negative sales growth – much lower than expected.
Goal:
▪ Increase Sales back to positive growth rate to reach $662m in Item Sales for 2016.
▪ List what metrics will be used.
Anomaly detection and data imputation within time series
Digital Analyst Forecasting
1. R E S T O R A T I O N H A R D WA R E
D I G I TA L A N A LY S T A S S I G N M E N T
D I G I TA L R E TA I L 4 0 7 0
C H R I S T O P H E R G A R C I A , M A D I S O N T H A I N ,
M A D I S O N W O L F E , W E S L I E C E N T E N O , I R I S L E
2. O V E R V I E W
The Problem
• Reduce marketing spending
• Cut Inventory
Negative Sales
Growth
End Goal
• Increases sales back to positive growth rate
• Reach $662 million in item sales for 2016.
3. 2 0 1 2 - 2 0 1 5 A T A G L A N C E
UNIQ UE V ISITO RS
0
37,500,000
75,000,000
112,500,000
150,000,000
2012
2013
2014
2015
Unique Vistors
Trending
UNIQ UE BUYE RS
0
1,500,000
3,000,000
4,500,000
6,000,000
2012
2013
2014
2015
Unique Buyers
Trending
S A L E S
$200,000,000
$400,000,000
$600,000,000
$800,000,000
2012 2013 2014 2015 2016
Fiscal Year
Trending
SESSIONS VS.
DIRECT SESSIONS
0
60,000,000
120,000,000
180,000,000
240,000,000
2012
2013
2014
2015
Sessions
Direct Load Sessions
BOUNCE RATE
0%
6%
12%
18%
24%
2012
2013
2014
2015
Fiscal Year
18.9%
20.9%
23.8%
21.7%
Product Page View Increased
• Review Product Page
• Up Sell / Cross Sell
• Perform Usability Testing
Unique Visitors To Site Increased
• Identify traffic sources using tracking URL
Abandonment Rate
• Lengthy checkout process (Evaluate time spent on site)
• Cumbersome
• Lack of Promotions
- Nothing to excite customers to complete purchases.
Are customers coming back to complete purchases after a 24 hour period?
How are customers behaving during seasons?
Do we have seasonal promotions?
Are Newsletters Effected By Reduced Marketing Budget
• Customers who receive email newsletters spend 82% more when they buy from the
company. (iContact)
4. N E W M E T R I C S C A L C U L A T E D
AVERAGE UN IT RETAIL
$26.00
$27.50
$29.00
$30.50
$32.00
2012
2013
2014
2015
Fiscal Year
$31.88
$28.75
$27.53
$26.60
AVERAGE ORDER VALUE
$80.00
$87.50
$95.00
$102.50
$110.00
2012
2013
2014
2015
Fiscal Year
$103.10
$95.29
$91.60
$88.18
CONVERSION RATE %
0%
1%
3%
4%
5%
2012
2013
2014
2015
Fiscal Year
4.22% 4.20%
3.02%
2.21%
$ / VISIT
$0.00
$1.25
$2.50
$3.75
$5.00
2012
2013
2014
2015
Fiscal Year
$4.35
$4.00
$2.77
$1.95
Year Sessions Direct Load Sessions Bounce Rate Unique Visitors Unique Buyers Sales Items Ordered Orders AUR AOV Conversion Rate $/Visit Product Page Views Abandonment Rate
2012 155,959,661 78,620,284 18.9% 97,067,073 4,792,221 $ 678,649,665 21,288,222 6,582,402 $31.88 $103.10 4.22% 4.35 410,011,875 69.6%
2013 179,274,970 89,034,041 20.9% 112,219,244 5,420,176 $ 717,109,805 24,940,782 7,525,855 $28.75 $95.29 4.20% 4.00 419,178,780 70.2%
2014 239,445,842 117,204,128 23.8% 143,995,412 5,999,375 $ 662,606,666 24,071,754 7,233,364 $27.53 $91.60 3.02% 2.77 585,012,226 74.6%
2015 236,032,975 112,887,345 21.7% 140,004,898 4,332,728 $ 460,044,428 17,296,216 5,216,403 $26.60 $88.19 2.21% 1.95 706,678,073 77.8%
2016 339,651,451 162,444,889 20.5% 201,467,048 6,234,796 $ 662,000,000 24,889,255 7,506,520 $26.60 $88.19 2.21% 1.95 600,000 73.5%
1.439 or 143%
increase
1.2 orders per unique vistor on
average
*Product page views has increased by 121,665,847 YOY
$201,955,572
Needed to make goal of $662 million
With average order at $88.19 we need approximately 2,290,005 more orders. Bounce rate has decreased YOY, meaning other metrics will have to be focused on to increase orders.
