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Should My Retail Business invest in Data and build a large Data Team?

Should My Retail Business invest in Data and build a large Data Team?
Table of Contents
Estimated Reading: 7 minutes
Post Author: Giuseppe Iafulli
Reviewed By: Andy Bird

Are you considering investing in a data project and building a data team for your retail business? As your datasets grow in complexity, you might wonder whether it’s beneficial to invest in such a project and whether you need a skilled team of data scientists, engineers, and senior leadership. But is this the right move? Do you need such a large team to achieve the growth you’re seeking for your business? And in this challenging economic climate, should you invest in data at all?

In this blog, we explore when and why building a dedicated data team is necessary, and when it might not be. We’ll discuss the importance of having a data strategy in place and how to ensure the success of your data strategy, whether you have a data team or not.

Common triggers for building a data Strategy

The importance of a robust data strategy in today’s business landscape cannot be overstated. Data-savvy companies don’t just outperform; they dominate. According to McKinsey, they’re 23 times more likely to crush the competition in customer acquisition and 19 times more likely to stay profitable. In short, you must use data to thrive in today’s retail industry. 

As companies in the retail sector navigate a myriad of challenges and opportunities, they often encounter specific triggers that highlight the need for a comprehensive data strategy. These triggers are not merely indicators of growth or change; they represent critical junctures where accurate and insightful data can be the deciding factor between success and stagnation.


Rapid business expansion

When a retail business undergoes rapid growth, it invariably leads to a significant increase in the volume of data generated. This data, originating from diverse sources such as sales transactions, customer interactions, supply chain logistics, and online traffic, can quickly become overwhelming. As the complexity of managing and interpreting this data escalates, it can start to strain the day-to-day operations of the business. Moreover, if you are relying on ‘master’ spreadsheets, the reliability  and consistency of the data used for decision-making can be compromised. This is often the case when each department compiles its own data in isolation, leading to inconsistencies and gaps in the overall data picture

In such scenarios, it may be prudent to consider increasing your investment in data,  whether it is hiring full-time data professionals, working with a data consulting company, or a mix of the two. This approach will help you to handle the surge of new information effectively.

By doing so, you can extract meaningful insights from the data, which can inform strategic decisions, optimise operational efficiencies, and enhance customer experiences. For instance, they can identify patterns in customer buying behaviour, predict market trends, streamline inventory management, and personalise marketing efforts.

Increased reporting requirements

As your business expands, the demand for precise and timely reporting becomes increasingly crucial. This growth often brings with it a complexity in data management that can no longer be efficiently handled through basic tools like Excel. At this juncture, many retailers recognise the need to invest in a data project to streamline their reporting processes. This move is not just about enhancing efficiency; it’s about ensuring accuracy and consistency in data handling, which are vital for informed decision-making.


The first and perhaps most critical step in this transition is creating a single source of truth for all data. This means consolidating data from various departments and sources into a unified, centralised system. Relying solely on Excel spreadsheets can lead to unreliable and inconsistent data due to issues like version control, human error in data entry, and difficulties in data integration. .

A single source of truth ensures that everyone in the organisation is working with the same data, reducing errors and discrepancies. It provides a clear, comprehensive view of the business’s operations, customer behaviours, marketing sales trends, and more. This unified data repository is crucial for generating accurate reports, forecasting, and strategic planning.

Furthermore, investing in a data project can help you leverage centralised data to apply advanced analytics, uncover insights that were previously inaccessible, and recommend  best next actions based on data-driven evidence. They can automate routine reporting tasks, freeing up valuable time and resources that can be redirected to strategic initiatives and growth opportunities.

Increasing customer expectations

As consumers become increasingly tech-savvy, their expectations for personalised experiences have risen. In fact, 60% of customers now expect companies to anticipate and meet all their needs. This could range from sending them a personalised email after a purchase or newsletter sign-up, to offering customised pricing or promotions based on the data collected about them.

A data team can significantly enhance customer satisfaction by analysing behaviors and preferences across various touchpoints. However, implementing such data-driven projects can be time-consuming, often taking several months to deploy and additional time to optimise and ensure they deliver the expected results. An alternative approach is to implement ‘plug and play’ data applications that increase personalisation. These applications have already been tested for maximum impact, so you only need to integrate them on top of your Single Source of Truth and tailor them to align with your company’s objectives.

By adopting this strategy, you can create a unified customer view, enabling your business to identify trends and patterns effectively. This approach not only provides a competitive edge but also ensures a more personalised and satisfying customer experience.

