Shoppers today want instant purchase gratification. For ecommerce sellers, this means having the right merchandise in stock to keep shoppers adding to their carts and clicking that buy button.
When shoppers leave without converting, the first question we have to ask is, why?
Sometimes the answer comes down to something a retailer can’t control, like a shopper simply changing their mind. But when it comes down to things you can control, like a broken link to your partner site, incorrect inventory information or delayed shipping dates, you should be able to identify those barriers to conversion and fix them immediately. The problem is, we don’t. Today, most ecommerce supply chain issues are discovered by looking at reactive reports, evaluating customer complaints, running out of SKUs or worse, a drop in revenue.
The good news is, automation and AI are starting to solve ecommerce supply chain problems before they can significantly impact the business. By applying new tools on top of the data already running through your systems, you can discover how to turn potential challenges into opportunities – or more precisely, turn data into dollars.
Tech Will Take You There
Ecommerce naturally has ups and downs due to evolving shopper behaviors. But continuous spikes and lulls in consumer demand can make retailers feel like they’re riding a rollercoaster with a blindfold on – they don’t know when the dips and turns are coming or how significant they’ll be. It’s difficult to determine which changes are the most important when every change feels unexpected. Is it a slight turn in the tracks or big dip that will end their ride?
Today’s retailers can (and should) take off the blindfold to better anticipate what’s coming. That’s where technology comes in.
Often juggling multiple suppliers and SKUs, retailers have an incredibly complex supply chain and an abundance of data. There’s an opportunity to leverage data to optimize the supply chain, but it’s difficult to gain actionable insights from such massive amounts of it.
Many retailers have invested in a business intelligence (BI) tool to simplify the volumes of data they’re gathering and help management make critical business decisions. But being able to visualize data is only the first step. If retailers can monitor their supply chain data and receive early warnings of issues or disruptions, they can conduct business more efficiently.
An automated business analysis (ABA) approach takes BI functionality to the next level. ABA leverages artificial intelligence to analyze billions of data points and quickly identify the 4-5 unexpected changes that matter most, acting as a virtual business analyst. This provides leaders and managers access to personalized insights, based on both historical and recent data, and highlights where they should be looking and what they should be looking for within the data. These insights would take weeks or months to find with a human analyst alone.
Better Insights, Improved Productivity
For retailer’s high highs and low lows, having visibility into unanticipated inventory shortages or spikes in consumer demand allows management to get ahead of changes that could drastically impact revenue.
An ABA approach could also shed light on a breakdown in the ecommerce supply chain. Is there an issue transferring inventory from the warehouse to motor freight? How long has this been an issue, and are all necessary parties aware of it? Is this a one-time problem or a recent trend? Most importantly, how is it impacting purchasing or your KPIs?
ABA can quickly flag hiccups along the supply chain so leaders and managers can address them in next-to real time. They’re not sorting through loads of data to pinpoint the problem when ABA serves up the necessary information to leadership. This helps ensure everything is operating smoothly from the warehouse all the way to the online shopping cart.
Opening the Door to New Opportunities
Having a single source of information with a next-level business intelligence approach reduces the time it takes to gather and analyze data and turn it into actionable information. Greater, faster access to insights allows resources to be reallocated to higher priority needs rather than crunching data and pinpointing trends. Technology can automate that process, taking it from days, weeks or months of analysis to hours.
More time means new opportunities. If a retailer learns that customers are abandoning a product because two-day shipping isn’t an option, that’s their chance to make (or at least discuss) a change to their supply chain. Do they need to re-think their distribution center placement? Should they start searching for a new shipping partner?
Less time assessing data allows for more time devoted to decision making that could have a positive impact on the bottom line.
With an ABA approach, retailers have greater visibility and insight into their ecommerce supply chain. Potential threats become opportunities. Reactive thinking becomes proactive thinking. And dips and turns on the rollercoaster ride are no longer feared – they’re part of the fun.
This article originally appeared on Multichannel Merchant.
Join this webinar to learn how AI and ML can enhance your category management approach.