Advanced Data Analytics in Retail: Challenges and Opportunities

A lot has changed in the retail space over the years, but one thing remains true: retail is the backbone of the economy. It’s more complex than ever, though. Every day, you’re dealing with rapidly evolving consumer preferences and expectations, fluctuating costs and tight margins, unpredictable supply chains, and more.

To compete and succeed, you need to harness the power of your business data with advanced analytics. Your data can help you understand what’s happening in your business, so you can make the right decisions for your business – decisions that are based in fact and reality, rather than gut feel and intuition.

With the technology and tools available today, this kind of analysis is no longer just the domain of large national and multinational companies. Every business of every size has data that can be leveraged to improve and optimize its operations. We can help you put those tools, and your data, to work for your business.

Data Challenges

The primary challenge in retail analytics is the complexity of the business itself. At any given moment, you’ve got data flowing from inventory systems, POS terminals, ERPs, OMSs, and more. So much data, in fact, that effective manual analysis is simply impossible. Often, that data is siloed, making correlations between data points impractical. With legacy systems – especially those that aren’t integrated – there’s a significant risk of flawed data, arguably worse than no data at all.

Retail teams waste valuable time managing multiple versions of spreadsheets, fixing data integrity errors, re-keying data, and double-checking broken formulas – static, mundane tasks that extend cycle times and hold teams back from delivering strategic value to their organization.

Gathering this data, cleaning it, and analyzing it requires time and specialized expertise. The tools available to retailers today automate large parts of that process, pulling data from a multitude of sources, and applying advanced analytics to generate valuable descriptive and diagnostic insights into the past and present, and predictive insights into the future.

The payoff? A highly optimized retail business, in which data-driven decisions related to sales, merchandising and marketing, customer experience, and operations can be made on the fly, in real time – one that has a greater ability than ever possible to predict and proactively respond to a rapidly-changing future.

Types of data

Most retail businesses use KPIs – to some degree or another – to track and measure results and performance over time. At even a simplistic level, these KPIs can help you identify customer patterns to increase sales and identify specific challenges in the operations and in the supply chain to lower costs.

In your business, you’re likely tracking some, if not all, of the following:

  • Gross Margin ROI. Arguably the most important metric of all, GMROI tells you how much profit you’re earning on what you’ve invested in inventory.
  • Traffic to your website or into your store. This allows you to track outcomes of your marketing and optimize your staffing levels. You might also be calculating your conversation rate, to assess your sales performance.
  • Total sales volume, over time, by location and channel. These data points help you optimize your inventory for your customer base, and in the case of multiple channels, conduct A/B testing to optimize even further. You might also be gathering related subsets of data – average transaction value to understand when your customers are buying, items per customer to identify cross-selling opportunities, and customer retention, to better understand where your repeat business comes from.
  • Inventory turnover helps you better manage stock levels. You may also be tracking backorder rates for better visibility into product demand and supplier challenges.
  • Returns data. Understanding both the rate and the reason for returns helps you to identify a range of issues from staff sales technique to product quality.

These are just a few relatively common examples; in your business you may be gathering many more pieces of information. Therein lies the challenge, and also the opportunity.

Individually, these data points can tell you some things about your business, but only to a point. Combining, analyzing, and visualizing the data gives you a powerful body of actionable information you can use to grow your business. Robotic Process Automation (RPA) tools like UiPath give you an unprecedented ability to gather and combine large volumes of data from a multitude of disparate sources. An Analytics Process Automation (APA) tool like Alteryx allows you to make sense of the raw data, drawing insights about what’s happening now, and what the future holds. Budgeting, planning, and forecasting tools like Workday Adaptive Planning provide the ability to plan, execute, and analyze—all in one system—enabling organizations to work from the same data and business logic, standardize on metrics across the organization, and make decisions based on one view of the truth. This reduces bottlenecks and friction while increasing collaboration. And with dashboarding tools like Tableau and PowerBI, you can quickly visualize and share that body of information, allowing you and your teams to make better decisions, faster than ever.

Advanced Retail Analytics

Advanced retail analytics provides you with the opportunity to bring all your data points together, combining and analyzing them to give you the clearest possible picture of what’s happening in your business. With this data you can track and visualize the entire customer journey, capitalizing on opportunities that may not have been apparent otherwise, and immediately responding to issues as they arise.

There are four kinds of data analytics that you can bring to bear in your business. From least to most complex, they are:

  • Descriptive analytics helps you understand what’s happening in your business right now.
  • Diagnostic analytics gives insight into why those things are happening.
  • Predictive analytics uses the previous two to give you foresight into what will most likely happen next.
  • Prescriptive analytics – the most complex of all – maps out the course (or courses) of action that are most likely to produce the best outcome.

Operationally, advanced analytics saves significant time and lessens the risk of human error with automated reporting capabilities. You can make better, more informed decisions, setting prices and managing your supply chain more effectively. Any issues or irregularities can be flagged immediately, allowing you to take quick action to solve problems.

At a more strategic level, you can gain deeper insight into your customers’ behavior and buying patterns, forecasting demand more accurately, understanding the outcomes of your marketing and merchandising strategies, and optimizing your store layout.

Better data, better analysis, better insights. All leading to a more successful and profitable business.


Are you working with legacy systems that aren’t integrated, don’t account for each other, and don’t easily allow you to bring your data together? Do you find yourself updating your forecasts to account for exceptions? Do you end up with too many markdowns at the end of season? Do you run into frequent inventory distortion problems – out-of-stocks and overstocks – resulting in lost sales?

If the answers to your business problems aren’t clear, maybe it’s time to put your data to work for you. We know your business, and the challenges you face. We also know advanced analytics, and how it can take on those challenges. Connect with us to start the conversation today.