Data Analysis For Sales Forecasting And Business Optimization

Dataset

In the recent past there have been growing interest for the E-commerce sector of business operations partly due to its non-geographical restrictions and also for its security and ability to reach a wide range of customers despite their location.

Consequently, the interest has brewed competition between old players and new entries into the business. Infinity company is an e-commerce company that specialized in supply of Electronic products as well as other major products. The company has a range of other products with reputable brands in clothes, household commodities, toys, and gadgets. The electronic line of goods dealt with are:

• Samsung electronics
• Microsoft products (laptops and accessories)
• LG appliances
• Hp computer products and accessories
• Sony Home entertainment products
• AUCMA electronics
• Apple mobile and computer appliances
• Techno mobile phones and accessories

The recent concern of declining of sales expressed by the executive has bee attributed to new competition as well as shift in consumer preference across the business regions. The new development therefore prompts for new methods of business approaches, even better, the innovation and adoption of suitable business methods

For our analysis we need to:

1. Examine sales patterns of the previous business years
2. Examine the relationship between the sales and current business patterns

• Propose new methods of business sales promotion

To enable us explore all the aforementioned problems, we will use data classification to explore relationships and regression to predict sales, given new business practices.

The data for this study was obtained from the sales department and the financial records department for the past three years. The entries available from the data are as in:

Variable description	Size	Denotation/ measure
Product	1386	Ø Samsung electronics Ø Microsoft products (laptops and accessories) Ø LG appliances Ø Hp computer products and accessories Ø Sony Home entertainment products Ø AUCMA electronics Ø Apple mobile and computer appliances Ø Techno mobile phones and accessories
Shipping method	1386	Paid- P Free- F
Sales recorded	1386	AUS dollars
Geographical region	1386	Asia America Europe Australia Other parts
Number of customers	1386	unspecified
Price of product	1386	AUS dollars
Customer type	1386	New- N Existing- E
Advertisement	1386	AUS dollars

For our classification method we employed logistic regression and explored the relationship between data variables. We use logistic regression in examining how sales are influenced by shipping methods, also how sales are spread across the marketing regions for the company. Moreover, we will determine the interrelationship between the independent variables and the response variable. According to an article on logistic regression by NCSS (2016), “Logistic regression analysis

studies the association between a categorical dependent variable and a set of independent (explanatory) variables.” We used linear regression for predictive modelling to predict the sales given different practices, for instance, how adoption of product promotion methods such use of more sales persons and advertisement would impact the sales recorded.

Use of forecasting in determining how different variables of interest are likely to play out following a positive or negative variation of the variables against a response variable will enable the company to near-accurately forecast on how the sales will be made if we adopt different marketing methods and exportation of given good. For instance through forecasting we determine how selling of related products together are likely to affect total sales.

Product	Price (AUS dollars)	Cost of Advertisement	Customers	Sales (AUS dollars)
APPLE	1335055	1318993	6086	3054878.0
AUCMA	1614704	1566711	6839	3206451.0
HP	8580	7363	29	5172.0
Hp	1317170	1239529	6883	3570759.0
LG appliances	1462941	1483838	7050	3327564.0
Microsoft electronics	1364818	1293901	6653	3281120.0
Samsung	1482765	1568058	7652	3531831.0
Sony	1386320	1386847	6648	3157285.0
Techno	224344	266384	848	0.0

From our statistics we deduce that the highest sales were recorded for Samsung electronic appliances at 3531831.0 AUD while the least sales were by Techno mobile at 0.0 AUD. This indicates that there was variance in the records made by the different products. Additionally, the cost of advertisement incurred by the company was such that promoting Samsung products had the highest revenue allocation while HP and Techno had the least revenue allocated for advertisement.

Classification and Regression Analysis

The total sales for monthly sales preceding our analysis recorded were at AUD 23,135,060.

Export Region	Price (AUS dollars)	Cost of Advertisement	Customers	Sales (AUS dollars)
Africa	2317687	2308667	10780	4921036.0
Australia	2015194	2002658	10372	4516548.0
Europe	1963479	1890778	9592	4787998.0
North America	3900337	3929521	17944	8909478.0

The highest sales were recorded from exports to North America at AUD 8909478.0 while the least were recorded from Australia at AUD 4516548.0, Africa was second with sales of AUD 4921036.0 while Europe had sales of AUD 4787998.0. Also the cost of advertisement in relation to regions were such that advertisement in North America were the highest followed by Africa and Australia while the least advertisements were done in Europe. Therefore for the business to ensure more sales, it should export more to North America where we have the largest market.

Product	Export Region	Price (AUS dollars)	Cost of Advertisement	Customers
APPLE	Africa	331337	329349	1608
APPLE	Australia	218470	218124	1100
APPLE	Europe	129908	170510	607
APPLE	North America	655340	601010	2771
AUCMA	Africa	351519	320429	1420
AUCMA	Australia	327375	337103	1489
AUCMA	Europe	343520	296816	1610
AUCMA	North America	592290	612363	2320
HP	North America	8580	7363	29
Hp	Africa	283226	246200	1370
Hp	Australia	273359	277508	1498
Hp	Europe	285316	303365	1616
Hp	North America	475269	412456	2399
LG appliances	Africa	310420	315892	1340
LG appliances	Australia	324535	307948	1676
LG appliances	Europe	309128	285657	1635
LG appliances	North America	518858	574341	2399
Microsoft electronics	Africa	311746	260592	1192
Microsoft electronics	Australia	286825	287213	1664
Microsoft electronics	Europe	347178	279859	1377
Microsoft electronics	North America	419069	466237	2420
Samsung	Africa	294825	365183	1914
Samsung	Australia	268159	273902	1395
Samsung	Europe	301610	289465	1596
Samsung	North America	618171	639508	2747
Sony	Africa	316442	336276	1539
Sony	Australia	296485	279021	1403
Sony	Europe	246819	265106	1151
Sony	North America	526574	506444	2555
Techno	Africa	118172	134746	397
Techno	Australia	19986	21839	147
Techno	North America	86186	109799	304
Product	Export Region	Price (AUS dollars)	Cost of Advertisement	Customers

