In December 2015, Cynthia Wright, a vice-president at Skyrose Marketing Agency (Skyrose), had just finished reviewing a summary of her team's performance for the past year. As head of the group responsible for beverage industry clients, she had led her team of four associates to achieve excellent results in revenue generation and client satisfaction. Despite these successes, she was determined to develop a plan for the upcoming year that would enable her to better manage her team while still delivering results. Wright noted that in the past year, her team's quality of life had suffered as she worked to grow her client book, particularly due to the cyclical nature of the marketing business. Around peak times, such as the holidays, her team members became overwhelmed both from completing projects for existing clients and generating new clients by responding to numerous requests for proposals. Wright was eager to devise a method for smoothing out the workload between peak and quiet periods of the year by better forecasting her clients' needs ahead of time. Specifically, she was planning to implement the new technique Google Trends, a database of search trends that spanned the past decade and that could be used to proxy consumer interest in different products. Wright believed that by forecasting consumer interest, she could predict demand from her clients, whom she anticipated would engage her firm to capture this consumer interest. As a result, Wright would be able to address two key problems. First, staffing decisions and firm resource allocation could be predicted ahead of time, giving her team members time to prepare for upcoming projects. Second, Wright could deliver better results for her clients by anticipating the timing of consumer demand and developing marketing plans around these timelines. Wright planned to use the upcoming calendar year as a trial for the Google Trends approach for forecasting demand. To test its efficacy, she would assess its influence on three key clients: Vintage Vino, On The Rocks Whiskey, and Downtown Brew Co.

THE BEVERAGE CLIENTS GROUP

Skyrose's staff members consisted of four associates plus Wright. Each associate had several years o experience in marketing or advertising. They were all well-versed in the beverage products marketing market segment. The team's work could be generally divided into two functions: (1) gaining new business by networking and responding to requests for proposals from potential new clients, and (2) maintaining recurring business by completing projects for existing clientsAlthough many ongoing projects had to be completed under a time-sensitive schedule, some functions such as networking, project preparation, and relationship building with old clients could be completed at any time throughout the year. Wright compiled all employee work hours from the previous year (see Exhibit 1).

CLIENTS Wright was planning to implement this initiative with three key companies: two current clients (Vintage Vino and On The Rocks Whiskey) and one prospective new client (Downtown Brew Co) Vintage Vino, a Canadian wine producer and distributor, had been working with Skyrose for the previous three yearsAs a leader in the wine market segment, the company was planning the release of a new white wine in the upcoming year. However, the company was unsure when exactly to release the new product to maximize sales. On The Rocks Whiskey was a Vancouver-based distributor of whiskey that worked closely with producers throughout the country to source the best products for consumersThe company had seen incredible success in sales in the previous year and credited this growth partially to the work of Wright and her team. As a loyal client, On The Rocks Whiskey was likely to seek direction from Skyrose on upcoming industry and consumer trends. Downtown Brew Co. was a rising star in the craft beer industry. As Wright was recently informed, the company was planning to expand its presence from Ontario to various other Canadian provincesThe company was not currently a Skyrose client, but Wright had a strong desire to win Downtown Brew Co.'s businessThe company was experiencing exponential growth and would likely be looking for a marketing agency in the upcoming year.

GOOGLE TRENDS Google Trends was a database that tracked search queries and the relative popularity of queries over t The online platform contained data from 2004 onwardIt contained search trends that could be segmente geography and timedown to minute-by-minute results (see Exhibit 2)A specific period of Google Tr data could be exported, with search data scaled relative to the highest search volume within that time fra The Google Trends database had shown great promise for numerous applications in the pastIt was even to make predictions about influenza outbreaks, in an attempt to slow the spread of the flu virus.2 Although Wright had never personally used Google Trendsshe had read about the impressive applicatio ofthistool1

