• AI is expected to have a significant impact on the retail industry, with increased investment predicted.
  • Advancements in technology and data analytics have improved retail business processes, leading to higher profitability, better customer experience, and employee engagement.
  • PUMA is an example of a brand using data and analytics to optimize assortment and pricing decisions, resulting in increased sales and better market intelligence.
  • Steps to get started with data and analytics in retail include determining goals, gathering and owning data, choosing the right tools, analyzing the data, and communicating findings effectively.
  • Continuous learning, exploration, and refinement are essential in the application of retail intelligence and data analytics.
  • Brands should involve all teams in using market intelligence for decision-making, not just silo it to one team.
  • EDITED is an AI-driven merchandising experience platform that helps brands and retailers make real-time decisions and drive profits through data and analytics.




Getting started with data analysis can at first feel and appear intimidating. If this is your initial reaction, fear not, EDITED works with many leading brands and retailers, and our retail strategists experience this daily. It is only natural to fear the unknown. The world has evolved with advancements in technology, and terms like ‘digital transformation’, and ‘data and analytics’ bounce around daily from the leaders in the retail and technology industry. We break down the meaning behind these terms to help you understand the basics and to get started with data and analytics in retail. 

Understanding Digital Transformation & What It Means for Your Business

Within your role as a brand or retailer, your business will always be looking into how to improve and deliver growth. Technology has become a catalyst for you and your wider team across different departments, enabling brands and retailers to accelerate, optimize and improve current business processes. From pricing optimization to assortment planning and visual merchandising, technology can act as a tool to help you move away from previously time constraint, siloed processes and instead empower you to make informed, aligned, and strategic business decisions.

An understanding of digital transformation and what this means throughout the business is key to enabling and empowering your whole retail business though to align. A recent Forbes article described 2023 as ‘shaping up to be the year of AI’, (artificial intelligence) quoting International Data Corporation, expecting retail ‘to invest more in AI technology than any other sector except finance. Between them, the two industries will account for roughly one-quarter of worldwide AI investment, set to reach $300 billion by 2026. Furthermore, in a recent Coresight Research study, 60% of brands and retailers plan to invest in AI to automate visual product content.’

How have advancements in technology and the application of data and analytics improved retail business processes?

According to McKinsey, technology will likely double store profitability. ‘The tech-enabled “store of the future” can double retailers’ EBIT margins and will be easier to operate. It will also provide a better customer experience and greater employee engagement.’ 

With this context, it is clear to see and understand why your business might be starting to look for ways to invest in technologies to aid in delivering business objectives. In the example below they provide examples of how data can impact retail business processes across the business. 

PUMA: Harnessing the Power of Retail Data Analysis for Success

Leading athletic and apparel brand PUMA is a recent example of a leader that invests in data and analytics to optimize their assortment and pricing decisions to find the ‘sweet spot’ in a saturated market. “As a brand that sells into hundreds of retailers, it can be quite common to only get data back from 20% of them,” said Danny Brown, PUMA UK’s Business Operations Manager. “What about all the rest? What’s my discount in the market at the moment? What’s my average selling price?” How do you formulate a successful pricing strategy in a saturated market such as the UK to get high sell-through, but not negatively impact margin? “As far as price goes, is the product situated in the right place?” asked Danny Brown. “I know personally, that if you overprice by £5, your sell-through can fall off by 70%.”

PUMA used Market Analytics assortment and option pricing tools to spot gaps in the PUMA assortment within specific price points at a key retail partner. “We launched on a key partner’s site first and our product sold well, but not as anticipated. I wanted to understand why this was,” asked Danny Brown.

Market Intelligence technology provided the insight that led to PUMA’s creating three new custom styles of footwear for that retailer. This decision increased sales with this key account, where one design became a PUMA UK top 10 footwear best-seller, with a stock turnover of thousands of units per week.

Using Market Analytics tools for market intelligence helps PUMA make data-driven decisions to quickly pivot product and pricing strategies to react to an ever-changing market. Moreover, the team can analyze impacts on the wider business and how it affects their day-to-day processes. “You gain access to data you’d never be able to get by manually searching. This allows me to make decisions on a local level and share with the wider global team,” said Danny Brown.

A Step by Step Guide To Getting Started With Data and Analytics

Getting started with retail data analytics can seem intimidating, but with the right approach, it can be a rewarding and valuable skill to learn for both the longevity of your career and your business. Here are some steps to help you get started:

  1. Determine your goals: Before diving into retail data and insights, it is essential to determine what you want to achieve. Whether solving a specific problem, improving a business process that might be manual, or gaining insights into a particular area for your job role, having a clear goal in mind will help guide your data analysis efforts. For example, if you want to optimize your pricing strategy or identify top retail trends, plan your assortments, or even look to expand into new markets or categories.
  2. Gather and own your data: Not all data is created equal. Once you have a goal and a basic understanding of the tools and techniques involved in data analytics, the next step is to gather and own your data. Whether you track top retail trends or your job requires competitive shopping or price and promotional data analysis as a buyer or planner, you need to understand where you are pulling your data from and the quality of it. If you are focusing on too many data sources or manual analysis, it could be costing you valuable time and you should question the validity of the data too. Partner with a world-class implementation team who are experts in supporting retailers to evaluate their data and determine the best data-sources to include within your analysis. Find data analytics solutions that will not simply report the news but combine those data siloes to generate AI-driven guided analysis and opportunity insights. 
  3. Choose the right tools: There are many tools available for data analytics, from spreadsheets to specialized software. However, if you want to optimize time-constraining or limited manual processes, consider a merchandising intelligence platform that combines external market data with smart analysis of your internal data. Investing in a tool where retail data is pre-prepared and data insights are automatically authored can help you save time and money and make informed decisions with data to back up your theories. 
  4. Analyze your data: Once the data is clean and organized, it’s time to analyze it which involves applying statistical techniques to the data to gain insights and identify patterns or top retail trends. If you have invested in a retail analytics platform, much of these will be automated already. Retail vendors often have existing workbooks, template dashboards, and resources to help get you started. Or even retail experts that will support you on your journey tailored to your level of expertise: ranging from training to take more of a consultative approach. 
  5. Communicate your findings: Finally, communicate your findings to others clearly and concisely. It may involve creating visualizations or reports that help others understand the insights you have gained from the data. The world of analysis can be democratic. Make your reports easily available to anyone who needs to make a decision in your business to aid in transparency and alignment. The art of storytelling with insights can prove invaluable to you as you demonstrate theories or suggestions with data-backed findings to justify your recommendations.

Remember, the application of retail intelligence and data analytics is a continuous process of learning, exploration, and refinement. With time and practice, you can develop a deeper understanding of retail data analysis and use it to drive meaningful business insights and decisions. 

So what advice does Danny Brown from PUMA have for other brands out there looking to incorporate market intelligence into their processes?

“Bring everyone on board, don’t just silo use of data to one team. Anyone who makes big product decisions should use it.”


EDITED is the world’s leading AI-driven merchandising experience platform that empowers brands and retailers with real-time decision-making power that drives profits and inspires customers.

We help retailers increase margins, generate more sales and drive better outcomes through AI-driven Market and Enterprise Intelligence to fuel Automation. By connecting business analytics and external market data, retail’s most successful brands and retailers use EDITED’s Platform to get closer to their best customers and future-proof their business.

Ready to take the next step in your journey of retail data and analytics? Get in touch with us today.