As the spread of the coronavirus has led to a rapid rise in e-commerce, CommerceIQ is offering a solution for brands that manages heightened short-term demand and plans for long-term growth.
With a growth rate increasing 400% during March, e-commerce experienced an acceleration by nearly five years and a permanent shift in the market. To better serve consumers, brands operating in this “new normal” can explore Ecommerce Revenue Automation (ERA), a strategy that combines data analytics, machine learning and automation to increase sales and drive sustained revenue growth.
The Growth Navigator from CommerceIQ combines the company’s machine learning and automation platform with in-house Amazon insight.
A dedicated Amazon associate provides training and an operating playbook on managing demand spikes from the perspectives of sales, operations and marketing. In addition to establishing goals and tracking progress, they’ll develop custom advertising strategies that integrate sales, inventory and competitor data to automatically shift spend across top keywords and peak shopping times to maximize revenue and share of voice for all essential in-stock products.
A rolling four-week forecast considers overall demand for products on Amazon, PO history and weeks of coverage, while the Amazon partner creates automations to proactively monitor and correct potential increases in PO discrepancies, out-of-stocks and third-party competition to reduce revenue gaps.
CommerceIQ partners, meanwhile, will develop strategies for long-term profitability and category leadership, as well as analyze brand assortment.
“We have a high number of products and multiple business categories with unique business objectives. We even have multiple audiences,” said Ricky Hernandez, Avery Products senior director of e-commerce sales and merchandising. “CommerceIQ helps us manage all those complexities, without having to devote a lot of people to it. We use CommerceIQ not only for the sales team, but our content team, supply team, and our logistics managers. Everyone is working from the same set of data, but it’s tailored to suit their individual needs.”