Analytics Assistant
Analytics Assistant in e-commerce: collects and validates data for reports, updates dashboards, reconciles metrics across systems, and prepares extracts for analysts and marketing.
What a Analytics Assistant does
Analytics Assistant is a junior analytical role responsible for the quality and accessibility of data for online store teams. The role pulls exports from the CRM, order platform, ad accounts and analytics systems, checks them for completeness and duplicates, and keeps regular reports and dashboards up to date. In e-commerce, decisions on purchasing, pricing, promotions and traffic budgets depend on this work, so a discrepancy of even a few percent can be costly.
The role appears in teams that have an analytics or product analytics function, but where senior analysts are overloaded with non-routine tasks. The assistant takes on the routine part: daily and weekly reports, tracking checks after releases, preparing tables for A/B tests and doing first-pass analysis of anomalies. They usually report to a Lead or Senior Data Analyst and work closely with marketing, the ecommerce manager and development on operational questions.
For the company, this is a way to get a reliable data layer quickly without hiring an expensive specialist for every task. The assistant does not make strategic decisions, but their accuracy determines how much analysts and managers trust the numbers.
Responsibilities
- Regularly update reports on sales, revenue, average order value, conversion and returns using agreed templates
- Collect exports from the store platform, CRM, email systems and ad accounts and bring them into a single structure
- Reconcile metrics across sources: orders in the admin panel, analytics data, payment reports and accounting exports
- Verify tracking accuracy after releases: add-to-cart, checkout and purchase events
- Find duplicates, gaps and anomalies in data and report them to data source owners
- Maintain dashboards: update filters, labels and sources, and remove outdated widgets
- Prepare data for A/B tests: extracts by group, traffic split checks and basic calculations
- Maintain metric documentation: definitions, sources and calculation rules
- Answer routine data requests from colleagues and escalate complex questions to the senior analyst
- Take part in regular team meetings and log tasks for improving data quality
Skills
- Confident use of Excel or Google Sheets: pivot tables, formulas, data cleaning
- Basic SQL: queries with filters, grouping and table joins
- Understanding of the e-commerce funnel and key metrics: CR, AOV, margin, LTV, returns
- Attention to detail and the habit of double-checking results before sending them
- Ability to explain data discrepancies in plain language to non-technical colleagues
- Basic understanding of the difference between correlation and causation
- Experience with task trackers and prioritizing parallel requests
- Clear written communication: short messages about a problem with an example and a conclusion
- Basic understanding of tracking, UTM tags and order attribution
Tools
- Google Sheets and Excel
- SQL client and access to a data warehouse (BigQuery, PostgreSQL or similar)
- Google Analytics or another web analytics system
- BI tools for dashboards (Looker Studio, Power BI, Tableau)
- Store CRM or admin panel for checking orders
- Jira, Trello or another task tracker
How performance is measured
- Share of reports delivered on time without manual corrections
- Number of discrepancies between sources found before the data consumer notices them
- Time from request to completed answer for routine tasks
- Share of tracking checks completed before campaigns launch
- Up-to-date state of metric documentation and dashboards
By vertical
E-Commerce
In an online store, the assistant most often works with orders, stock, returns and the funnel from catalog to payment. The core value of the role is making sure revenue, margin and conversion match across the admin panel, analytics and accounting, because purchasing and promotion decisions are made based on these numbers.
Levels
Junior / Entry
Junior-level work means completing ready-made tasks according to instructions: updating reports, running extracts and reconciliations, and finding simple errors. Decisions about which metrics to calculate and how to interpret results are made by the senior analyst, while the assistant is responsible for accuracy and timely execution.
How to get there
People often move into this role from adjacent positions: online store operations, order management, customer support with CRM experience, junior marketing, or a background in economics, mathematics or technical fields. What matters most is showing that you can work with spreadsheets, understand store business processes and are comfortable with numbers.
To get started, build confident skills in Excel or Google Sheets, then learn basic SQL and the key e-commerce metrics: conversion, average order value, margin, returns and LTV. It helps to understand how web analytics and UTM tags work, and to try building a simple dashboard from public or your own data. A portfolio of a few clean analyses is more valuable than certificates.
Growth comes from expanding your scope: moving from executing ready-made reports to independently checking tracking, analyzing anomalies and proposing improvements to data structure. A good sign of readiness for the next step is when the assistant spots problems before being asked and draws conclusions instead of just pulling numbers.
Next steps: Junior Data Analyst, Product Analyst, Marketing Analyst, E-commerce Analyst, Business Analyst
FAQ
How is an Analytics Assistant different from a Data Analyst?
The assistant mainly executes tasks based on ready-made templates: collecting data, updating reports and checking accuracy. A Data Analyst independently formulates questions, chooses analysis methods and draws business conclusions. The move usually happens when the assistant starts conducting independent analyses on a regular basis.
Is a university degree required for this role?
Formally it is often not required, but employers value an understanding of mathematics, statistics and logic. Much more important is the ability to work with spreadsheets and SQL and to show at least a few examples of your work. Experience in e-commerce or online store operations also helps a lot.
What knowledge is needed to start?
At minimum: confident Excel or Google Sheets skills, basic SQL, and an understanding of the online store funnel and core metrics. It is useful to know how web analytics, UTM tags and order attribution work. The rest is usually learned on the job under the guidance of a senior colleague.
What determines income in this role?
Income depends on the region, company size, the maturity of the analytics function, and how much SQL and BI tool work is required. Moving toward more independent tasks also has a significant effect, since it immediately raises the employer's expectations.
Are there any specifics for high-risk verticals?
In high-risk e-commerce, accuracy in returns, disputed payments and cancellations is often critical, along with reconciliation against payment reports. The assistant must understand that an incorrectly attributed or duplicated order can distort the picture for margin and budgets. Sometimes access to data is restricted by security and regulatory requirements, and these must be respected.
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