Retailers Need Faster, Optimized Data to Avoid Falling Behind

If you’re leading a retailer or CPG company, the pressure to digitally transform is real. But the reality is only 3 in 10 executives are rating their organizations as having mature digital capabilities. 

At the same time, you’re making massive investments in e-commerce, contactless capabilities, and store technology. With these investments come huge increases in the volume of data. If that data isn’t analyzed accurately at scale and speed, the cost is immense. Here’s what’s coming in 2023 for data in the retail and CPG space and how Sigma fits in.

The Latest Industry Trends 

Retail continues to change faster than many companies can adapt. Consumers are now their own sellers, buying from various retail channels, promoting their own products on social media, selling used goods on digital platforms, and choosing how items arrive on their doorsteps.

1. Tackling the delivery dilemma 

Consumers are willing to pay for convenience, and delivery options like buy-at-home, Buy-Online-Pickup-In-Store (BOPIS), and curbside delivery continue to rise. CPG companies must digitally transform to take advantage of the “new normal”. 

2. Mobile-driven store designs and real-time, personalized shopping experiences

Many stores now provide navigation by product look-up on mobile devices. Other capabilities include price checks, competitive pricing analysis, as well as consumer recommendations or ratings of products on the shelf. Likewise, product suggestions are based on what you put into your cart. Self-checkout is expanding beyond grocery stores to other retailers as COVID continues to modify behavior.

3. Omnichannel retailing experience

Consumers now expect a unified, seamless brand experience on every platform, at any time, creating an unparalleled shopping experience.  This requires an understanding of each of the customer touch points using the most up-to-date data to improve their experience. 

4. Increased warehouse management and optimization

Supply chains continue facing extreme pressure with the increase of online buying in addition to economic uncertainty and supply shortages. Improved warehouse management via efficiencies of automation and AI will help better prepare retailers for future unplanned events. Achieving this agility and resilience will require more technical staff or tools that enable less technical users to gain the insights that they need. 

5. Auto-Replenishment via online subscriptions 

Now more than ever people across the globe want to optimize their time and resources, which can range from household items like detergent and cleaning products, all the way to skin care and shampoo. To make the most out of auto-replenishment, companies must use the most recent data to track inventory and shipping so that the customers remain happy, and shelves remain stocked. 

What Does This Mean? 

 What’s the common thread in these seemingly disparate retail trends? It all comes down to data. With increasing tight margins and competition focused on the ideal customer experience, businesses can’t afford to be playing the guessing game. Everything, from delivery optimization to warehousing to experience management must be data-driven if you want to be competitive in retail in 2023. The problem is – many of the analytic tools on the market today are built for the fast-paced, hyper-dynamic world of modern retail. They’re built for an era when things changed more slowly and when you could afford to wait for the “data experts” to build and deliver reports, often on a weekly or even monthly schedule. Those days are long gone. You need faster, more flexible, easy to use analytics that use every ounce of data available to help you make the right decisions, right now. 

How Sigma Helps your Retail/CPG Team 

1. Near unlimited scalability: As a retail analyst or business leader, you understand there are BILLIONS of rows of data available for you to make decisions, but you may only be using a quarter of that data with your current BI tool. With Sigma, you connect directly to your Cloud Data Warehouse (CDW), giving you access to real-time data so that you’re able to drill down to the lowest level of detail. This helps companies territory plan, optimize inventory, conduct cohort analysis at scale, and improve ROI. Taking advantage of all customer, inventory, marketing, finance, and other data in your warehouse can also assist in the creation of complete customer journeys, 360s, and much more.

2. You don’t know what's next: In traditional BI tools, as an analyst is building out a dashboard, they must know exactly what answers they are looking for for the business user, such as a merchandiser, buyer, or inventory planner. This process can be a timely one that leads to lost revenue in the future for your business. For example, let’s say that an analyst is building out a dashboard to report store performance across the Northwest region that they are sending to the merchandising team. They send the dashboard over and the business user says they want more detail on how many shoes of one particular color are in a specific store. The analyst then goes back and builds that dashboard. They send that dashboard over for the store that the business user requested, but the business user then wants to know about the sizes of the shoes. This cycle can go on and on. Using Sigma, your business users can find out all of that information without having to continuously send ad-hoc requests over to the analytics team and burden them with having to build multiple dashboards to answer questions. 

3. Technical Expertise: If you are the technical user (typically a data analyst) building out dashboards, then you understand how to write SQL and merge data sets in order to get the information that the business user needs. But, analysts tend to be bombarded with requests from multiple business users which takes up a lot of time and leaves them with little room to accomplish their other tasks. Sigma was created for both business and technical users to accomplish what they need in a timely manner. 

Real World Examples 

Veronica Beard: Other BI tools lacked the agility and flexibility we were looking for,” explains Lagresle. “Many required knowledge of either SQL or their own proprietary coding languages. These tools would have been a very heavy lift for us engineering-wise and would have prevented our business teams from finding the answers they need, the moment they need them. We really wanted to eliminate the BI bottleneck. Looker is too robust for a single user." - Max Lagresle, Ecommerce Analytics Manager 

Check out the full case study here.

Olivela: “Sigma is closing the distinction at Olivela between a data expert and a business expert — which means more people at the company making better decisions,”. –Dominic Go, Director of Analytics at Olivela 

Read full case study here.

Conclusion

Analyzing data at scale with zero lag time will soon be the way retailers survive. Business analysts need to know instantly what data analysts used to spend weeks finding so that the best decisions for your retail company can be made. In the digital economy, there is no time to waste and getting the insights that you need as soon as possible is more important than it has ever been.