Marketing Data Analyst – Toronto
About the candidate
Maggie has 10+ years solid experience woth marketing insights (Direct Marketing, Email, Web / Digital Marketing) covering:
Descriptive Analysis:
– Dashboarding KPI and OKR with Power BI / Tableau / Data Studio
– A/B testing hypothesis analysis
– Personalization maturity model
Diagnostic Analysis:
– Customer insights / Marketing funnel / Engagement / User path analysis with GA4 etc., to find opportunity and / or issues
– Campaign effectiveness analysis
Prescriptive Analysis:
– Customer profile (Cluster analysis etc.,) to design segmentation
– Customer behaviour (Time series) analysis
Predictive Analysis:
– Predictive model (Linear Regression model / Logistic model / Classification model etc.,) within Big Query to predict Key metrics (Response rate / conversion rate / customer spending pattern etc.,) for marketing activities
– Revenue gap analysis
• Demonstrated proficiency with large-scale relational database and associated tools –
– 14 years’ experience of SQL (SQL Server)
– 6 years’ experience of Google Cloud Platform (Google Sheet, Big Query, Google Drive etc.,)
– 6 years’ experience of Universal Analytics / Google Analytics 4 (3 yrs)
– 5 years’ experience of Bigquery Machine learning model to develop predictive model
– BI tools: Tableau Dashboard / Power BI / Data Studio
– Experience with R Programming Language (basic R, dplyr, statistic summary etc.,)
– Marketing automation tool: Eloquo
– 5 years’ experience of Salesforce CRM database
– 10 years’ experience of MS Office, Advanced Excel (Power Query / Power Pivot etc), MS PPT, MS Word etc.,
– 6 years’ experience of JIRA, Confluence
Experience:
– Designed and worked out data model in BQ, queried and built datasets and tables / views for dashboard.
– Worked out dashboard in Data Studio to track web / Acquisition / Email / Marketing Funnel feed-in / Paid Social /
Paid Search performance.
– Presented insights and market trend in client meeting.
– Designed QA process for analytical team to follow and make sure data presenting to the client is accurate and
reliable.
– Collaboration with Paid Strategists setting up campaigns in FB Ads / Google Ads:
– Designed standard UTM and give direction to paid team of how to set up campaigns correctly in platforms for
effective and accurate tracking.
– Worked with Data Engineers to debug in-house API data.
– Worked with Implementation team to debug GTM settings.
– Lead Marketing analytics work cycle from Description stage to Predictive Staget
– Defined OKR (Objective Key Result) and developed Descriptive dashboard for master website and various
campaigns in Data Studio (Looker) to present “what happened”.
– Checked out business dashboard as daily routine and flagged out the opportunity and risk. Interpreted the issue
from data language to business story and presented to the business team.
– Worked out Diagnostic analysis (OKR Trending, Correlation analysis etc.,), to evaluate campaign effectiveness,
opportunity / risk, and answered the question of “why it happened”.
– Based on diagnostic result, developed Prescriptive analysis (waterfall chart etc.,) and recommendation on
marketing effort (“What should we do”)
– Based on business decision, worked out Predictive analysis with Big Query Machine learning model to define
targeted customer segmentation / customer spending etc., for marketing effort.
– A/B testing and Personalization Strategy:
– Developed Personalization Maturity Model to define the status quo of personalization practise, discussed with
client on the next move.
– Worked with Data Engineer to set up personalization criteria in Ninetailed platform. Tested and reviewed the result.
– Lead the analytic related data teamwork:
– Developed various pre / post analysis into different marketing activity stage to build up “Data-driven” and “Critical
thinking” culture in analytical team.
– Designed data model in Big Query and worked with Data Engineer to export the data from CDP (Customer Data
Platform) to Big Query for dashboard.
– Established Data Warehouse for marketing analytics in Big Query for analytical use.
Worked out measurement plan for paid tactics tracking, including paid social (FB Ads), paid search (Google
Ads) / Bing, and Mega Search (Derbysoft).
– Set up and audited Google Analytics 4 accounts for new products, set up standard GA4 report for stakeholders.
