Tackling obtuse data might intimidate novices in the retail field, but residing within real-time analytics is the way to navigate a climate of fickle shoppers and wavering sales. The fact of the matter is that the data isn’t so dense after all.
Cathy Han, chief executive officer of 42 Technologies, a cloud-based retail software company that consolidates and analyzes complex retail data in a central location, noted “Everyone is always busy, so there is a dilemma of taking the time to change or to just continue with existing tools. It can be hard to step back and evaluate changes to core platforms, but investments to improve overall efficiency will pay off in a short time.”
It’s worth it. With customers more informed than ever, relevance and timeliness are crucial. “Consumers are constantly bombarded by streams of messages from multiple social mediums. Today’s consumers are savvy with their time and quick to filter irrelevant messaging. It’s better to be known as the brand that makes timely and genuinely valuable offers,” Han said.
When it comes to consumer engagement, trim down messaging and boost customization. Han recommended companies to: “stay relevant with current channels; reduce volume and increase personalization of communication; and provide truly valuable offers with timed calls to action.”
Then there’s the matter of what to actually do with the insights. Han noted, “The best retailers use data to supplement their industry expertise and iterate on design. Retailers can see the exact attributes and styles that work and apply this information for the next design cycle.” She suggested looking to Zara as a reference of a retailer that capitalizes on quick data and even speedier product turnaround in order to remain a top player in the fast fashion arena.
By reviewing frequently updated data, retailers have the ability to remain on top of stock levels and future production plans. “Retailers can make sure to have the right amount of stock when a product is in demand….Retailers can break down elements of a product and see what should be repeated and to stock the right products for a reduction in lost sales due to [low inventory],” Han said.
Inefficiencies don’t just live in product cycles — they’re in the team that reads the analytics. “If users feel like it’s cumbersome to access the data, they’re far more likely to settle for existing reports that are delivered to them. This is a big lost opportunity since every company is sitting on a gold mine of data most people are not looking at,” Han said. Comprehensive introductions to new tools are pertinent in setting up users for streamlined reading of data.
In reviewing new data analysis, be sure that it’s intuitive and tailored to the specific responsibilities of the team member. Han said, “If the learning curve is simple, there will be more adoption. Trying it out to see the difference real-time data makes is key. The users know best, give them the tools to empower them to make data-driven decisions.”