5. S I G N A L I N G T H E R O O T F O R D E C L I N E
PRODUCT PAGE VIEWS
0
200,000,000
400,000,000
600,000,000
800,000,000
2012
2013
2014
2015
Fiscal Year
410,011,857 419,178,780
585,012,226
706,678,073
ABANDONMENT RATE
68%
71%
74%
76%
79%
2012
2013
2014
2015
Fiscal Year
69.6%
70.2%
74.6%
77.8%
• Increased Product Page
Views by approx. 121
million.
• Possibly looking for
other items to purchase
on site due to items
being out of stock.
• Abandonment rate is
increasing YOY.
• However, Bounce Rate is
falling meaning
consumer has (intent to
purchase.)
Possible Causation:
Low Inventory Turnover Rate / Buying Levels Are Too Low
Declining Customer Service Score
BOUNCE RATE
2014
2015
23.8%
21.7%
6. Assuming there is increased traffic, our customer is still coming back meaning customer loyalty is strong.
This is our 2nd chance to increase retention amongst new consumers.
We should:
‣ Leverage this traffic to convert unique visitors into unique buyers.
There is promise here seeing as unique buyers from 2012-14’ has seen an increase by ~1.2 million or 125%
We do this by:
• Increasing inventory levels by using 2013 as our POR.
* 2013 accounted for the highest orders placed and sales revenue.
This will result in:
• Consumer confidence
• Ability to purchase desired items / Less Browse Time
• Opportunity to capitalize on consumer buying intent.
S T R A T E G Y 1
“Decrease in inventory level for a retailer may result in lower
service level in some cases. In such cases, the impact on
future profitability would depend on the trade-off between
the benefit of having lower inventory levels and the cost of
decline in service levels.” (ChicagoBooth)
Year Sessions Direct Load
Bounce
Rate
Unique Visitors Unique Buyers Sales Items Ordered Orders AUR AOV
Conversion
Rate
$/Visit Product Page Views
Abandonment
Rate
2 0 1 3 1 7 9 , 2 7 4 , 9 7 0 8 9 , 0 3 4 , 0 4 1 2 0 . 9 % 1 1 2 , 2 1 9 , 2 4 4 5 , 4 2 0 , 1 7 6 $ 7 1 7 , 1 0 9 , 8 0 5 2 4 , 9 4 0 , 7 8 2 7 , 5 2 5 , 8 5 5 2 8 . 7 5 9 5 . 2 9 4 . 2 0 % 4 . 0 0 4 1 9 , 1 7 8 , 7 8 0 7 0 . 2 %
2 0 1 4 2 3 9 , 4 4 5 , 8 4 2 1 1 7 , 2 0 4 , 1 2 8 2 3 . 8 % 1 4 3 , 9 9 5 , 4 1 2 5 , 9 9 9 , 3 7 5 $ 6 6 2 , 6 0 6 , 6 6 6 2 4 , 0 7 1 , 7 5 4 7 , 2 3 3 , 3 6 4 2 7 . 5 3 9 1 . 6 0 3 . 0 2 % 2 . 7 7 5 8 5 , 0 1 2 , 2 2 6 7 4 . 6 %
2 0 1 5 2 3 6 , 0 3 2 , 9 7 5 1 1 2 , 8 8 7 , 3 4 5 2 1 . 7 % 1 4 0 , 0 0 4 , 8 9 8 4 , 3 3 2 , 7 2 8 $ 4 6 0 , 0 4 4 , 4 2 8 1 7 , 2 9 6 , 2 1 6 5 , 2 1 6 , 4 0 3 2 6 . 6 0 8 8 . 1 9 2 . 2 1 % 1 . 9 5 7 0 6 , 6 7 8 , 0 7 3 7 7 . 8 %
7. Restoring Marketing Practices
We aim to:
‣ Rebuild ROI
‣ Understand the consumer’s decision journey for purchasing product as well expected service quality
‣ Shed light on what marketing program are profitable (Tracking URLS)
This discussion should be had with every aspect of the organization during marketing planning meetings and not
limited to the marketing team exclusively. This is especially true for CPG to ensure that the value of these
established relationships with our customer is sustained as we continue to scale.