– Designed and set up date integration from different data sources ( GA4 / FB Ads / Google Ads / Bing etc.) in ETL
tool (Funnel.io) and exported to Big Query to build data warehouse.
– Worked with IT implementation team to standardize the parameters in data layer and event tagging process in
GTM to make sure the consistency in GA4 tracking across marketing digital event.
– Worked with project managers to adjust the working process of analytical team to ensure the productivity and
smooth communication with client.
– Set up dashboard QA process for the analytical team to ensure the quality of deliverables to client.
– Deeply involved in Marketing campaigns. Worked with Marketing Campaign / Digital Marketing team to design
campaign strategy, optimize campaign execution:
– Review campaign result with marketing managers, went thought KPIs, best practice, and learning lessons. Came
up with demand generation strategy / campaign tactics for this year (i.e. budget, targeting audience, set up
audience panel for test / control / volume, to do and not to do etc.,)
– Developed data plan based on campaign strategy (i.e. audiences inclusion and exclusion, interaction between
campaigns to avoid over-contact to the audience and ensure best customer experience, etc.,). Worked in
BigQuery / R to prepare the data.
– Used BigQuery Machine Learning packages to develop predictive model on customer response rate to every
specific campaign, as well as campaign series on quarterly / yearly basis. Chose the right audiences based on
the predictive model to maximum the revenue.
– Worked out Power BI and Data Studio dashboard to track the daily result during campaign period, including
related sales and marketing activities, revenue generation channel, conversion rate, ROI up-to-date etc., Sat
down with campaign managers to go through the KPIs and make sure the business questions are well answered.
Flagged the potential risk when the numbers show abnormal and discussed with campaign managers to adjust
the strategy.
– Developed a wrap-up deck of in-depth analysis in about 3-4 month after the campaign lunched in order to present
the insight of financial figures (including marketing P&L, cost management etc.,), as well as the success of
campaign strategy / tactics.
– Worked with Customer Marketing team on Customer Conversion / Retention projects:
– Worked with business owners (i.e. Marketing / Product team) to design KPIs / tracking metrics for each specific
digital campaign, and worked independently to collect, compile, analyze the data to make business
recommendations to the management team. i.e. Landing page or Email A/B testing, First Time User Campaign,
Leads Generation Campaign, In Product Usage, 3rd Party Application Usage, Effectiveness for Marketing Events
etc.,
– Worked out the dashboards to present the success of the campaigns by using advanced Tableau skill, SQL Query
(DbVisualizer / Alation), Eloquo, Omniture etc.,
– Provided business insights and presented to marketing / product / management team to help them make strategic
business decision.
– Worked with Project Managers and third party agency to design campaign strategy, and worked with IT developers
on tagging to make sure sufficient and accurate data is tracked to generate meaningful business insights.
– Worked with Campaign operation team on tracking campaign result in Eloquo to make sure campaign strategy is
executed as expected.
– Conducted end to end comprehensive web analytic package for Save.ca:
– Designed and defined the KPIs to measure the web traffic (page view, sessions, users, unique purchase, value,
saving, conversion rate by different source / campaign / channel / device / segmentation etc.,) and transaction
metrics (leads, order, unit, revenue, margin etc.,).
– Determined the reliable data source and dig the logical data set from Impala SQL and Google Analytics.
– Presented meaningful data chart, index graph, business insights and provided recommendations to executive team.
– Designed and conducted various reports and analysis to track the Loyalty Campaign Effectiveness, including Online
and Offline, to make sure the management team has a clear view on the loyalty campaigns.
– Worked out Digital Campaign effectiveness analysis: Email campaign, Digital Initiatives, Online Traffic, Landing Page
Summary etc., to provide the actionable recommendation and support strategic decision.
– Created the new analysis to monitor the customer activities (Purchasing Behavior, Purchasing Frequency,
Engagement Tier, Redemption Activity), flagging the business opportunity and risk to the management team and
recommend the proper solution.
– Provided regular reports and analysis of customer segmentation / profile to track the customer pattern change and
make sure the marketing strategy get aligned with the changes.
– Actively monitored and analyzed the performance of acquisition and retention campaigns, and provided thoughtful
recommendations on how to remove obstacles and improve performance.
