5 Common Mistakes Retailers Make, And How To Avoid Them

The retail industry is growing increasingly competitive, and already slim profit margins make it essential for retailers to avoid costly mistakes. Many common oversights involve data management. Utilizing analytics to generate actionable insights from that data is becoming imperative for retailers to remain competitive in today's marketplace.

Advanced retail analytics solutions can provide a more holistic view of what's really occurring in your retail environment. Essential supply chain data such as point-of-sale (POS), inventory levels, deliveries and credits, and even loyalty programs can be more effectively managed and utilized using the right tools, while helping to avoid costly mistakes.

Here's five common mistakes retailers make with analytics, and how to avoid them.

1. Not Putting Available Data to Good Use

If you already collect data from customers, why aren't you putting it to better use? A big mistake retailers often make is having comprehensive data sets and not using it. Whether it is to manage your supplier's order fulfillment rates to ensure adequate in-stock positions, to forecast future sales using predictive analytics based on historical trends, or to customize loyalty programs and promotions based on your customers' shopping habits, your data is valuable.

An inability to leverage the value of this data can put a retailer at a competitive disadvantage. Retail analytics has advanced significantly in both capabilities and functionality, so don't get left behind.

2. Not Using the Right Analytics Tools

The tools you use to gather and interpret data can have a significant impact on understand your business realities. Using multiple tools only leads to a lack of standardization and confusion across various departments who need to read the data collectively.

Retailers benefit from choosing solutions that can centralize analytics capabilities, while remaining flexible and customizable to ensure users can get the most out of their use of the platform. Most importantly, you need an analytics solution that's able to organize disparate information in a way that's easy to read so it doesn't need an expert to interpret it all.

SEE ALSO: 9 Ways You Didn't Realize You Could Utilize Retail Analytics

Not integrating data is arguably the biggest mistake a retailer can ever make, and researching to find the most thorough solution is imperative.

3. Not Training Your Staff to Use Analytics

Another common mistake is thinking not every retail department needs to utilize analytics. Not allowing every employee to access enterprise analytics at some level ultimately leads to inconsistent interpretation of data, and many versions of the truth.

With statistics showing 93% of customers buy products when helped by a knowledgeable employee, it's important to have analytics available for everyone. It also helps in general customer service since metrics help glean valuable insights into what customers want and their habits.

4. Not Using Scalable Analytics Platforms

Some retailers don't look far enough into the future to see whether the data platform they use can scale to keep up with growth. As your own retail business grows, more data will inevitably keep coming in, and it can get overwhelming. Using an analytics solution that is not scalable may end up causing frustration when it shuts down due to an excessive data onslaught.

SEE ALSO: How Scan-Based Trading Can Improve Inventory Management and Increase Customer Satisfaction

Using real-time tools with unlimited storage, you'll keep yourself updated every day without fear of technical issues that can impact your business.

5. Relying On Old Data

Industry-leading analytics solutions can aggregate data feeds in real-time, providing retailers with analytics and insights that are updated daily. No longer to retailers have to rely on sales from last week to gauge their sales trends. Choosing a solution that utilizes the power of automation can help retailers take advantage of data like never before to analyze sales, orders and replenishment, inventory, plus assortment optimization.