20 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.
You’ll split time between data work, meetings, and creating materials. Morning might be checking market-monitoring tools and dashboards for changes in sales, competitor moves, or consumer trends. Afternoon often goes to running or reviewing surveys, analysing results with statistical tools, and writing short reports or slide decks for managers.
Evenings or the end of the day usually means updating task boards (Asana), prepping presentations in Canva, and sending action items to sales or product teams based on the day’s findings.
Start with Asana and Canva. Asana handles daily project tracking and coordinating survey interviewers; knowing it helps you run research projects and show status to managers. Canva makes quick visuals and slide decks for stakeholder presentations.
Next learn basic SQL and how to query Amazon Redshift or Apache Hive to pull customer or sales data. You don’t need deep database admin skills, just writing SELECT queries and joining tables to measure trends.
Use AI to draft survey questions, summarise findings, or create visuals, but always verify. Check that AI-generated survey wording is unbiased, matches your sampling plan, and doesn’t lead respondents. For analysis, validate AI summaries against your statistical outputs.
Never share raw personal data (names, emails, exact customer IDs) with public AI chat tools. Keep data queries and storage inside your company systems like Redshift or Hive, and follow your company’s privacy rules.
You’ll regularly handle percentages, sample sizes, conversion rates, and time-series data. Typical tasks: compute change in market share (percentage points), survey sample sizes (hundreds to thousands), and week-over-week sales growth (percent).
You might pull sales tables from Redshift or Hive and produce charts showing monthly or quarterly trends, with clear metrics like a 3% drop in conversion or a 25% spike after a campaign.
Begin by learning basic statistics (mean, median, standard deviation, confidence intervals) and survey design basics. Build simple projects: design a short survey, run it with 100 responses, analyse results in Excel or Python, and make a Canva presentation.
Practice using Asana to plan the project and try querying a sample dataset in Redshift or Hive (many companies provide sandbox data). Show these projects in interviews instead of claiming theoretical knowledge.
A Business Development Executive here focuses on researching markets, assessing demand, and making positioning recommendations. You build surveys, track competitor activity, and present findings to stakeholders. You don’t close deals like a sales rep.
Product managers decide product features and roadmaps; they use your research as input. You provide data and recommendations; product managers and sales turn those recommendations into action.
Necessary: clear written communication (you’ll prepare reports and presentations), basic statistics for analysing survey and sales data, and comfort with Asana and Canva for project work and visuals. You must also know how to design a simple survey and interpret results.
Learnable on the job: advanced SQL for Redshift/Hive, sophisticated data engineering, and building new research techniques. Employers often train you on company data schemas and advanced tools once you show initiative and basics.