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How should Brand Owners think about their Data and Data Team?




Building a brand is not easy. It requires passion, the commitment to take a belief system and turn that into a product, go to market and convince the market to believe in what you believe in.

I couldn’t help but notice over the past eight years of working in the eCommerce and Retail Industry that most founders came from one of three backgrounds-

  • Marketing
  • Product and/or
  • Operations

I seldom noticed someone with a background in Analytics building a consumer brand. It doesn’t mean that those who are analytical-minded do not or cannot build brands; it is just that that number is considerably lower in comparison to the other three.

Challenges faced by Brand Owners

Founders who go through the journey of building a brand are faced with hurdles of various kinds. As the brand grows, the nature of the problems that they need to undertake also changes. It starts with 

  • Conceiving a product idea
  • Developing a prototype
  • Finding a manufacturer to produce the product in bulk
  • Hiring a marketing team or an agency
  • Working with marketers to commercialize the product
  • Exploring different sales channels and selling on those channels
  • Maintaining profitability and margins
  • Fundraising, investor relationships and
  • More!

All the categories of tasks listed above are typically overseen by the founding team or by the initial set of hires. Those tasks are critical to getting the business off the ground and onto a stable footing. Some do a great job at it, while some may find it hard to scale. Nevertheless, it is an enriching learning experience, and in my opinion, it is the journey that matters more than the results. 

During the early stages of the business, executives tend to be more hands-on and know most of what is going on in the business. They are involved in most decisions, and they are generally aware of the health of the business, even if that awareness comes from a combination of manual work, hunch, and reality.

I was no different. I knew every customer, every trial that happened, every issue that was raised, and how our customers felt. I was always there to answer every question, even if those questions came up in the middle of the night. My team would often expect to hear from me when an escalation happened. This continued for a couple of years, and we have gained and lost in the process.  We gained customer trust, our churn was limited, referrals kept coming in, and in general, we made forward progress. We gained all that while temporarily sacrificing the ability to scale exponentially.

I was working in the business rather than on the business, as the saying often goes.

Need for Data Team for Brand Growth

Every business goes through a phase where they have achieved the scale, they could with the founding team running point on everything. But to keep that growth trajectory up and to the right, it is imperative that the team they have assembled is empowered to deliver results.

As businesses continue to grow, executives spend more time understanding what is happening in their business rather than being presented with the data and making the best decision possible. The most common solution to this problem is to hire an “analyst,” which is why I am writing this article.

Often the first hire in the data team at a DTC brand is an "Analyst," and this is the first mistake founders make when thinking about their data. An analyst is a catch-all phrase for a person with critical thinking ability and can analyze a set of numbers and find meaningful insights.

Tasks Undertaken by the Data Team

Let’s look at the JTB framework for the data team at a DTC Brand and assess what tasks need to be performed-

  • Identify the tools required to build and manage a data stack
    • A data warehouse, an ETL platform, and A BI Platform at the least

  • Evaluate each of these tools for
    • performance, scalability, features, cost, and usability

  • Implement the data stack
    • Setup the data extracts and move the data to a data warehouse
    • Conduct workshops with the internal users to understand business requirements
    • Implement the requirements by building the data models, reports, and dashboards

  • Socialize the data stack with resources within the company by training them and driving the adoption of the stack

  • Solve any ad-hoc questions that get asked by analyzing the data and distilling that information into consumable insights.

Having worked at data teams in enterprise companies for over a decade, I can confidently tell you that the person who will check all the criteria above is a unicorn. You will most likely not be able to hire them even if one was available or retain them even if one was hired.

Questions for Hiring First Internal Data Resource

I have the following questions for founders who come from marketing, operations, and product backgrounds and are hiring their first data resource-

  • How do you budget for your data team/stack?
  • Who owns the decision related to what technologies to use?
  • How do you assess the right candidate for your data needs?
  • What challenges do you face while building the data team if you have not built a data team in the past?
  • What criteria would you be looking for when hiring a data resource?
  • Which criteria would you prioritize over the other and why?
  • What questions would you ask them in an interview?
  • How would you manage the data resource (analyst)?
  • Who on your team manages the data resource (analyst)?
  • How do you know the analyst/data resources are doing a good job?
  • How do you ensure the quality of the work that is being done?
  • Who on your team can help the analyst if they are stuck?
  • Are you looking for analysts who have worked in your domain?

How to actually build your Data Team?

After working with over 100+ brands, I’ve concluded that many founders at D2C brands still think of data as a second-grade citizens to marketing, operations, and product. This thinking often leads to short-term decisions that eventually add up and cost more money, time, and frustration to everyone involved in the process. The number of abandoned data projects indicates a failure in a data team’s hiring strategy. 

For someone thinking along the lines of “I will hire an analyst, and they will take care of all my data needs” is akin to saying I will hire a marketer. They will excel at sending emails, running social media ads, handling retention marketing, branding, and more- You know that does not work.

Just like how marketing is a specialized function, so is data. Many marketing functions are outsourced to agencies and managed internally by a key resource, typically a CMO. 

Why not data? Building a scalable data foundation and managing it over time requires the involvement of people with skills in enterprise architecture, data engineering, data governance, the total cost of ownership evaluation, data modeling, business intelligence, business process evaluation, and data science. People with all these skills are in short supply, so an alternative way to build this team is to hire a team of fractional resources who bring these skills to the table to achieve stated goals. Once the business grows, hiring a Chief Data Officer in-house and relying on outsourced resources or building an in-house team of data resources for execution support is a more viable option.

How does a Fractional Data Team look for a DTC Brand?

Over the past few years, we at Saras Analytics have pioneered an approach to modern data team development for eCommerce brands by making fractional data teams available for brands. We ask our customers to spend time defining the problem statement and leave the execution to us.

Your first internal hire on the data team should be a planner, not a doer.

  • A good project manager with an understanding of business processes and data and who can work internally to prioritize projects and oversee delivery should, in my opinion, be the first data hire.

Hire an agency to do the execution, preferably an agency that is focused on your domain

  • Understanding systems and business processes is a critical part of any data project.

  • Resources who work solely in your domain have a better understanding of these systems and, therefore, can deliver results quickly and more reliably.

Do not overburden yourself or your executive team by asking them to manage the data team/resource.

  • Even if you have a data savvy executive who is interested in running the data initiative, it is probably not the best idea.

  • Data projects tend to take away their executives’ time from being able to perform their core business functions.

  • If you get one of your executives to manage a data team/resource, try to keep it short-term or give them enough cushion in their core team, allowing them to focus on the data projects.

If you are an emerging brand thinking about building a data team (of one or two resources), consider bringing a data partner on board.

Reach out to us if you are a brand looking to put your data to work!