Top 6 Mistakes to Avoid In Retail Analytics Solution

Data is everywhere, driving retail analytics solutions, changing how we do business, and redefining what it means to be a customer. However, many businesses still operate in a data-aware mode rather than adapting to a data-driven mindset.

What is standing in their way? The data is accessible. So why are so many companies struggling to go from data to insight to action?

Here are the most common data mistakes we see businesses make: 

Data Blunder #1: Betting on average-of-breed vendors

Businesses often need help to part with their legacy BI tools for retail data analytics solutions. Unfortunately, clinging to these one-size-fits-all tools can prevent you from constructing a modern data stack. The issue is that legacy BI tools for advanced retail analytics solutions were designed for desktops and single-server applications. As a result, they typically do not scale as well as today's cloud-based data warehouses.

Worse, traditional BI vendors must design their products with today's data challenges in mind. It's not just about the size of the data; it's also about the demands that a modern data-driven business places on that data. As the number and complexity of use cases increase, tools based on dashboarding, cubes, and extracts begin to fail.

Read more: Roles & Responsibilities of Data Analysts in the Retail Industry
 

Data Blunder #2: Relying on Data Analysts to Spoon-Feed Insights to Business Users

It defies logic to require business users to go cap in hand to advanced retail analytics solutions whenever they need data to make decisions. Relying on data analysts completely to give everything is a waste of both parties time.

Meanwhile, over two-thirds of data analysts say they need more time to implement profit-generating ideas because they spend up to 50% of their workdays maintaining dashboards and providing customized reports.

Data Blunder #3: Relying on Static Dashboards for Critical Information

Too many companies need to rely on data extracts and static dashboards. They may have the necessary insights but need to be updated, difficult to access when needed, or too fragmented to be reliable.

This is posing significant challenges for companies seeking to dominate the data decade. According to the HBR report, two-thirds of the organizations surveyed believe that improving their organization's success with advanced retail analytics solutions comes down to using live data and improving data trustworthiness.

Data Blunder #4: Building on Top of an Inflexible Data Foundation

While too many businesses rely on static dashboards, an equal number rely on fixed and inflexible data pipelines. This is commonly referred to as the insanity cycle.


Every time a new use case emerges, the business user must contact experts for retail analytics solutions, who must then contact the data engineer, who must then contact the IT team to ensure that the new data is validated, governed, and secure before it can be modeled. The procedure is tedious, frustrating, and costly.

Read more: Understanding the Importance of Subscription Analytics for Your Startup 

Data Blunder #5: Building an Analytics Culture from the Ground Up Rather Than From the Top Down

When developing their company's retail analytics solutions culture, many prefer a bottom-up approach because it uses data as a starting point and produces a more accurate market forecast to base their business strategy. This approach has only one major flaw: it forces you to tailor your business strategy to fit the data, which may be counterproductive to your company's needs. 

Data Blunder #6: No Defined Metrics

Plan to do so if you were to do so. It is critical to define key metrics because it provides employees with a set of attainable, quantifiable goals to work towards and keeps your workforce management.
Stop Letting Data Errors Hold You Back

This is the data-defining decade. Sure, data is bigger and more complex than ever before, but the implications of that are far-reaching.

LatentView Analytics assists businesses in using retail data analytics solutions to drive action, disrupting how we work, transforming the customer experience, and shifting power to frontline workers. Now is your chance to be a data leader and leave your competition in the dust.