Review:
• Customer Comments/FAQ
• Data Review
• Industry Buzz
Effects: Purchasing, Allocation,
S T R A T E G Y 2
“Marketing and sales leaders need to develop
complete pictures of their customers so they can
create messages and products that are relevant to
them. Our research shows that personalization
can deliver five to eight times the ROI on
marketing spend and lift sales 10 percent or
more” (Forbes)
8. SAVE UP TO 30% ON HUNDREDS
OF HOLIDAY GIFTS
HOLIDAY DECOR
9.
10. K E Y D R I V E R S /
M E T R I C S T O C O N S I D E R
Bounce Rate
• Rate decreases: Marketing strategy is successful which we can use to support our
findings.
• Rate increases: We will need to reevaluate which metrics to consider moving forward
seeing as this is reason to believe there is oversight on our part.
Unique Buyers
• If this metric increases it is indicative of our conversion rate increasing, this can be
attributed to a successful promotional strategy or adequate buying levels that drives
consumers to checkout.
Abandonment Rate
• We hope to see a noticeable decrease in percentage (~5%) of cart abandonment once
we roll out our A|B testing for offers at checkout as well as popups on homepage.
Conversion Rate
• We hope that conversion rate will increase with the added traffic however we will have to monitor this portion with each quarter to
see how our customers are behaving.
F O R C O N S I D E R A T I O N …
•Time On Site
•Visitor Recency
•Traffic/Traffic Sources
•Customer Demographics
•Value Per Visit (VPV)
•Cost Per Visit (CPV)
11. UNIQ UE V ISITO RS
0
55,000,000
110,000,000
165,000,000
220,000,000
2012
2013
2014
2015
2016
Unique Vistors
Trending
UNIQ UE BUYE RS
0
1,750,000
3,500,000
5,250,000
7,000,000
2012
2013
2014
2015
2016
Unique Buyers
Trending
S A L E S
$0
$200,000,000
$400,000,000
$600,000,000
$800,000,000
2012 2013 2014 2015 2016
Fiscal Year
Trending
SESSIONS VS.
DIRECT SESSIONS
0
100,000,000
200,000,000
300,000,000
400,000,000
2012
2013
2014
2015
2016
Sessions
Direct Load Sessions
BOUNCE RATE
0%
6%
12%
18%
24%
2012
2013
2014
2015
2016
Fiscal Year
18.9%
20.9%
23.8%
21.7%
23.8%
P R O J E C T E D I N C R E A S E F O R 2 0 1 6
Year Sessions Direct Load
Bounce
Rate
Unique Visitors Unique Buyers Sales Items Ordered Orders AUR AOV
Conversion
Rate
$/Visit Product Page Views
Abandonment
Rate
2 0 1 6 1 7 9 , 2 7 4 , 9 7 0 8 9 , 0 3 4 , 0 4 1 2 0 . 9 % 1 1 2 , 2 1 9 , 2 4 4 5 , 4 2 0 , 1 7 6 $ 7 1 7 , 1 0 9 , 8 0 5 2 4 , 9 4 0 , 7 8 2 7 , 5 2 5 , 8 5 5 2 8 . 7 5 9 5 . 2 9 4 . 2 0 % 4 . 0 0 4 1 9 , 1 7 8 , 7 8 0 7 0 . 2 %
Projected Data
for 2016
QUESTIONS?