Year	Month	Relative Interest
2010	1	6
2010	2	9
2010	3	15
2010	4	12
2010	5	17
2010	6	17
2010	7	12
2010	8	14
2010	9	14
2010	10	18
2010	11	13
2010	12	12
2011	1	11
2011	2	14
2011	3	22
2011	4	22
2011	5	43
2011	6	22
2011	7	21
2011	8	22
2011	9	27
2011	10	20
2011	11	18
2011	12	25
2012	1	24
2012	2	25
2012	3	34
2012	4	31
2012	5	48
2012	6	35
2012	7	37
2012	8	38
2012	9	32
2012	10	28
2012	11	31
2012	12	34
2013	1	32
2013	2	43
2013	3	49
2013	4	52
2013	5	67
2013	6	51
2013	7	50
2013	8	49
2013	9	55
2013	10	51
2013	11	51
2013	12	56
2014	1	52
2014	2	57
2014	3	61
2014	4	74
2014	5	89
2014	6	64
2014	7	68
2014	8	70
2014	9	71
2014	10	69
2014	11	61
2014	12	67
2015	1	55
2015	2	78
2015	3	76
2015	4	90
2015	5	100
2015	6	77
2015	7	79
2015	8	84
2015	9	75
2015	10	66
2015	11	66
2015	12	70

Year	Month	Relative Interest
2010	1	41
2010	2	42
2010	3	44
2010	4	41
2010	5	39
2010	6	36
2010	7	39
2010	8	39
2010	9	39
2010	10	40
2010	11	43
2010	12	55
2011	1	52
2011	2	51
2011	3	52
2011	4	48
2011	5	47
2011	6	49
2011	7	49
2011	8	46
2011	9	49
2011	10	52
2011	11	60
2011	12	73
2012	1	60
2012	2	55
2012	3	60
2012	4	52
2012	5	58
2012	6	59
2012	7	56
2012	8	53
2012	9	55
2012	10	55
2012	11	65
2012	12	84
2013	1	69
2013	2	65
2013	3	67
2013	4	59
2013	5	58
2013	6	61
2013	7	61
2013	8	63
2013	9	57
2013	10	66
2013	11	73
2013	12	90
2014	1	71
2014	2	66
2014	3	73
2014	4	66
2014	5	66
2014	6	65
2014	7	67
2014	8	66
2014	9	65
2014	10	72
2014	11	84
2014	12	98
2015	1	74
2015	2	69
2015	3	73
2015	4	65
2015	5	66
2015	6	67
2015	7	67
2015	8	69
2015	9	63
2015	10	65
2015	11	87
2015	12	100

Year	Month	Relative Interest
2010	1	54
2010	2	54
2010	3	58
2010	4	52
2010	5	61
2010	6	59
2010	7	67
2010	8	64
2010	9	56
2010	10	50
2010	11	65
2010	12	74
2011	1	73
2011	2	72
2011	3	66
2011	4	63
2011	5	67
2011	6	72
2011	7	79
2011	8	72
2011	9	66
2011	10	67
2011	11	72
2011	12	83
2012	1	77
2012	2	78
2012	3	71
2012	4	69
2012	5	74
2012	6	84
2012	7	83
2012	8	73
2012	9	77
2012	10	65
2012	11	78
2012	12	86
2013	1	77
2013	2	77
2013	3	72
2013	4	69
2013	5	73
2013	6	79
2013	7	80
2013	8	79
2013	9	71
2013	10	67
2013	11	83
2013	12	91
2014	1	82
2014	2	77
2014	3	68
2014	4	70
2014	5	74
2014	6	79
2014	7	83
2014	8	73
2014	9	68
2014	10	63
2014	11	77
2014	12	84
2015	1	81
2015	2	74
2015	3	72
2015	4	68
2015	5	76
2015	6	76
2015	7	84
2015	8	81
2015	9	72
2015	10	70
2015	11	83
2015	12	100

1. Why is Wright choosing to use Google Trends data? What insights can this data set provide to help her manage her team? (Explain how useful the Google Trend data is and whether using search trends as a proxy for sales is valid.) 2. Which months have the highest search volumes for each of the three key products: white wine, whiskey, and craft beer? (Run a descriptive analysis on the data set for each product and discuss the behaviour of the data) 3. Which time series modelling techniques are the most appropriate for the data sets? (Compare different forecasting models, tested on each product data, based on the accuracy factors learned in our course. Use the methods covered in our course) 4. What do your forecasted search volumes imply for wright and her team in 2016? What can she do to plan for the upcoming year, based on the findings from your model? should she use Google Trends in the future to optimize her teams workload