From our analysis of the performance of different products in different regions we found out that:

	Price (AUS dollars)	Cost of Advertisement	Customers	Sales (AUS dollars)
count	32.0	32.0	32.0	32.0
mean	318646.78125	316613.25	1521.5	722970.625
std	154355.9865783103	152344.73382155778	709.3730080261928	384421.32040037913
min	8580.0	7363.0	29.0	0.0
25%	272059.0	263977.5	1303.0	591527.75
50%	309774.0	293140.5	1518.5	710760.0
75%	348263.25	344123.0	1735.5	843049.25
max	655340.0	639508.0	2771.0	1462076.0

The average cost of advertisement was 316613.25, the average number of customers across the trade regions was 1521 while the averages of sales and total cost of the products was 722970.625 and 318646.78125 respectively. Elsewhere the individual products played across the regions as from table-4 above.

Product	Customers	Sales (AUS dollars)
AUCMA	6839	3206451.0
Samsung	7652	3531831.0
LG appliances	7050	3327564.0
Sony	6648	3157285.0
Microsoft electronics	6653	3281120.0
APPLE	6086	3054878.0
Hp	6883	3570759.0
Techno	848	0.0
HP	29	5172.0

Samsung had the most customers with the highest number of sales as well, techno had 848 customers with no sales recorded whereas HP had the least customers (29) with a sales of 5172.0.

From our analysis the company exports more of Samsung products, it will be able to increase its sales.  

	Price (AUS dollars)	Customers	Sales (AUS dollars)
count	1131.0	1131.0	1131.0
mean	9015.64721485411	43.04862953138815	20455.402298850575
std	6840.105141136656	30.01233264763024	9701.732328385526
min	508.0	3.0	5152.0
25%	4222.5	21.0	12366.0
50%	7924.0	33.0	19812.0
75%	12197.0	63.0	28375.0
max	46813.0	203.0	70750.0

Advertisement had an effect of causing an average increase of AUD 20455.40 therefore there was a relationship between the sales and and the cost of advertisement. The company can utilize advertisement as a means of promoting sales volumes through increasing the advertisement budget.

shipping Method	Price (AUS dollars)	Cost of Advertisement	Customers	Sales (AUS dollars)
Free	5150372	5250000	25323	11961382.0
Paid for	5046325	4881624	23365	11173678.0

Higher sales were recorded when free-shipping was used for the purchases made I.e. 11961382.0 compared to the sales for which shipping was paid for at 11173678.0. From the analysis of shipping method, we conclude that for the company to ensure return customers and also increase of sales, it should adopt measures such as free-shipping and other product promotion incentives.

Using regression we find out that there is a relationship between the geographic regions in which the company conducted business. For instance from earlier tables we inference that North America and Africa comprise the company’s product market, therefore the company should purpose to prioritize the two market spaces so as to ensure more sales. Therefore, using forecasting we can view how varying the company sales is more likely to play out owing to the current statistics and we can project the probable sales through prioritizing company sales.

From the data analysis exercise we make the following recommendations for consideration by the executive:

1. The company should prioritize sales to North America and Africa mostly. As well as considering employing of methods to curb competition from home firms in Australia so as to increase sales. This can be through exploiting the avenues through which the local consumers can make more purchases, including more supply of popular electronics brands.
2. The company should offer free shipping for every purchase made by both new and existing customers, this will help foster a relationship and ensure more return purchases.

• The company should drop redundant products such as Techno products and concentrate on more sales generating products

1. Given our analysis results, business methods such as more advertisement revenue would ensure more use of new methods of advertisement such as celebrity endorsement, free sampling, use of agents and more in order to increase product awareness which will subsequently increase the sales volumes
2. Also the company should try the affiliate sales program, where there are referrals by interested independent marketers who gain commission through sales made by their referrals. This would be an excellent method to get new customers to buy our products due to the enormous potential of affiliate marketing 

Below we recommend the best method through which the company can ensure that the recommendations are productive after implementation if the executive adopts the recommendations, then the sales department can anticipate more sales in the coming financial year. The implementation plan includes:

1. Set the minimum export volumes to the regions at a value of USD500,000 with a plan of varying them with a ratio of the scale 0.10 on the current ratio, such that first the measure of the sales at the end of the coming financial year is recorded and the executive determines whether the current sales increase projection ratio is low or should be modified or maintained
2. Adopt a mechanism to ensure the optimal revenue for advertisement purposes is set aside such that we do not over advertise or under advertise, this will serve the purpose of both checking the overall expenditure and ensure increased product awareness

• The sales department should adopt free samples, affiliate marketing, and use of coupons as a measure of advertising. Affiliate marketers can be found through use of websites and referral advertisement by bloggers and interested parties.

Conclusion

In conclusion, we have found out that, as time changes methods of business conducting change too, in a way we can say they are linearly related. In order to ensure the firm’s sustainability, the executive ought to employ methods that ensure the company evolves with time. One of the best measures against which the firm can program itself to adapt with change is through data analysis. Data analysis provides means through which the company can gain insights on the performance as well as gauge its sustainability prospects through factors such as how much profits it generates.

Even more interesting is the role of data analysis in business intelligence and decision making. Generally, data is key to better decisions and eventual growth of business and ought to be fully adopted. 

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