Subject: Marketing Analytics - Promotion Analytics

Introduction

You are the marketing analyst for (fictitious) Acme Restaurant. Acme serves organic, gluten-free dishes to discerning diners. Acme is particularly well known for its vegetable melee dish, garnished with red and green peppers, organic beets and artichoke hearts, served over a bed of spinach with spicy balsamic vinaigrette.

Acme Restaurant uses four promotion tools to generate marketing responses, which in turn drives new business to the restaurant:

-G: Google:Acme uses Google to guide web searchers looking for restaurants in the geographical area.

-M; Meta(formerly known as Facebook): Acme posts content on its business page, discussing special dishes at the restaurant.

-O: OpenTable:Acme uses OpenTable's solution for restaurant marketing, which includes a simple reservation app that Acme uses on its website.

-Y: Yelp:Acme works with Yelp to leverage positive reviews to generate new business for the restaurant.

Each of the promotion tools has associated effectiveness and cost values. Effectiveness values refer to the number of responses generated per campaign. Cost values refer to the cost that the tool charges Acme for each campaign.

Data: Effectiveness and Cost Values for Promotion Tools

Google: Effectiveness: 50; Cost 20

Meta (Facebook): Effectiveness: 40; Cost: 10

OpenTable: Effectiveness: 30; Cost: 10

Yelp: Effectiveness: 20; Cost: 20

The table below summarizes the data for effectiveness and cost:

Values	G: Google	M: Meta	O: OpenTable	Y: Yelp	Total
Effectiveness	50	40	30	20	$20,000/month
Cost	$20	$10	$10	$20	$20,000/month

You face several constraints. First, you are limited to a maximum budget of $20,000 per month. Second, you face labor resource constraints. In order to run each promotion tool, labor is required from the marketing manager, who prepares the ads, the marketing operations person, who runs the ads, and the marketing analyst, who measures the effectiveness of the ads. Your resources are limited to 40 hours per week, or 160 hours per month. For example, each Google ad requires 3 hours from the marketing manager, 4 hours from the marketing operations person, and 1 hour from the marketing analyst, with a total availability of 160 hours per month. The data below summarizes the constraints, showing the hours (hr) per campaign required for each of the promotion tools.

Data: Constraint on Budget

Budget: Maximum available for total marketing promotion effort: $20,000 per month.

Data: Constraint on Labor

Google:Marketing manager: 3 hr/campaign; Marketing operations: 4 hr/ campaign; Marketing analyst: 1 hr/ campaign

Meta: Marketing manager: 2 hr/campaign; Marketing operations: 2 hr/ campaign; Marketing analyst: 3 hr/ campaign

OpenTable:Marketing manager: 2 hr/campaign; Marketing operations: 3 hr/ campaign; Marketing analyst: 4 hr/ campaign

Yelp: Marketing manager: 3 hr/campaign; Marketing operations: 2 hr/ campaign; Marketing analyst: 1 hr/ campaign

Total for all hours per month for each resource not to exceed 160 hours/ month

The table below summarizes the data for labor resource constraints.

Resource	G: Google	M: Meta	O: OpenTable	Y: Yelp	Total Hr/Mo.
Marketing Manager	3	2	2	3	160
Marketing Operations	4	2	3	2	160
Marketing Analyst	1	3	4	1	160

Question: Develop the objective equation to maximize the number of total responses. Remember, you are selecting a mix of promotion tools to generate as many responses as possible from the promotion tools you have available. For the equations, use the letter G to represent Google, M for Meta, O for OpenTable, and Y for Yelp.

This is what I have so far:

X = Effectiveness; Y = Cost

G = Google; M = Meta; O = OpenTable; Y = Yelp

G = 50X + 20Y

M = 40X + 10Y

O = 30X + 10Y

Y = 20X + 20Y

Am I on the right track?