Growing complexity of data

As your retail business expands, you’ll find yourself managing vast amounts of data from various sources, including CRM systems, sales records, and social media platforms. For early-stage retailers, handling this influx of data can be a daunting task.

Having a dedicated data team, comprised of experts in data science and engineering, can significantly simplify this complexity. However, with the right solutions and support, these challenges can be effectively addressed even by a small team or a few skilled analysts. Sometimes, companies that lack the necessary skills, expertise, or personnel may even opt for services like analysts or a Chief Data Officer as a service while they test their project and build their skills. This approach helps in strategising and ensuring the business is equipped to meet its challenges head-on.

Ineffective Marketing campaigns

The success of a business is significantly influenced by the effectiveness of its marketing campaigns. Data plays a pivotal role in enhancing the impact of these campaigns. With the aid of a data team, retailers can delve deep into performance metrics, customer engagement, and market trends, not only to identify areas of weakness but also to propose actionable solutions for improvement.

One of the key ways data can improve marketing efforts is through the use of attribution models like multi-touch attribution or media mix modelling. These models allow businesses to accurately track customer interactions across all touchpoints. By understanding which channels and tactics are most effective in driving customer engagement and conversions, retailers can optimise their marketing strategies for better results.

Moreover, it’s crucial to attribute all marketing spend, including often-overlooked areas such as influencer marketing, offline spend, and production costs. This comprehensive view ensures that every dollar spent is accounted for and its impact on customer acquisition and overall sales is clearly understood.

Software companies like are at the forefront of leveraging AI to enhance marketing efficiency. They offer AI predictive modeling to ensure the best budget allocation. This technology eliminates much of the guesswork involved in understanding how changes in budget allocation affect Customer Acquisition Cost (CAC). AI-driven Scenario Planning tools can forecast the outcomes of different budgeting strategies, allowing businesses to make informed decisions that improve campaign outcomes and enhance Return on Ad Spend (ROAS).

In essence, a data team equipped with the right tools and technologies can transform the way a retail business approaches its marketing efforts. By providing a clear, data-driven picture of what works and what doesn’t, they enable businesses to refine their marketing strategies, allocate budgets more effectively, and ultimately, achieve better engagement and sales results. 

Inventory management challenges

Inventory challenges—including overstocking, understocking, and inconsistent tracking, can significantly impact the efficiency and profitability of a retail business. investing in data can play a crucial role in mitigating these issues, where it can help se to optimise supply chains, accurately track stock levels, and predict demand patterns.

By analysing sales data, market trends, and historical patterns you can identify potential risks of stockouts or overstock situations, enabling the business to take proactive measures to balance inventory levels. This approach not only reduces the risk of lost sales due to stockouts but also prevents financial strain from excess stock. Additionally, it allows to evaluate suppliers based on metrics such as cost, performance, and reliability, thereby improving supplier performance visibility. This analysis helps in identifying the best suppliers, fostering stronger supplier relationships, and making informed decisions about which suppliers to continue working with.

In essence, a data analysis is pivotal in enhancing overall operational efficiency by ensuring that inventory management is both responsive and efficient.


Do I need a large data team?

The notion that “bigger is better” in terms of data team size is a common misconception. In reality, the size of a data team should be tailored to fit the scale and complexity of your business needs. Interestingly, smaller teams can often make the most significant business impact, particularly when they are equipped with the right tools.


For small and medium-sized retail businesses, a strategic approach is to partner with a software company that functions as a business partner. This partnership goes beyond just implementing software for data unification and insight extraction. It’s about closely collaborating with the business to provide tailored advice on what’s necessary to ensure that data projects yield a tangible return on investment. stands out as a key tool in this context. Our decision intelligence platform consolidates all company data into a single source of truth. It enables businesses to seamlessly adopt plug-and-play data apps and machine learning models, streamlining the process to achieve quicker, more efficient business results from data projects. This approach facilitates better, faster decision-making in areas like marketing, supply chain, and finance.

Become more data mature with our free eBook

It’s clear that every retail business needs to leverage their data. But rest assured, you don’t need a huge fleet of data analysts and engineers to make that happen. With the right tools and strategies, even a lean retail business can excel in a data-driven landscape, helping the whole team use data more effectively.

To help you set up your data function, we’ve created an eBook. In it, we’ll help you pinpoint where you are in your journey to data maturity. We’ll then offer expert advice on how you can advance your company’s data capabilities at each stage. 

Download your free copy today.

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