Do you need a data team? A checklist

The three paths

Brand teams that want better answers usually pick one of three paths.

Our comparisons go deeper on hiring a team and analytics software.

What a marketing data team needs, at minimum: someone to connect the data from your teams, partners and ad accounts; someone to analyze it and design tests; someone to read public conversation if that matters to you; and someone senior enough to turn findings into decisions. In a small team those can be two people. Rarely one.

It also needs time. Connecting sources, agreeing definitions and checking the first numbers takes months before anyone answers the question you hired them for.

The checklist

1. How often do you have questions? Every week, or a few a month?
2. Can you hire and keep analysts and data engineers in your market, at your pay range?
3. Who will manage them? Someone who can judge their work, not only their output.
4. Is your data already in one place, or spread across teams, partners and tools?
5. Do you need answers this quarter?
6. Does anyone on the team read dashboards today, or do they go unread?
7. Do you need to read conversation online as well as your own data?
8. Would a few slides with the answer on top be enough for your leadership?
9. Do your questions change with each launch, season or release?
10. Do you need to see across every team and partner?

How to read your answers

Mostly “weekly, yes, we have someone, it’s already in one place”: build the team. You’ll get value from people who live in your data every day.

Mostly “a few a month, not sure, no, it’s spread out”: get help first. You’ll get answers sooner, and you’ll learn which questions matter before you hire anyone to answer them.

Mixed answers are common. Some teams get help now and hire later, once the setup is running and they know what kind of person they need.

Two answers carry extra weight. If you need answers this quarter, hiring is unlikely to deliver them in time. And if you need to see across every team and partner, all their data has to be connected first, and that takes up most of a new hire’s first months.

A worked example

A composite to show how the checklist reads, not a client.

A brand marketing lead at a beverage brand runs paid social, search and a creator program, mostly through partners. Her questions come in bursts: before each budget decision, after each campaign, when the CMO asks whether summer worked. Her sales data sits with finance and retail partners. Social exports sit with whoever runs each account. Nobody on her team writes queries, and she doesn’t want to learn.

Her checklist reads: a few a month, hard to hire, nobody to manage them, spread out, needed this quarter, dashboards unread, yes to listening, yes to a few slides, questions change every season, seeing across every team and partner is central. That’s a clear “get help first.” Hiring would take months before her first answer, and her first hire would spend their first months connecting data before answering anything.

What she does instead: she tries Arcus free on one question, whether the summer push paid off. The answer comes from her own sales data and what people said online, and she takes it into her next budget meeting. If that first answer earns its place, the setup follows. A few months later she has the answers she was missing, and a much better idea of whether she’ll ever need to hire.

What getting help looks like with Arcus

Arcus is the third path for entertainment and lifestyle brands, and we build it for you. First we connect every piece of your data, from sales and email to social accounts and agency reports, into one place you own: your own data lake, inside your own setup. Then we add what people say online, and write down what we learn about your products, seasons, audiences and goals, so every answer starts from your business. That’s your context layer. It takes about three months. Answers arrive as a few slides: the answer on top, the evidence, then what to keep, test and stop. They land in Slack, email or Sheets. Before we connect anything, we agree with you on exactly what we can access.

Once it’s connected, any leader can ask a question and get an answer that sees the whole picture: whether the summer push paid off, which posts work, who a launch is really for. See how it works.

The way in is small on purpose: you try it free first. If you want it built after that, we scope the setup and the monthly work for your brand and quote it once you’ve seen your free answer. The pricing page explains how it works.

Common mistakes, and what this checklist doesn’t decide

• Hiring one analyst and expecting a team. One person ends up connecting data instead of answering questions.
• Buying software nobody has time to set up. A tool doesn’t answer questions on its own.
• Waiting for perfect data. Start with one question and the data that touches it.
• Hiring before you know the questions. The questions decide the skills. Write ten of them down before you write a job description.
• Treating it as forever. The right answer this year may change next year.

Questions to ask anyone offering to do it for you, Arcus included: Who owns the setup, and where does it live? Which of our existing tools do you connect to? Who reads the data, and how often? What do we get each month, and in what form? What happens to the setup if we stop?

The checklist tells you which path fits your questions today. It doesn’t tell you what any path will cost your company, or how good your data is until someone looks. The quickest way to see what your data can answer is to try it free: pick a question, and we answer it with your own numbers and walk you through it in 30 minutes.