Marketing Analytics of Shopping Mall Paid Search

Introduction

This project aims to fulfil the requirement to finish Pacmann’s Bootcamp in business analytics. A Case observed in this project is related to marketing analytics. It is about a shopping mall paid search Campaign. The digital era has shaped the entire market industry to migrate to online platforms so customers can easily access various products beyond the border. Paid search is one of the most efficient ways to promote merchant products or services. Companies compete to get the best keywords on the first Google search page.

To be able to survive in a competitive market, a business must be able to utilize the data they gather to make a data-driven action that can be beneficial for the company. Therefore, as a data analyst, exploring data, finding solutions to problems, and producing actionable insights are superior skills that must be possessed.

Background

A campaign ads project in an online shopping mall involves creating persuasive advertising materials to promote a product or service to online shoppers within the shopping mall’s website or app.

Overall, a successful campaign ads project in an online shopping mall requires a deep understanding of the audience, clear objectives, a solid creative concept, effective placement of advertising materials, and continuous monitoring and evaluation. Through this project, a dashboard is created to gain business insights to evaluate and make actionable decisions.

Problem Statement

A dashboard is subject to the user, who is a marketing manager. As a marketing manager, several tasks have been given, such as:

1. Evaluate the awareness.
2. Monitor generated traffic through the campaign.
3. Find best-performing ads.
4. Evaluate marketing cost.

Goals

To tackle the problems, a dashboard is built up to help assess the campaign performance & create an actionable plan

User Persona

User Persona

A given picture above depicts the user persona and its associated tasks. A dashboard is primarily subjected to the marketing manager, who is responsible for making decisions. However, it is not limited to employees in the marketing division because a proper discussion in the division should be conducted. In addition, the group must know its performances.

User Flow

User Flow

The dashboard’s user flow shows in the picture above. A summary and comparison of ad types can be reviewed by the marketing manager. Moreover, the interactive dashboard can satisfy users’ need to gain business insights.

Dataset Explanation

Dataset

The dataset is a real dataset contanining data of a 2021 5 months paid search campaign of a Us shopping mall (that for privacy reasons for this project the name has been anonymized) promoting through paid search coupons and promo codes (Link). The dataset consists of following columns, such as:

1. Ad Group: category of the advert (coupon/promo code, desktop ad/mobile ad etc…)
2. Month: month of the campaign (July — November 2021).
3. Impressions: metric used in digital marketing to quantify the number of digital views or engagements of an advertisement. Impressions are also referred to as an “ad view.
4. Clicks: how many clicks the ad received
5. CTR: Click Through Rate, the number of clicks that your ad receives divided by the number of times your ad is shown: clicks ÷ impressions = CTR.
6. Conversions: Conversions are those valuable actions that users take on your site like buying something or filling in a form. The success can be measured in the number of conversions generated at a particular cost.
7. Conv Rate: Conversion Rate. It is the percentage of people who convert after clicking on your ads. Depending on your goals, a conversion may mean they make a purchase, complete a contact form, request a free trial, or take another desired action.
8. Cost: Cost is the actual money spent by the advertiser (the “shop”) for the related ad group.
9. CPC: Cost Per Click, it is the cost of the specific ads divided by the click. It is one of the metrics used to evaluate the effectiveness of the campaign in terms of ROI (Return on Investment), therefore a low or decreasing CPC is better than a high or increasing CPC.
10. Revenue: Revenue is the total amount of income generated by advertisment.
11. Sale Amount: Sale Amount for this dataset means the quantity of sales derived by the single ad group.
12. P&L: Profit and Loss, based on the formula Revenue — Cost. For this dataset mesaures the profit of the specific Ad Group.

Dashboard Explanation

Tableau Dashboard

The dashboard can be accessed through this link. The picture above shows what the dashboard looks like. It consists of four filters: month, ad type, device type, and coupon. Several metrics, such as total click, CTR, conversion, conversion rate, and profit & loss, can be evaluated. It is associated with bar charts as well.

Dashboard Insights

Awareness:

Awareness

1. The highest impression reached its peak in November
2. 1:1 was the Ad type that enhanced the highest awareness, followed by Exact & Phrase, respectively
3. It was linear with its CPM, which was 1:1 ad type was the highest
4. September had the lowest impression of all types of Ads

Traffic Generations:

Summary in November

1. The highest total clicks reached their peak in November
2. Exact was the Ad type that enhanced the highest CPC, followed by 1:1 & Phrase, respectively
3. September had the lowest total clicks for all kinds of Ads

Best Performing Ads:

Best Performing Ad (in Sales)

1:1 had consistenly generated the highest sale amount within July — November 2021 followed by Exact, and Phrase respectively.

Cost Evaluation:

Profit & Loss

Overall, during a 5-month period, the company had suffered a loss. October was the only month that generated net profit. However, the marketing cost was still beyond its revenue.

Conclusion

From the dashboard, we can conclude:

1. Awareness showed a potential prospect. There was a significant ad types utilization to gain impressions
2. CTR performed around 30%
3. Conversion rate had performed less than 10 %
4. 1:1 had consistently generated the highest sale amount
5. Surprisingly, in terms of net profit, exact performed better. 1:1 suffered an excessive loss despite having the highest revenue
6. Marketing costs should be reduced, and maximize revenue by cutting discounts/coupons gradually. During 5-month, the company had a loss of 73K USD